Survey of Electricity Market Simulation

8/6/2019 Survey of Electricity Market Simulation

1/70

Technical Report

Survey of Electricity Market

Simulation

Effective December 6, 2006, this report has been made publicly available in accordance

with Section 734.3(b)(3) and published in accordance with Section 734.7 of the U.S. Export

Administration Regulations. As a result of this publication, this report is subject to only

copyright protection and does not require any license agreement from EPRI. This notice

supersedes the export control restrictions and any proprietary licensed material notices

embedded in the document prior to publication.


2/70


3/70

EPRI Project ManagerR. Entriken

ELECTRIC POWER RESEARCH INSTITUTE3420 Hillview Avenue, Palo Alto, California 94304-1395 PO Box 10412, Palo Alto, California 94303-0813 USA

800.313.3774 650.855.2121 [email protected] www.epri.com

Survey ofElectricity Market Simulation

1010703

Final Report, November 2005

New York Independent System Operator

5172 Western TurnpikeAltamont, NY 12009

Project ManagerN. Bouchez


4/70

DISCLAIMER OF WARRANTIES AND LIMITATION OF LIABILITIES

THIS DOCUMENT WAS PREPARED BY THE ORGANIZATION(S) NAMED BELOW AS ANACCOUNT OF WORK SPONSORED OR COSPONSORED BY THE ELECTRIC POWER RESEARCHINSTITUTE, INC. (EPRI). NEITHER EPRI, ANY MEMBER OF EPRI, ANY COSPONSOR, THEORGANIZATION(S) BELOW, NOR ANY PERSON ACTING ON BEHALF OF ANY OF THEM:

(A) MAKES ANY WARRANTY OR REPRESENTATION WHATSOEVER, EXPRESS OR IMPLIED, (I)WITH RESPECT TO THE USE OF ANY INFORMATION, APPARATUS, METHOD, PROCESS, ORSIMILAR ITEM DISCLOSED IN THIS DOCUMENT, INCLUDING MERCHANTABILITY AND FITNESSFOR A PARTICULAR PURPOSE, OR (II) THAT SUCH USE DOES NOT INFRINGE ON ORINTERFERE WITH PRIVATELY OWNED RIGHTS, INCLUDING ANY PARTYS INTELLECTUALPROPERTY, OR (III) THAT THIS DOCUMENT IS SUITABLE TO ANY PARTICULAR USERSCIRCUMSTANCE; OR

(B) ASSUMES RESPONSIBILITY FOR ANY DAMAGES OR OTHER LIABILITY WHATSOEVER(INCLUDING ANY CONSEQUENTIAL DAMAGES, EVEN IF EPRI OR ANY EPRI REPRESENTATIVEHAS BEEN ADVISED OF THE POSSIBILITY OF SUCH DAMAGES) RESULTING FROM YOURSELECTION OR USE OF THIS DOCUMENT OR ANY INFORMATION, APPARATUS, METHOD,PROCESS, OR SIMILAR ITEM DISCLOSED IN THIS DOCUMENT.

ORGANIZATION(S) THAT PREPARED THIS DOCUMENT

EPRI

NOTE

For further information about EPRI, call the EPRI Customer Assistance Center at 800.313.3774 ore-mail [email protected].

Electric Power Research Institute and EPRI are registered service marks of the Electric PowerResearch Institute, Inc.

Copyright 2005 Electric Power Research Institute, Inc. All rights reserved.


5/70

iii

CITATIONS

This report was prepared by

EPRI3412 Hillview AvenuePalo Alto, CA 94303

Principal InvestigatorR. Entriken

This report describes research sponsored by the Electric Power Research Institute (EPRI), andNew York Independent System Operator.

The report is a corporate document that should be cited in the literature in the following manner:

Survey of Electricity Market Simulation. EPRI, Palo Alto, CA, and New York IndependentSystem Operator, Altamont, NY: 2005. 1010703.


6/70


7/70

v

PRODUCT DESCRIPTION

This report documents results of an online survey developed by EPRI and ChristensenAssociates to investigate research and development in simulating electricity markets. The surveyshould not be considered as comprehensive, but rather as a limited representation of knownavailable power market simulation packages. Every effort was made to identify and contact abroad array of survey participants, yet some were missed and some chose not to participate.

Results & Findings

Questionnaires were sent to 35 groups and individuals found through a web search and word ofmouth. When the survey was closed May 31, 2005, 21 responses had been received. The range ofresponses is very informative. First, the number of sites that are active in electricity marketsimulation is quite large, indicating a growing level of maturity. Second, the variety ofapproaches shows true innovation, with commercial applications and research results beingdeveloped worldwide.

Challenges & ObjectivesSurvey responses, which offer insights into the variety and progress of research anddevelopment, will benefit engineers and economists who want state-of-the-art information onpower market simulation. Descriptions of the most current simulation technologies and extensive

references for further exploration also are contained in the document.

Applications, Values & UseFurther studies of this type are anticipated. Such studies will both teach the community how tobetter use this technology and drive the technology to new heights of achievement andapplication. Two areas that could extend benefits are more realistic market data and the study oflonger time frames. The most important contribution that this report and power marketsimulation can make to the debate over regulatory policy and industry reform is to helpstakeholders better understand each other and the implications of their decisions.

EPRI Perspective

EPRI has pioneered development and application of agent-based simulation for the study ofdecision-making in electricity markets. While use of computers to achieve this is relatively new,others have used people in similar experiments for some time. In fact, the recent Nobel Prize ineconomics was awarded to the pioneers of this type of investigation, termed ExperimentalEconomics. EPRIs agent-based efforts build on this experience directly, replacing people asparticipants with computer programs that make the same decisions. The goal is to continuefollowing developments in Experimental Economics and to create agents that can mimic humandecision-making processes, eventually mimicking and even predicting actual market behavior.


8/70

vi

ApproachThe project teams goal was not only to document the state of the art of power marketsimulation, but also to introduce the subject to two primary audiences: engineers and economists.The team devoted one chapter in the report, Scientific Background, to explain power systemphysics and engineering for economists and economic equilibria and experimentation for

engineers. This chapter also defines industry jargon used in the questionnaire.

KeywordsElectricity marketsAgent-based simulationEconomicsCompetitionInvestment


9/70

vii

ABSTRACT

This report documents an online survey of research and development to simulate electricitymarkets. The documents two primary audiences are engineers and economists. To help thesetwo groups better understand the state of the art in power market simulation, the reportoverviews the scientific background of power system physics and engineering for economistsand economic equilibria and experimentation for engineers. The final report also provides adictionary of industry jargon frequently used in conversation and published papers.


10/70


11/70

ix

ACKNOWLEDGMENTS

EPRI would like to thank all of the survey participants for their support not only in taking thetime to seriously consider their responses to the questionnaire, but in helping to ensure thequality of this report through conversations on its content and their reviews. While many peopleshare the success of this project, all remaining errors are the responsibility of the author.

Support from Nicole Bouchez and Bob DeMello of the New York Independent System Operatorwas crucial in setting the goals and reviewing the report for appropriate use in practice. ChrisSchlegel of Southern Company provided helpful comments and corrections. Finally, Hung-po

Chao of EPRI was an important advisor and supporter for this project.


12/70


13/70

xi

CONTENTS

1 INTRODUCTION ....................................................................................................................1-12SCIENTIFIC BACKGROUND.................................................................................................2-1

Power System Physics and Engineering...............................................................................2-1Generation........................................................................................................................2-2

Physical Characteristics...............................................................................................2-2Physical Limitations .....................................................................................................2-2

Units/Plants/Portfolios.............................................................................................2-2Minimum and Maximum Operating Point ................................................................2-3Reactive Power .......................................................................................................2-3Minimum Notification Time, Minimum Down Time ..................................................2-3Ramp Rates ............................................................................................................2-3Forced Outages ......................................................................................................2-4

Economic Characteristics ............................................................................................2-4Capital Costs...........................................................................................................2-4Fuel Cost and Incremental Heat Rate .....................................................................2-4Startup Costs ..........................................................................................................2-4Minimum Generation Costs.....................................................................................2-4

Reliability Characteristics.............................................................................................2-5Transmission ....................................................................................................................2-5

Physical Characteristics...............................................................................................2-6Lines, Transformers, Switches, Circuit Breakers, Capacitors .................................2-6Network Simplifications...........................................................................................2-6Neighboring Networks.............................................................................................2-6

Physical Limitations .....................................................................................................2-7Thermal Constraints................................................................................................2-7Stability Constraints ................................................................................................2-7

Economic Characteristics ............................................................................................2-7


14/70

xii

Capital Costs...........................................................................................................2-7Operating and Maintenance Costs..........................................................................2-8Congestion Revenues.............................................................................................2-8

Reliability Characteristics.............................................................................................2-8Load..................................................................................................................................2-8

Physical Characteristics...............................................................................................2-8Physical Limitations .....................................................................................................2-9Economic Characteristics ............................................................................................2-9Reliability Characteristics.............................................................................................2-9

Settlements .........................................................................................................................2-10Investment......................................................................................................................2-10Forward Markets.............................................................................................................2-10Day Ahead Markets ........................................................................................................2-10Real Time Markets .........................................................................................................2-10

Economics...........................................................................................................................2-11Modeling Economic Equilibria ........................................................................................2-11

Competitive Equilibria and Minimum Cost Production ...............................................2-11Nash Equilibria...........................................................................................................2-12Supply Function Equilibria .........................................................................................2-12

Experimental Economics ................................................................................................2-12Human Agents ...........................................................................................................2-13

Computer Agents.......................................................................................................2-13Mixed Systems...........................................................................................................2-13

3SURVEY RESULTS ...............................................................................................................3-14REFERENCES .......................................................................................................................4-1A SURVEY QUESTIONAIRE ................................................................................................... A-1

Product Information.............................................................................................................. A-1Use and Capabilities ............................................................................................................ A-1Availability ............................................................................................................................ A-2Real-Time Modeling Features.............................................................................................. A-3Day-Ahead Modeling Features............................................................................................. A-3Forward Market Modeling Features ..................................................................................... A-4


15/70

xiii

Market Participant Modeling Features.................................................................................. A-4Reporting Features............................................................................................................... A-4New Features....................................................................................................................... A-5Planned Features................................................................................................................. A-5Software Characteristics ...................................................................................................... A-5Platforms .............................................................................................................................. A-6

BSURVEY LETTERS .............................................................................................................. B-1Introductory Letter ................................................................................................................ B-1Instructions........................................................................................................................... B-2Update.................................................................................................................................. B-3Response ............................................................................................................................. B-4Review ................................................................................................................................. B-5


16/70


17/70

xv

LIST OF TABLES

Table 3-1 Use and Capabilities (1 of 2) .....................................................................................3-2Table 3-2 Use and Capabilities (2 of 2) .....................................................................................3-3Table 3-3 Availability..................................................................................................................3-4Table 3-4 Real-Time Modeling Features ...................................................................................3-5Table 3-5 Day-Ahead Modeling Features ..................................................................................3-6Table 3-6 Forward Market Modeling Features ...........................................................................3-7Table 3-7 Market Participant Modeling Features .......................................................................3-8Table 3-8 Demand Response and Load Modeling ....................................................................3-9Table 3-9 Reporting Features ..................................................................................................3-11Table 3-10 New Features ........................................................................................................3-12Table 3-11 Planned Features ..................................................................................................3-13Table 3-12 Software Characteristics........................................................................................3-14Table 3-13 Compatibility ..........................................................................................................3-15Table 3-14 Memory Usage ......................................................................................................3-16Table 3-15 General Comments................................................................................................3-17Table 3-16 Contact Information (1 of 2) ...................................................................................3-18Table 3-17 Contact Information (2 of 2) ...................................................................................3-20


18/70


19/70


20/70


21/70

2-1

2SCIENTIFIC BACKGROUND

This chapter provides the necessary background for economists and engineers to understandthe survey questions and responses. We first introduce the physical and engineering aspectsof electric power systems; so that economists can realize the important role of that the physicalsystem and its operations play in the simulation of an electricity market. These aspects oftenappear as constraints on, or limitations to, the free trade of energy and ancillary services. Nextwe introduce aspects of economic modeling so that engineers can appreciate the challenges indesigning and simulating power markets that accommodate the major physical and engineeringaspects of the system. The overall objective of the joint physical/economic system can be

thought of as serving load reliably and at least cost, but recognizing that because of physicalconstraints, the incremental cost of energy will vary both with time and location.

Power System Physics and Engineering

To properly simulate an electric power market, one must begin with a sufficient understandingof power system physics. The physical nature of the production, transport, and consumption ofelectric power is well documented and inviolate, leading to operations of power markets asdistant abstractions of physical laws.

Several layers of approximations occur between the operation of a power system and the

operation of a power market, which may or may not be significant in the operation of both.The physics is approximated in the engineering and construction of the system. The engineeringand design of a power system is meant, primarily, to promote safe and efficient operations, whileaccommodating errors and uncertainties of various sorts. The result is a grand machine that haslimited controls and limited operating latitude. Operators, further limited by system conditions,utilize available controls to keep the system within preset bounds. Finally, power markets, fortractability reasons, can incorporate only simplified versions of operational controls and latitudewhen allocating resources and determining prices.

Consider three examples of the treatment of transmission congestion, which is caused byoperating limits on the transmission system. First, the New Electricity Trading Arrangement in

the England and Wales market neglects transmission congestion during market operations [1, 2];all congestion costs are uplifted and charged to the transmission operator. Second, congestionin eastern U.S. electricity markets, including NYISO, the PJM Interconnection, and ISO-NE isan explicit component of market operations [3, 4]. Finally, in the current California market [5],neglected transmission congestion is uplifted and charged to consumers. Having little recourseto manage these costs, California consumers incur significant charges [5]. These three examplesshow that the physical system and the design of the market can have considerable implicationson the ability to reliably operate both the system and the market.


22/70

Scientific Background

2-2

These three examples demonstrate different approaches to both the engineering approximationsincorporated into the market and to the allocation of responsibility and control over financingand control of the system. In the NYISO market, details of the transmission system areincorporated, so that participants have control of their finances through the NYISO market.In the England and Wales market, little detail of the transmission system is incorporated intothe market, and the system operator is financially liable and operates the system. In California,little detail of the transmission system is incorporated into the market, the system operatorcontrols the system, and the participants are financially liable. California will soon change itsmarket to incorporate more details of the transmission system [6, 7].

The following subsections review the aspects of the power system that are addressed in thissurvey, and they are broken down into Generation, Transmission, and Load. Crosscutting thesebroad subjects are descriptions of their physical characteristics and limitations (where limitationscan be both static and dynamic), their economic characteristics, and their reliabilitycharacteristics.

Generation

Physical Characteristics

The vast majority of electric power generators produce alternating current (AC) power, and sincethe power is delivered in a wave fashion it can be viewed as having two components.

The first component, real power, is very intuitive in that this component seems familiar, becauseit is the major part of power production and consumption and can be transported and traded overvast distances. It is also, by far, what market participants think of in terms of trading.

The second component, reactive power, is less familiar, even esoteric. It is a minor part of powerproduction and consumption, but it is absolutely essential to the stability of the system. It cannotbe transported over long distances, making it a very local phenomenon. The local balance ofreactive power ensures that the voltage of the power system is maintained according to tightquality standards.

No market yet explicitly trades reactive power, but discussions have recently begun in the UnitedStates [8] regarding its economic exchange. This is because for a given generator unit, thepractice of generating reactive power can significantly reduce the generation of real power andthus reduce profits.

Physical Limitations

Units/Plants/Portfolios

Different markets utilize different levels of granularity when incorporating generation. Somemarkets incorporate the concept of unit-level generation and others handle generation at aportfolio level. Since we now know that the location of a generator can be an important aspect


23/70


2-3

of network stability, the level of detail about generation is tightly coupled with the level ofdetail in the network representation used by the market, which is described shortly. All easternU.S. electricity markets view generators at the unit level. That is, the network location and thecapability of each generator are important considerations for the electricity markets.

Minimum and Maximum Operating Point

Most large generating units have minimum power outputs. Sustained operation belowthis minimum level may be unstable, expensive, excessively polluting, unduly stressfulon equipment, or otherwise undesirable. Generators specify the minimum operating level.Schedules calculated for generators honor their minimum generation levels.

Generating units also have maximum power outputs levels. Each generator specifies botha normal and emergency upper operating limit. The normal upper operating limit reflectsthe maximum output of a generator under normal circumstances. Some generators maytake extraordinary measures to increase output above the normal level. The emergency upperoperating limit reflects the additional capacity of these units that is available under emergency

conditions. Schedules calculated for generators usually honor their normal upper operatinglimits. During emergencies however, the generator may be required to operate up to itsemergency upper operating limit.

Reactive Power

Generators normally have the ability to adjust their production or consumption of reactive powerindependently of their real power production. However, the range of a generators reactive powerproduction or consumption depends upon its output of real power. This range is fairly large whenthe output of real power is low, and more limited when the output of real power is high. Therelationship between maximum reactive power output (or consumption) and real power output is

non-linear. There are occasions when a generator is required to reduce its real power output sothat it can produce more reactive power.

Minimum Notification Time, Minimum Down Time

Most generators have an extensive start-up process, in part due to requirements that the unit notbe heated too quickly. The minimum notification time requirements specifies how much advancewarning a generator needs to reach its minimum generation level in accordance with its startingand loading process. This allows the unit to start up in a uniform fashion, according to its design.

Likewise, Most generators have a minimum down time that limits how soon the generator canbe turned on after it has been given instructions to shut down. This allows it to cool uniformly,

according to design.

Ramp Rates

Ramp rates are specifications that limit how quickly a unit can increase or decrease itsproduction of real power. Ramp rates are specified in units of megawatts per minute.A generator may specify up to three ramp rates over its operating range in addition toa ramp rate for regulation and an emergency ramp rate.


24/70


2-4

Forced Outages

Generating units can be forced to shutdown, or reduce their capacity (derate), for mechanicalproblems and other reasons. The forced outage rate is a measure of a generators reliability.A reliable generator will have a low forced outage rate; a less reliable generator will have ahigher forced outage rate. The expected (or average) forced outage rate of a generator depends,in large part, on the type and complexity of a generators technology. Hydro and nuclear units,for example, are expected to have low forced outage rates. Quick-start units are expected to havehigher forced outage rates. Since the production and consumption of electricity must always bein perfect balance, forced outage rates have reliability implications for planning and operations,which are described later.

Economic Characteristics

The economic characteristics of a generating unit imply the incentives for efficient operation.For instance, the owner will resist operating at a loss and will try to maximize profit.

Capital Costs

Generation capital costs are very intensive; a moderately sized (500 MW) coal unit will costabout five billion dollars. There is a tendency for per kW unit of capacity costs to be highestfor the most efficient technologies and vice versa. Combined-cycle units, which are efficientand relatively less expensive to construct, require a fairly expensive fuel (natural gas).The most efficient technologies tend to be large and slow, while the cheapest and least efficienttend to be small and very responsive. Most generation units have life spans of 50 years or longer.

Fuel Cost and Incremental Heat Rate

The incremental heat rate is the incremental amount of fuel (MBTU/hr) or cost ($/hr) neededby a generator to produce energy at a slightly increased rate (MW). The incremental heat rate(BTU/KWh) is used to determine the most cost effective means of adjusting generation tomatch the ever-changing load. The incremental heat rate of a generator changes as its operatinglevel changes. Constant incremental heat rates are often assumed as a first order approximation,but truly efficient system operations require that this conversion be treated as varying.

Startup Costs

Generating units require not only time to warm up and synchronize, but they often requirespecial fuel mixes to start up. The combination of these factors causes generating units toincur a cost, called a startup cost, each time the unit is started.

Minimum Generation Costs

A generator incurs a cost when running at its minimum operating point. This cost, referredto as the minimum generation cost, has units of $/hr. This is also known as no-load cost.


25/70


26/70


2-6

The point where the distribution system connects with the transmission system is calleda substation. Distribution networks generally have a branching topology, like trees, andare without loops. The transfer of electricity from the substation to a load generally hasonly a single path.

Distribution systems play an important role in the retail electricity markets but have a minor

role in wholesale electricity markets. Hence wholesale electricity markets rarely representdistribution systems, but instead treat substations, which are the interfaces between transmissionand distribution, as the point of delivery of power. Therefore, distribution systems will not bediscussed further in this report.


Lines, Transformers, Switches, Circuit Breakers, Capacitors

These lines carry real power over long distances and they can also consume reactive power.

Conversions between the voltage levels are handled by transformers, which can be extremelylarge, expensive, and difficult to transport and replace. Switches are used to alter the topologyof the network and circuit breakers and relays are used to protect it from damage. Finally,capacitors, some with crude control settings, are use d to provide limited reactive power tosupport stability.

Network Simplifications

The many components of a transmission system are not represented explicitly in markets. Sincegeneration and load, as linked by the transmission system are the primary focus of power marketoperation, it is possible to use the concept ofequivalent circuits [11, 12] to accurately simplify

the AC network representation to focus on only the primary elements.The equations for an AC circuit are non-convex, making them difficult to solve on the routinebasis required by most markets. Given a nominal power flow, the use of linear sensitivityparameters offer a relatively accurate way to convert an AC circuit representation into a directcurrent (DC) equivalent, which can be reliably solved. Some markets incorporate AC networksand fall back on DC equivalents as needed. Other markets use only DC equivalents.

A less accurate simplification of the transmission network is to aggregate nodes (substations orbusses) intozones. Sometimes these aggregations are very broad. For instance the currentnetwork of the CA-ISO has three zones with a radial (tree-like) network for their control area.Such a network has very simple model, but as noted earlier congestion on the network is not

fully accounted in the schedules and prices of the market.

Neighboring Networks

Rarely does a power system or power market operate in isolation. Most power systems adjoinand are connected to other power systems, each called a control area. The connection betweencontrol areas is called an interface and is made up of one or more transmission lines. Electricitymay flow from one control area to another over the interface, and it is often traded between


27/70


2-7

control areas. In the simplest case, electricity is imported or exported across the interfaceaccording to fixed schedules. In other cases, bids to purchase or offers to sell electricity comefrom buyers or suppliers outside the control area. So, a representation of the neighboring networkis incorporated into the market. In the most sophisticated case, an equivalent circuit for theneighboring network, including the suppliers generating units, is incorporated into the market.


Transmission lines, with attendant components, have so-called thermal and stability constraints.The tighter of which will be used to limit the amount of power transferred across the line whenthe market is cleared. When these constraints are active, the network is said to be congested.We briefly explain the reasons for thermal and stability constraints.

Thermal Constraints

High temperatures that damage equipment and line sagging are the two main contributors tothermal constraints.

Transmission lines and their components are subject to resistive losses, which heats them up.First, air currents typically cool these system components passively. Some components, liketransformers will have heat exchangers and fans.

As transmission lines become hotter, they lengthen due to thermal expansion. As they lengthenthey sag, and can become too close to the ground, or objects connected to the groundlike trees.

Stability Constraints

In order to maintain the local balance of reactive power the flow on some transmission linesis subject to stability constraints. Long transmission lines and loads consume reactive power.As the power transfer on a line increases, its reactive power consumption increases. Therefore,when a local area has only a limited supply of reactive power, the import of power into theregion across the line must be restricted.


Capital Costs

The costs of new transmission lines are on the order of hundreds of thousands of dollarsper mile [13], not including right-of-way costs. The latter present risks and costs that varysignificantly by location. Transmission lines can have life spans of up to 50 to 100 years underroutine maintenance. Often though, component parts and conductors are replaced to increasethe transfer capability of the corridor. Such upgrades have a mixture of characteristics frommaintenance and investment.


28/70


2-8

Operating and Maintenance Costs

Operations and maintenance costs for transmission systems are generally small compared toother costs.

Congestion Revenues

When the flow on a transmission line is not constrained, the price of electricity at each endof the line will be equal (neglecting losses), as if the two locations operate as part of the samemarket. When the flow on a transmission line is constrained, the prices can separate, as if thetwo locations operate as separate markets. The difference between the two prices, multipliedby the flow on the line constitutes a potential revenue source for the owner of the line and iscalled the congestion rent. The situation is as if the owner can offer to buy low at one end ofthe line and sell high at the other, pocketing the difference.

Congestion Revenue Rights (CRRs) are handled differently across power markets. In some

markets, the transmission owner auctions them off. In other, markets the consumers are endowedwith CRRs. To maintain a balance of funds, it is important to account for these revenues and toassign them in some way.

Reliability Characteristics

A transmission interface is a form of constraint that ensures that the transmission system cancontinue to function after a key transmission line is forced out. It is typically represented asa regional boundary across which many transmission lines can import or export power. Aninterface constraint will limit the combined import or export of power across the boundaryso that if a one line fails, the remaining lines can continue to carry the power. In a sense,

it is meant to hold transmission in reserve.

Load

Load, or the demand for electric power, is analogous to generation in many ways. Becauseof this, this section follows closely the structure of the Generation section and includes manyreferences.


Power markets typically represent load at the substation level or higher, depending on the levelof detail represented in the network model. Some markets, may trade at pre-specified tradinghubs, where there can be risks of paying congestion rents between the generator or load and thehub. Most loads consume real power, while large inductive loads like motors and transformersconsume reactive power.


29/70


2-9

Load is the most variable component of the power system. The rest of the system is designed toanticipate and follow changes in the load. There are predictable seasonal and daily fluctuations,that make load more predictable, but the major component of uncertainty is the weather. Marketsmay trade large portions of power ahead of the time when it is actually produced and consumed,based on the level of predictability of the load, but there is always a level of error in these

forecasts that necessitates the management of the real-time balance of supply and demand forelectric power.


Industrial loads can be switched, and some markets accommodate this ability with features toschedule loads within certain parameters, much in the way that generation is scheduled. Loadswill require notice to increase or decrease, which corresponds to the minimum startup andshutdown times of generation. They can also require minimum load levels, so that they are notcompletely shut off from supply. The rate of change of the load may also be specified, analogousto a generation ramp rate.


When an industrial or even retail load offers to be scheduled, it will also specify how much itneeds to be compensated for this flexibility. In this case, the load is said to be price responsive.Load is known to be price responsive over multi-month durations, but without explicit exposureto prices and market features in the short term, most of the demand for electric power is not priceresponsive. For this reason, when load is shut down, the process tends to be indiscriminate.

Reliability Characteristics

Absolute shortages of energy in a power system force system operators to shut down load.Before this is done, all efforts are made to acquire and ramp up reserves and other emergencysupplies. Simulations of electricity markets often show price spikes as supply becomes tight.

An evolving response on the load side is to install emergency generation that can be quicklyswitched on to supply local loads. Hospitals and other critical infrastructure operate this way.The reason that this response is evolving is because more people are installing generation andat the same time realizing the benefits of selling power on the market. Residences can havephotovoltaic generation and larger industrial sites can have quick start generation.

As markets evolve, more of this form of generation can be used as a source of profit in additionto a way to provide insurance against blackouts. Since this generation is often sited past thesubstation, it can look to the wholesale markets like a form of price response (or weatherinsensitivity in the case of photovoltaic devices).


30/70


2-10

Settlements

Trading of power market products occurs over different durations and at different points in time.For instance, it is typical to trade in over-the-counter (OTC) markets for power contracts thathave monthly or seasonal durations. Spot power markets, whether the day ahead or real time

have products traded having durations of one hour or less. Note also that all of these trades maybe buys and sells of the same megawatt hour of power passing from one party to the next. Thisis referred to as multiple settlements, or multi-settlement.

Trading decisions in earlier markets necessarily involve expectations of uncertain conditions inlater markets, while trading decisions in later markets can depend heavily on what trades havebeen settled in earlier ones. For this reason, the effects of multiple settlements are an importantaspect of simulating power markets.

Investment

Investment in the power system is not normally thought of as a market with settlement, but itcan be approached in this way to study issues of resource adequacy, new entry, and long-runefficiency. The traded product is physical capacity and there can be multiple buyers and sellers.All power market investment decisions have implications for decades.

Generation investments decisions occur as short as two years ahead

Forward Markets

The term forward market is a catchall for trades that occur in advance of the spot market. Manydifferent products are traded in many different fashions in the forward markets. These marketsmay or may not follow preset schedules.

Day Ahead Markets

Day ahead (DA) markets along with real markets are often called spot markets, which can lead tosome confusion. The DA markets follow a trading schedule to clear and settle some time duringthe day before power flows. The trading covers the entire following day, which is typicallydivided into hourly intervals. The main reasons for trading in the day ahead are to accommodatethe time constraints for startup and shutdown and to acquire sufficient reserves. Regulations mayalso stipulate that the vast majority of trading should be completed by day ahead in order to

allow system operators to focus on operating the system, rather than trading power.

Real Time Markets

Real-time trading focuses on settling balancing energy and transmission. Some markets arecontemplating real time reserve settlement. The amount of energy traded in real time should besmall compared to the total power transfer in order to facilitate efficient operations and systemstability.


31/70


2-11

Economics

Earlier sections on generation, transmission, and load have short descriptions of their respectiveeconomics. This section takes the system as a whole, and describes economic modeling thatforms the foundation for power market settlement and simulation. The focus is on the short-term

scheduling and operations of the power system with single settlement.

Modeling Economic Equilibria

Under vertically integrated utilities, all decisions across the power system are integrated andbalanced by the organization of the firm. When markets are introduced, single firms no longerharbor this integration and balance and we rely on multiplier firms to interact through marketmechanisms [14].

Rather than centralized control to minimize costs to the consumers, the nature of the modelbecomes that of an economic equilibrium, wherein independent, profit-maximizing agents make

buy and sell decisions. When equilibrium is reached, no one agent can profitably choose tochange its buy or sell decision.

In this section, we describe three types of equilibrium models, the Competitive Equilibrium,the Nash Equilibrium, and the Supply Function Equilibrium. All of these equilibrium modelshave a focus on tractability and thus rely on simplifying assumptions that can be quiteunrealistic. Nevertheless, they represent important benchmarks because they are well understoodand have shed insights on the detailed behaviors and interactions that make up markets of manydifferent forms.

The issue of tractability is has consequences for this type of modeling, in that the violation ofthe simplifying assumptions will fail to yield any useful information about the market. The fact

that of generation units have minimum startup and shutdown times is typical of a real-worldcharacteristic that rends most equilibrium models useless. Therefore it is common to assumethese limitations away.

Competitive Equilibria and Minimum Cost Production

The competitive equilibrium assumes that no participant will attempt to game the market;generators offer at marginal cost, loads offer at marginal value, and transmission is a price taker.It is well understood and quite tractable under most circumstances.

Traditional power system simulations, which rely on minimizing the cost of production, in effect,

reproduce the competitive equilibrium. These traditional simulations have been the tools ofchoice for vertically integrated utilities, because they model centralized decision-making undercost-based regulation.

The competitive equilibrium also has the important property that it produces the most efficientterms of trade from the standpoint of overall societal benefit. Therefore, market designers striveto organize their markets so that they are always competitive, and the competitive equilibriumserves as a very important market performance benchmark.


32/70


33/70


2-13

The concept of market simulation used in this survey involves extensions on these sorts ofall-human experiments. The following sections describe first the use of human agents, butthen consider the use of computer agents that mimic human behavior, and finally mixedsystems of human and computer agents.

Human Agents

Notable early references on experimental economics are [28, 29, 30]. Two advantages ofusing human agents are that they best represent actual human behavior and that human agentscan often deal with complex decisions. Two disadvantages are that the reasoning behind humanbehavior is not always transparent and conducting these experiments can be relatively expensivein time and other resources.

Computer Agents

In computer science, a computer agent is an autonomous piece of software, able to makedecisions to reach a goal. Early applications of agents are in packet routing over communicationnetworks. The Unix operating system, for instance, introduced services for e-mail, file transfer,and remote access through the use of agents (or daemons) that lay in wait and respond torequests to route and process packets for these various services.

In power market simulation, computer agents are meant to replace human agents, makingbid decisions to maximize profits [31, 32, 33]. Two advantages of computer agents are thattheir decision-making environment can be precisely controlled and analyzed and thatsuch experiments can be run parametrically in the thousands with little added expense.A disadvantage is that it can be difficult to teach computer agents to make complexdecisions.

Since computer agents are meant to substitute for human ones, their behavior must bebenchmarked against human behavior under similar circumstances. For this reason,human experimentation will lead and serve as a foundation for other techniques.

Mixed Systems

One perspectives for the use of mixed systems of human and computer agents is that computeragents can automate simpler aspects of a market, like bidding marginal cost for a competitivefringe or price taking players. Another perspective is that of a single player competing in amarket against the computer. This mode is useful for training and for exploring strategies and

market behaviors.


34/70


35/70

3-1

3SURVEY RESULTS

In early January 2005, EPRI conducted an on-line search for active research and developmentin power market simulation. Informal conversations with leaders in the area helped to identifyeven more prospective participants.

This survey was begun on March 9, 2005 with introductory e-mails sent to prospectiveparticipants. Follow-up posts, e-mails, and phone calls helped to ensure that all prospectiveparticipants were aware of the study and how it would be conducted. All participants wereoffered full copies of the final report and the opportunity to review and revise their responses.

Very few revisions were submitted. The character of the revisions was to update the availablefeatures, based on recent developments, and to include more descriptive comments. The firstdraft of the report was completed in late May 2005 and there was a two-month review period,during which all of the respondents made corrections and suggestions for improving this reportand future ones.

An automated on-line web site was used to collect the initial responses used to form the draftreport. This technology allowed the participants to submit multiple responses for multipleproducts and to pause and continue their responses. The entire questionnaire required about15 minutes to complete. As each participant completed a questionnaire, their responses wereautomatically sent back to them in an e-mail as a first level of confirmation and validation.

The second and final level of validation was the review of this report.


36/70

Survey Results

3-2

Table 3-1Use and Capabilities (1 of 2)

Simulation Type Problem SizeH

u

manEx

perim

en

ts

Agen

t-Based

Experim

en

ts

Equilibrium

Com

putation

s

Buses

Transmis

sionLin

es

G

enera

tingUnits

Particip

an

ts

Interd

epen

den

t

TimeP

erio

ds

Product Name q2a q2b q2c Q3a Q3b Q3c Q3d Q3e

MAPS 50,000 100,000 7,500 175 8,7

EP 1 1 1 limited by solution time 0 0

MELBOURNE 0 1 0 100 0 100 100 1000

EMCAS 1 1 1 2,000 2,400 400 ? 87

PLEXOS 0 0 1 15,000 18,000 2,000 1,000 800,0

MADERE 0 1 0 ? ? ? ? 10

EE 1 0 1 4 5 40 16

ENERGY 2020 1 1 1 110 2,000 50,000 80 5

NetaSim 0 0 1 0 0 200 30

TSCM 0 0 1 53 71 19 5

COMPETES 0 0 1 ~20 ~40 ~1,000 20

CTCEM 0 0 1 ~100 ~800 ~3,000 ~800

PowerACE 0 1 0 1 1 300 100 175,0

LTEPM 0 0 1 1 0 500 1 14,4

Eureca 0 0 1 30 30 15,000 1 14,4

PD EMPS PriceForecast

0 0 1 30 30 15,000 1 14,4

IPSPE Model 0 0 1 8 20 1,500 0 6

STEMS-RT 1 1 1 180 200 200 50

Market Sim 0 0 1 2,500 5,000 500 500 8,0

GENERIS 0 1 0

POWERS 0 0 1


37/70

Table 3-2Use and Capabilities (2 of 2)

Minimum Computer System Resources

A

vailable

Memory

Ava

ilableDisk

Space

P

rocessor

Ar

chitecture

Product Name q4a Q4aT1 q4b Q4bT1 q4c

MAPS 1 1 GB 0 0

EP 0 0 0

MELBOURNE 0 0 0

EMCAS 1 2 GB 1 1GB 0

PLEXOS 0 0 0

MADERE 0 0 0

EE 0 0 0

ENERGY 2020 1 512 MB 1 5 GB 1 WindoNetaSim

TSCM

COMPETES 1Sufficient to run AIMMSand PATH

1Sufficient to run AIMMSand PATH

1Sufficieand PA

CTCEM 1Sufficient for runningPATH

1Sufficient for runningPATH

1SufficiePATH

PowerACE 0 0 0

LTEPM 0 0 0

Eureca 0 0 0


0 0 0

IPSPE Model 0 0 0STEMS-RT 1 150 MB 1 10 MB 1 Java 1

Market Sim 0 0

GENERIS

POWERS


38/70

Survey Results

3-4

Table 3-3Availability

Availability

Av

ailableto

N

ewUsers

Commercially

Other

Comment

Product Name q5a q5b q5c q5cT1Oth

MAPS 1 1

EP 1 1 on request

MELBOURNE 0

EMCAS 1 1

PLEXOS 1 1

MADERE 0

EE 0ENERGY 2020 1 1 1 Available as part of a consulting project

NetaSim 0

TSCM 0

COMPETES 1 1 By special arrangement. Prices negotiable

CTCEM 1 GAMS code available with permission from Dr. U. Helman at F

PowerACE 0

LTEPM 1 1 NA

Eureca 1 1


1 1 Marketed by POWEL ASA

IPSPE ModelSTEMS-RT 1

Market Sim 1

GENERIS

POWERS


39/70

Table 3-4Real-Time Modeling Features

Real-Time Market

Re

al-Time

E

nergy

Re

al-Time

Congestion

Rihts

DC

Tran

smission

Re

al-Time

Reserves

Re

al-Time

Interfaces

S

ecurity

Constrained

Multi-Period

Ramp

Constraints

Other

Char

acteristics

Product Name q6a q6b q6c q6d q6e q6f q6g q6h q6i

MAPS 1 1 1 1 1 1 1 0

EP 1 1 1 1 1 1 1 1

MELBOURNE 0 0 0 0 0 0 1 0EMCAS 0 0 0 0 0 0 0 0 0

PLEXOS 1 1 1 1 1 1 1 1 1 ALL

MADERE 0 0 0 0 0 0 0 0

EE 1 1 0 0 0 0 1 0

ENERGY 2020 1 1 1 1 1 1 1 0 Ancillary Services

NetaSim

TSCM 1 0 0 0 1 1 1 0 1 generation and transm

COMPETES 1 1 1 0 1 1 1 0 1

Note: This is a single sgenerally be used to simforward and real-time minclude reserves. Can b

CTCEM 1Simulates single settlemahead, contracts togethexogenous forward con

PowerACE 1 0 0 1 0 0 1 1

LTEPM 1 0 0 1 0 1 1 0

Eureca 1 1 1 1 0 1 1 1

PD EMPS PriceForecast 1 1 1 1 0 1 1 1

IPSPE Model 0 0 0 0 0 0 0 0

STEMS-RT 1 1 1 1 1 1 0 0 0

Market Sim 1 1 1 1 1 1 1 1 1 Other ancillary and conGENERIS

POWERS


40/70

Survey Results

3-6

Table 3-5Day-Ahead Modeling Features

Day-Ahead Market

D

ay-Ahead

Energy

D

ay-Ahead

C

ongestion

Rights

D

ay-Ahead

Reserves

D

ay-Ahead

Interfaces

Day

-AheadUnit

Commitment

Security

Constrained

M

ulti-Period

Ramp

C

onstraints

Other

Characteristics

Product Name q7a q7b q7c q7d q7e q7f q7g q7h q7i

MAPS 1 1 1 1 1 1 1 0

EP 1 1 1 1 1 1 1 1

MELBOURNE 1 0 0 0 0 0 1 0

EMCAS 1 0 1 0 1 1 1 1 1 bilateral contracts

PLEXOS 1 1 1 1 1 1 1 1 1 ALL

MADERE 1 0 0 0 0 0 0 0

EE 0 0 0 0 0 0 0 0ENERGY 2020 1 1 1 1 1 1 1 0

Native load, bilateral (Hour-Ahead, Month

NetaSim

TSCM 1 0 0 1 0 1 1 0 1Different granularity RT nodal)

COMPETES 1 1 0 1 0 1 0 0 1Reserves could be insystem, real-time and

CTCEM

PowerACE 1 0 1 0 1 0 1 1

LTEPM 1 0 1 0 1 1 1 0 0

Eureca 1 1 1 0 1 1 1 1

PD EMPS Price Forecast 1 1 1 0 1 1 1 1

IPSPE Model 1 0 0 1 1 0 1 fuel markets

STEMS-RT 1 1 1 1 0 1 0 0 0

Market Sim 1 1 1 1 1 1 1 1

GENERIS

POWERS


41/70

Table 3-6Forward Market Modeling Features

Forward TradingForw

ardEnergy

Fwd

Congestion

Rights

Forward

R

eserves

In

vestment

N

ewEntry

Other

Cha

racteristics

D

escribe

Product Name q8a q8b q8c q8d q8e q8f q8T1

MAPS 1 1 1 1 1

EP 0 0 0 0 0

MELBOURNE 0 0 0 0 0

EMCAS 1 0 0 0 1 0

PLEXOS 1 1 1 0 1

MADERE 0 0 0

EE 0 0 0 1 1ENERGY 2020 1 1 1 1 1

NetaSim

TSCM 1 0 0 0 0 1 Forward price cap as a proxy to new entry

COMPETES 1 1 0 0 0 1Reserves could be included with modification.approximation of energy market.

CTCEM

PowerACE 1 0 1 1 1

LTEPM 1 0 1 1 1

Eureca 1 1 1 1 1


1 1 1 1 1 Hydrological variation (60 inflow scenarios)

IPSPE Model 1 0 1 fuel marketSTEMS-RT 1 0 1 0 0 0

Market Sim

GENERIS

POWERS


42/70

Survey Results

3-8

Table 3-7Market Participant Modeling Features

Market Participant Modeling

Cournot

Bertrand

Su

pplyFunction

Equilibrium(SFE)

MPEC

Heuristic

Other

Describe

Product Name q9a q9b q9c q9d q9e q9f q9T1

MAPS 0 0 1 0 1

EP

MELBOURNE 1 1 0 0 1

EMCAS 1 1 1 0 1 1 Learning and adaptation

PLEXOS 1 1 0 0 1 1 LRMC Recovery

MADERE 0 0 0 0 1EE 1

ENERGY 2020 1 1 1 1 1 1

NetaSim

TSCM 1 0 0 1 0 1 EPEC, Subgame Perfect Two stage Nash

COMPETES 1 1 0 0 0 1 Conjectured Supply Functions

CTCEM 1 1 0 0 0 0

PowerACE 0 0 0 0 0

LTEPM 0 0 1 0 1

Eureca 0 0 1 1 0


0 0 1 1 0 Water Value Method - Multi Area

IPSPE Model

STEMS-RT 0 0 0 1 1 0

Market Sim

GENERIS

POWERS


43/70

Table 3-8Demand Response and Load Modeling

Demand Response

Is

DemandPrice

Responsive?

Hard-wired

Elasticities

U

ser-Specified

Elasticities

U

ser-Specified

Reductions

Other

Describe

W

holesalePrice

Caps

Fixed

Product Name q10 q10a q10b q10c q10d q10dT1 q11 q12a

MAPS 1 1 1 1 1

EP

MELBOURNE 0 1 1

EMCAS 1 1 1 1 1 1

PLEXOS 1 1 1 1 ALL Option Available 1 1

MADERE 1 1 Demand devised in fourtypes of consumers witha % of their consumptiondirectly contracted withone supplier and theremaining part boughton the spot market. Forthe bilaterally contractedpart, they may switch toanother supplier if thepricedifference

0 1

EE 1 1 1 1

ENERGY 2020 1 1 Full multi-fuel energydemand forecastingmodel with causaldynamics

1 1


44/70

Survey Results

3-10

Table 3-8Demand Response and Load Modeling (Continued)

Demand Response

IsDemandPrice

Responsive?

Hard-wired

Elasticities

User-Specified

Elasticities

User-Specified

Reductions

Other

Describe

WholesalePrice

Caps

Fixed

NetaSim

TSCM 1 1 1 0

COMPETES 1 1 1 0 1

CTCEM 1 1 0 1

PowerACE 1 1 Graphical output andcomma-separated valuefiles.

1 1

LTEPM 0 1 1

Eureca 0 1 1


0 1 1

IPSPE Model 0 0 1

STEMS-RT 1 1 1 1 Market Sim

GENERIS

POWERS


45/70

Table 3-9Reporting Features

Diagnostic and Reporting Features

Product Name q13T1

MAPS Generation, costs, spot prices, and line and interface flows available on an hourly basis

EP

MELBOURNE A GUI gives the development of price and costs, demand and supply. All data is logged

EMCASBasic reports include locational marginal prices (LMPs) at each bus, generator output, tagent (including GenCo, TransCo, DistCo, DemCo) profitability, consumer costs, zonal planned outages, forced outages.

PLEXOS

diagnostics:- various algorithm diagnostics, LP infeasibility reports, infeasibility repair (auto)reporting:- solution querying and tabulation, graphical solution viewing, automated report generat

MADERE

EE

ENERGY 2020All the variables in the model can be viewed interactively or exported to a text file, whichother third party software. The model can be interfaced, in general, with any third party

NetaSim

TSCM nodal prices, production quantities, forward commitments, social welfare.

COMPETES AIMMS report generation system is very flexible, and can be readily used to generate w

CTCEM GAMS report generation capabilities.

PowerACE Graphical output and comma-separated files.

LTEPM

Eureca


Quite poor... but all the simulation data is available in text files. Reporting routines consorganize all the simulation data.

IPSPE Model text output

STEMS-RT All data in comma-separated files.

Market Sim

GENERIS

POWERS


46/70

Survey Results

3-12

Table 3-10New Features

New Features

Describe

Product Name q14 q14T1

MAPS 0

EP

MELBOURNE 0

EMCAS 1 Graphical user interface

PLEXOS 1 refer to web site

MADERE 0

EE 1 Now runs in near continuous time.

ENERGY 2020 1

The latest features are additional detail in the number for forward markets(they are now essentially unlimited), time periods, economic sectors andpollution accounting including emissions reduction curves. We also now

interface our model with the PowerNetaSim

TSCM 1 Product is under development not released yet

COMPETES 0

CTCEM 1Note: This formulation also available in PLEXOS (http://www.draytonanalyand COMPETES (http://www.ecn.nl/ps/research/grp2/index.en.html and w

PowerACE 0

LTEPM 1

Eureca 1

PD EMPS Price Forecast 1

IPSPE Model 0

STEMS-RT 1 Reserves, Interfaces, Security Constraints, MPEC (experimental)

Market Sim

GENERIS

POWERS


47/70

Table 3-11Planned Features

Planned Features

Describe

Product Name q15 q15T1

MAPS 1 Enhanced modeling of intermittent resources.

EP

MELBOURNE 0

EMCAS 1 Long term expansion planning, hydro cascade simulation

PLEXOS 1Version 5.0 is complete new version: new interface, database structures, emany, many new features

MADERE 0

EE 0

ENERGY 2020 1 We continually add new features in response to market and client demand

NetaSim

TSCM 0

COMPETES 1Exogenous forward contracts have been included in a pre-release versionreal-world transaction constraints for transmission rights. Extension to a la

CTCEM 0

PowerACE 1 bilateral trading, emissions trading, derivatives trading

LTEPM 1

Eureca 1

PD EMPS Price Forecast 1 We are using an older version of Powels MPS model and will update it in

IPSPE Model 1 ongoing research, e.g. reserve, risk, ...

STEMS-RT 1 multiple settlements

Market Sim

GENERIS

POWERS


48/70

Survey Results

3-14

Table 3-12Software Characteristics

Software Form Third-Party SofSo

ftwareLibrary

Stand-Alone

Application

WebAccessible

C

lient-Server

Architecture

Yes/No

Software

Product Name q16a q16b q16c q16d q17 q17T1 q1

MAPS 0 1 0 1 1 Hummingbird Exceed Separ

EP

MELBOURNE 1 0 0 0 1 JADE Separ

EMCAS 0 1 0 0 1 Linear optimizer Bundle

PLEXOS 1 1 1 0 1 Access Separ

MADERE 0 1 0 0 0 None EE 0 0 0 1 1 LP Solve Separ

ENERGY 2020 0 1 0 0 1 Promula Separ

NetaSim

TSCM 0 1 0 0 1 Mathlab Separ

COMPETES 0 1 0 0 1 AIMMS Separ

CTCEM 0 1 0 0 1 PATH Separ

PowerACE 0 1 0 0 1 MS Access (to be changed toan open source product)

Separ

LTEPM 0 1 0 0 0 None

Eureca 0 1 0 0 1 LP Separ

PD EMPS Price Forecast 0 1 0 0 1 None IPSPE Model 0 1 0 0 1 CPLEX solver Separ

STEMS-RT 1 1 1 1 1 Java 1.4 Separ

Market Sim Separ

GENERIS

POWERS


49/70

Table 3-13Compatibility

Data Compatibility Co

R

eads

Spre

adsheets

W

rites

Spre

adsheets

R

eads

Da

tabase

W

rites

Da

tabase

CIM

Market

Ext

ensions

Readsand

WritesText

Files

Readsand

Wri

tesXML

Files

Windows

Linux

S

olaris

Product Name q18a q18b q18c q18d q18e q18f q18g q19a q19b q1

MAPS 1 1 1 1 0 1 0 1 0 0

EP

MELBOURNE 0 0 0 0 0 1 0 1 1 0

EMCAS 0 1 0 0 0 1 1 1 1 1

PLEXOS 1 0 1 1 0 1 0 1 0 0

MADERE 0 0 0 0 0 1 0 1 0 0

EE 0 0 0 0 0 1 0 1 0 0

ENERGY 2020 1 1 1 1 1 1

NetaSim

TSCM 0 0 0 0 0 0 0 1 0 0

COMPETES 1 1 1 1 0 1 0 1 0 0

CTCEM 0 0 0 0 0 1 0 1 1 0

PowerACE 0 0 1 1 0 1 1 1 0 0

LTEPM 1 1 0 0 0 0 0 1 0 0

Eureca 1 1 0 0 0 1 0 1 0 0


1 1 0 0 0 1 0 1 0 0

IPSPE Model 0 0 0 0 0 1 0 1 1 1

STEMS-RT 0 1 0 0 0 1 1 1 1 1

Market Sim

GENERIS

POWERS


50/70


51/70

Table 3-15General Comments

Comments

Product Name q21T1

MAPS

EP

MELBOURNE

EMCAS EMCAS has been used to study electricity markets both in the U.S. and abroad.

PLEXOS

MADERE

EE

ENERGY 2020 ENERGY 2020 has a 25-year track record in simulating and analyzing electricity

NetaSim

TSCM Model is currently being developed as part of a Ph.D. thesis. It is not being comm

COMPETES See website for the ECN COMPETES model http://www.electricitymarkets.info/ iFor documentation, see the following paper:Hobbs, B.F. and F.A.M. Rijkers Modeling Strategic Generator Behavior with ConResponses in a Mixed Transmission Pricing System I: Formulation.IEEE Trans. Power Systems. vol.19. 2 (2004). pp. 707 - 717.

CTCEM For documentation, see the following paper:C.J. Day, B.F. Hobbs, and J.-S. Pang, Oligopolistic Competition in Power NetwoFunction Approach, IEEE Trans. Power Systems, 17(3), 597-60

PowerACE The project is described at www.powerace.de

LTEPM

Eureca

PD EMPS Price Forecast EMPS is a multi-area simulation tool, which uses water value method (dynamic pmid-long term analysis (1->15 years) in the Nordic Power Market for its outstand

hydropower production.

IPSPE Model network model, using NTC or PTDF included

STEMS-RT Multi-process support depends on Java implementation.

Market Sim

GENERIS

POWERS


52/70

Survey Results

3-18

Table 3-16Contact Information (1 of 2)

ProductName

Name ofContact

Company Address1 Address2 City

MAPSGlennHaringa GE Energy

Building 2,Room 637 1 River Road Schenectady

EPRobertThomas

Cornell University

MELBOURNEClemensCzernohous

UniversittKarlsruhe (TH)

InformationManagementand Systems

Englerstr. 14 Karlsruhe

EMCASRichard R.Cirillo

Argonne NationalLaboratory

9700 S. CassAvenue

Argonne

PLEXOSGlennDrayton

Drayton Analytics PO Box 13North

AdelaideAdelaide

MADEREFlorenceDubroeucq

EDF1 avenue duGeneral de Gaulle

Clamart

EE Bart WilsonGeorge MasonUniversity

4400 UniversityDrive

MSN 1B2 Fairfax

ENERGY2020

Jeff AmlinSystematicSolutions, Inc.

4420 Snypp RoadYellowSprings

NetaSim Derek BunnLondon School ofEconomics

TSCM Shmuel Oren UC Berkeley IEOR Dept.

Room 4119,

EtcheverryHall Berkeley

COMPETES Wietze LiseEnergy ResearchCentreof the Netherlands

Badhuisweg 3 Amsterdam

CTCEM B.F. Hobbs Johns Hopkins U. 313 Ames Hall Baltimore


53/70

Table 3-16Contact Information (1 of 2) (Continued)

ProductName

Name ofContact

Company Address1 Address2 City

PowerACE AnkeWeidlich

Karlsruhe University Englerstrae 14 Karlsruhe

LTEPMAlainSchmutz

Electrowatt-Ekono /IlexEnergy Consulting

Hardturmstrasse161

Zrich

EurecaAlainSchmutz

ILEX EnergyConsulting /Electrowatt-Ekono

King CharlesHouse

Park EndStreet

Oxford

PD EMPSPrice Forecast

Jussi Mkel Power Deriva Tlnkatu 5 PO BOX 41 Helsinki

IPSPE ModelThomasHartmann

Institute of PowerSystemsand PowerEconomics (IAEW)

Schinkelstr. 6 Aachen

STEMS-RTRobertEntriken

EPRI3412 HillviewAvenue

Palo Alto

Market SimGeraldSheble

Iowa StateUniversity

1115 Coover Hall Ames

GENERISSimoMakkonen

Process Vision Oy Melkonkatu 18 HELSINKI

POWERS Ad Seebregts ECN Policy Studies Westerduinweg 3 Petten


54/70

Survey Results

3-20

Table 3-17Contact Information (2 of 2)

Product Name Your Email Company URL

MAPS [email protected] www.ge.com

EP [email protected]

MELBOURNE [email protected] http://www.iw.uni-karlsruhe.de

EMCAS [email protected] www.energycenter.anl.gov

PLEXOS [email protected] http://www.draytonanalytics.com

MADERE [email protected] http://www.edf.com

EE [email protected] http://ices.gmu.edu

ENERGY 2020 [email protected] www.ENERGY2020.com

NetaSim [email protected]

TSCM [email protected]

COMPETES [email protected] www.ecn.nl

CTCEM [email protected] http://engineering.jhu.edu/~dogee/hobbs

[email protected]

www.iw.uni-karlsruhe.de

LTEPM [email protected] http://www.ewe.ch / http://www.ilexenergy.com

Eureca [email protected] http://www.ilexenergy.com / http://www.ewe.ch


[email protected]

IPSPE Model [email protected] http://www.iaew.rwth-aachen.de

STEMS-RT [email protected] www.epri.com

Market Sim [email protected]

GENERIS [email protected] www.processvision.fi

POWERS [email protected] http://www.ecn.nl/ps/index.en.html


55/70


56/70

References

4-2

15.Nash, J.F. (1995).John F. NashAutobiography, From Les Prix Nobel. The Nobel Prizes1994, Editor Tore Frngsmyr, [Nobel Foundation], Stockholm, 1995.http://nobelprize.org/economics/laureates/1994/nash-autobio.html

16.Nash, J.F. (1950). Equilibrium points in N-person games, Proceedings of the NationalAcademy of Sciences, U.S.A., 36:48-49.

17.Bertrand, J. (1883): Theorie mathematique de la richess sociale,Journal des Savant,pp. 499-508.

18.Cournot, A. (1838): Recherches sur les principes mathmatiques del la thorie des richesses.Paris.

19.Varian, H. (2002).Intermediate Microeconomics A Modern Approach W. W. Norton &Company; 6th Edition.

20.R.W. Cottle, J.S. Pang, and R.E. Stone, The Linear Complementarity Problem, AcademicPress, New York, 1992.

21.P.D. Klemperer and M.A. Meyer, Supply Function Equilibria,Econometrica, 57, 1989,

1243-1277.22.Green, R. and D. Newbery (1992): Competition in the British Electricity Spot Market,

Journal of Political Economy, vol. 100, no 5.

23.Carolyn A. Berry, et al (1999). Understanding how market power can arise in networkcompetition: a game theoretic approach, Utilities Policy, 1999, vol. 8, issue 3, pages 139-158.

24.C.J. Day, B.F. Hobbs, and J.-S. Pang, Oligopolistic Competition in Power Networks: AConjectured Supply Function Approach,IEEE Trans. Power Sys., 27(3), 2002, 597-607.

25.Wikipedia (2005). Scientific method http://en.wikipedia.org/wiki/Scientific_method

26.Wikipedia (2005). Vernon L. Smithhttp://en.wikipedia.org/wiki/Vernon_Smith

27.McKinney, C.N, and A. Roth, (2004). Experimental Economicshttp://kuznets.fas.harvard.edu/~aroth/exper.html

28.Smith, V. (1982). Microeconomic Systems as an Experimental Science, AmericanEconomic Review 72(5), 923-955.

29.Smith, V. (1987). Experimental Methods in Economics, in The New Palgrave: ADictionary of Economics, John Eatwell, Murray Milgate, and Peter Newman Eds.

30.Smith, V. (1994). Economics in the Laboratory, Journal of Economic Perspectives 8(1),113-131.

31.John Bower and Derek Bunn (2001). Experimental Analysis of the Efficiency of Uniform-Price versus Discriminatory Auctions in the England and Wales Electricity Market,Journalof Economic Dynamics and Control 25, March 2001, pages 561-592.

32.Derek Bunn and Fernando Oliveira, Agent-Based Simulation: An Application to the NewElectricity Trading Arrangements of England and Wales,IEEE Transactions onEvolutionary Computation, Volume 5, Number 5, October 2001, 493-503.

33.Leigh Tesfatsion (2005). Agent-Based Computational Economics (ACE) Research Area:Restructured Electricity Markets, web sitehttp://www.econ.iastate.edu/tesfatsi/aelect.htm
http://nobelprize.org/economics/laureates/1994/nash-autobio.htmlhttp://nobelprize.org/economics/laureates/1994/nash-autobio.htmlhttp://en.wikipedia.org/wiki/Scientific_methodhttp://en.wikipedia.org/wiki/Scientific_methodhttp://en.wikipedia.org/wiki/Vernon_Smithhttp://en.wikipedia.org/wiki/Vernon_Smithhttp://en.wikipedia.org/wiki/Vernon_Smithhttp://kuznets.fas.harvard.edu/~aroth/exper.htmlhttp://kuznets.fas.harvard.edu/~aroth/exper.htmlhttp://www.econ.iastate.edu/tesfatsi/aelect.htmhttp://www.econ.iastate.edu/tesfatsi/aelect.htmhttp://www.econ.iastate.edu/tesfatsi/aelect.htmhttp://www.econ.iastate.edu/tesfatsi/aelect.htmhttp://kuznets.fas.harvard.edu/~aroth/exper.htmlhttp://en.wikipedia.org/wiki/Vernon_Smithhttp://en.wikipedia.org/wiki/Scientific_methodhttp://nobelprize.org/economics/laureates/1994/nash-autobio.html


57/70

A-1

ASURVEY QUESTIONAIRE

Product Information

1. Please provide the following information about the simulation-modeling product?Fill in the blanks

Your Name

Your E-mail Address

Product Name MADERE

Company EDF

Address 1 1 avenue du General de GaulleAddress 2

City Clamart

State/Province

ZIP Code/Postal Code 92140

Country France

Telephone 33 1 47 65 16 41

Company URL http://www.edf.com

Use and Capabilities

2. For what types of simulations can this product be used?Click on yes or no for each item

1= Yes, 0=No -9=No Answer

Human Experiments 0

Agent-Based Experiments 1

Equilibrium Computations 0


58/70


59/70

Survey Questionaire

A-3

Real-Time Modeling Features

6. Is the product capable of modeling the followingreal-time market characteristics?Click on yes or no for each item


Real-Time Energy 0

Real-Time Congestion Rights 0

DC Transmission 0

Real-Time Reserves 0

Real-Time Interfaces 0

Security Constrained 0

Multi-Period 0

Ramp Constraints 0

Other Real Time Market Characteristicspleasespecify in box below

-9

Day-Ahead Modeling Features

7. Is the product capable of modeling the following day-aheadmarket characteristics?Click on yes or no for each item


Day-Ahead Energy 1

Day-Ahead Congestion Rights 0

Day-Ahead Reserves 0

Day-Ahead Interfaces 0

Day-Ahead Unit Commitment 0

Security Constrained 0

Multi-Period 0

Ramp Constraints 0

Other day-ahead market characteristicsplease

specify in box below -9


60/70

Survey Questionaire

A-4

Forward Market Modeling Features

8. Is the product capable of modeling the followingforward trading characteristics?Click on yes or no for each item


Forward Energy 0

Forward Congestion Rights 0

Forward Reserves 0

Other forward market characteristicspleasespecify in box below

-9

Market Participant Modeling Features

9. Is the product capable of the followingmarket participants modeling?Click on yes or no for each item


Cournot 0

Bertrand 0

Supply Function Equilibrium (SFE) 0

MPEC 0

Heuristic 1

Other market participant modeling capabilityplease specify in box below -9

Reporting Features

10. What are the diagnostic and reporting capabilities of this product?Please type description in box


61/70

Survey Questionaire

A-5

New Features

11. Have you added any features to this product since the last release?Please click on no or yes


0 If yes, specify added features below

Planned Features

12. Do you plan to add any features in the next 12 months? Please click on no or yes


0 If yes, specify added features to be added below

Software Characteristics

13. Please indicate whether the following features, attributes or characteristics describe this

product. Click on yes or no for each item


Software Library 0

Stand-Alone Application 1

Web Accessible 0

Client-Server Architecture 0

14. Is third party software needed to use this product? Click on no or yes


0If yes, for each third party software that is needed, please specify the name of thesoftware and how the user gets access to it.

Software neededfill-in blank Available as:

None

None

None


62/70

Survey Questionaire

A-6

15. What types of data compatibility does the product have? Click on yes or no for each item


Reads spreadsheet 0

Writes spreadsheets 0

Reads database 0

Writes database 0

CIM Market Extensions compatible 0

Reads and writes text files 0

Reads and writes XML files 0

Platforms

16. Is the product available for the following platforms? Click on yes or no for each item


Windows

Linux

Solaris

Mac OS

Otherplease specify below

17. For each platform for which the product is available, please indicate whether the following

types of multiprocessing are supported. Click on yes or no for each item


Platform Shared Memory Distributed Memory Networked

None -9 -9 -9

None -9 -9 -9

None -9 -9 -9

None -9 -9 -9


63/70

B-1

BSURVEY LETTERS

Introductory Letter

From: Cara Lee Mahany BraithwaitSent: Monday, March 14, 2005 10:43To: Entriken, RobertSubject: EPRI Power Market Simulation Survey

Date: March 9, 2005To: Dr. Bob

From: Cara Lee Mahany Braithwait on behalf of Robert Entriken, Manager for Policy Analysis, EPRIRegarding: Simulation Model Survey

EPRI has had a long interest in the development of power market simulation tools. As part of their ongoing researchthey periodically conduct surveys to document the state-of-the-art of power market simulation models.

We are asking you to complete a short (about 10 minutes) on-line survey to collect information about power marketsimulation tools, with emphasis on the use of autonomous agents in simulation, which your organization may havedeveloped or is using. The survey focuses on collecting basic information about the models features:

type of markets and agents it can model

the size of problems it can handle

pricing and channels through which the model may be available

minimum system requirements third party software used

recent and/or planned enhancements

A summary report of the survey findings will be shared among the survey participants and EPRI Funders. EPRI mayeventually publish the survey, if it is seen to be worthwhile.

In the next few days, you will receive a hardcopy version of this letter and another email fromme,([email protected]), the survey manager. The subject line will be EPRI Survey. This email willinclude a URL for the survey site and a set of access keys that you can use to access the survey. We are supplyinga set of keys on the chance that you have more than one product.

If you like, please feel free to contact Dr. Robert Entriken about this survey. His contact information is RobertEntriken 650/855-2665 [email protected]

If we should direct this survey to another person in your organization, please turn this email around and send me thecontact information.

Hardcopy to follow


64/70

Survey Letters

B-2

Instructions

From: Cara Lee Mahany BraithwaitSent: Thursday, March 17, 2005 11:41To: Entriken, Robert

Subject: EPRI Survey--Power Market Simulation Models

March 17, 2005

To: Dr. BobFrom: Cara Lee Mahany BraithwaitEPRI Survey Manager on behalf of Robert Entriken of EPRIRegarding: EPRI Power Market Simulation Model SurveyYour Key Numbers: KFE nnn, KFE nnn, KFE nnn

Earlier this week you should have received an email about a Power Market Simulation Model Survey from me onbehalf of Robert Entriken. A hardcopy should arrive today. As explained, EPRI periodically surveys key players inthe power market simulation-modeling world to document the current capabilities of power market simulationmodeling tools. The survey focuses on collecting basic information about the models features:

type of markets and agents it can modelthe size of problems it can handlepricing and channels through which the model may availableminimum system requirementsthird party software used andrecent and/or planned enhancements

EPRI has hired my firm, Christensen Associates to conduct the survey. The survey is short; it takes most peopleabout 10 minutes to complete. A copy of the results will be provided to each organization that completes a survey.

The survey can be accessed at:http://power.lrca.com/Survey/survey.asp?survey=14216

At the login page you will be asked to provide an access key. You will see that there are two text boxes for anidentifying key. Each access key has three letters and three numbers. Simply insert the three letters of an access keyin the first box and the three numbers in the second box. We have given you three keys in case you have more thanone modelif you have more than three models, for which you would like to complete a survey, please contact usand we can send more keys.

We would like to have all responses in the next few days.

We thank you in advance for your help. If you have any questions, please contact me at [email protected] or bycalling 1-888-332-3258.
http://power.lrca.com/Survey/survey.asp?survey=14216http://power.lrca.com/Survey/survey.asp?survey=14216http://power.lrca.com/Survey/survey.asp?survey=14216http://power.lrca.com/Survey/survey.asp?survey=14216


65/70


66/70

Survey Letters

B-4

Response

From: Cara Lee Mahany BraithwaitSent: Tuesday, March 22, 2005 16:53To: Entriken, Robert

Subject: EPRI Power Market Model Survey Response Form

Thank you for completing EPRIs Power Market Modeling Survey. As promised, this is a copy your surveyresponses. If there are any changes you might like to make please follow these simple steps:

1. Go to where you wish to make a change and type in the changetrack changes will show your change2. Email the word file back to me and we will modify the database

We thank you for you time and effort. Look for a draft report to come your way--we invite input at this point too. Ifyou have any questions, please direct them to me and I will either answer them or get answers for you.

Best regards, Cara Lee Mahany BraithwaitSurvey Manager for Robert Entriken of EPRI1-888-332-8258


67/70

Survey Letters

B-5

Review

From: Entriken, Robert

Sent: Tuesday, June 28, 2005 19:07

To: [email protected]; [email protected]; [email protected]; [email protected];

[email protected]; [email protected]; [email protected]; [email protected];[email protected]; [email protected]; [email protected]; Entriken, Robert;[email protected]; [email protected]; [email protected]

Cc: Cara Lee Mahany Braithwait; Chao, Hung-po

Subject: Draft Market Simulation Survey for your review

Dear Colleague,

Please find attached the first draft of our survey of market simulationsoftware. It does not yet have the tables of responses completed, be

Survey of Electricity Market Simulation

Documents

Transcript of Survey of Electricity Market Simulation