1 Chapter 11 Planning Planning examples PDDL (Planning Domain Definition Language) Planning systems.
SYSTEM PLANNING SMART G - Clark Science Centerjcardell/Courses/EGR325/slides/C12_325.pdf ·...
Transcript of SYSTEM PLANNING SMART G - Clark Science Centerjcardell/Courses/EGR325/slides/C12_325.pdf ·...
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SYSTEM PLANNING & SMART GRIDS
EGR 325 March 6, 2018
Overview ■ Time scale separation ■ System planning – Planning which power plants to build (and where) to meet future (anticipated) load growth
■ Screening curve – Old tool, but useful to understand process of deciding which type of generating plant to build – Determining the ‘technology mix’
■ Reliability measures – Understanding a plethora of measures, and why they are both inputs to and outputs from
computer models
■ On to the future – the smart grid – NOVA video – EPRI casestudies
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Time Scale Separation
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Primary Dynamics: Sub-cycle to multiple cycles; local controls and device natural
response; automation and intelligent devices
Secondary Dynamics: Seconds to minutes; AGC, AVC; demand-
response; automation and intelligent devices
Tertiary Dynamics: 30 minutes through month(s); Regional system, and spot & day-
ahead market coordination
Long-Run Dynamics and decision making: Months to years; System
planning and expansion; Investment decisions and forward contracting
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Time Scale Separation 1. Decide what to build
2. Given the plants that are built, decide which plants to start for use tomorrow, next week, next month…
3. Given the plants that are ready to generate electricity, decide which plants to use to meet expected demand today, the next hour, the next 5 minutes
4. Given the plants that are generating (‘spinning’), decide how to maintain the supply-demand balance cycle to cycle
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Today: System Planning
■ What are the types of generating plants we can build? ■ How do we decide...
– Which type of generating plant to build? – How much capacity of each type? = “The technology mix”
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System Planning Criteria ■ Meet system demand into the future ■ Low cost ■ High reliability ■ Low environmental impacts (emissions) ■ Fuel diversity ■ Sustainability (inter-generational issues)
■ Every variable will have a time series ■ System planning implies questions for the future
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System Planning ■ What types of generating plants can we
build? ■ How do we decide...
– Which type of generating plant to build? – How much capacity of each type? = “The technology mix” ■ Planning starts with cost information on
generating technologies – Fixed costs and variables costs
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Types of Generators: Hypothetical Fixed & Variable Costs
IAEA report Table 6.XVIII, 1984
Technology/Capacity (MW)
Fixed Cost ($/kW annual)
Variable Cost (mills/kWh)
Coal / 600 53.80 14.44
Coal / 200 88.34 14.87
Oil / 400 49.44 46.85
Nuclear / 1000 88.33 6.34
Gas Turbine / 50 13.40 87.04
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Technology Mix Example: ERCOT Electric Supply Curve –
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Example: SERC Electric Supply Curve Relate to ‘system λ’ from homework
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Example: ECAR Electric Supply Curve Relate to ‘system λ’ from homework
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Analysis Tool: the Screening Curve ■ The screening curve compares the costs of different
technologies ■ Two generating plant cost components plotted
1) Fixed, or capital cost 2) Variable or O&M costs (operating & m
■ On the screening curve 1) The capital cost is the y-intercept (cost even if no energy is
ever generated) 2) The variable cost is the slope of the line 3) The x-axis is indexed to capacity factor, in order to line up
with the LDC (second step in the analysis process)
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Setting up a “Screening Curve”
IAEA report, 1984
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The LDC & the Screening Curve ■ A load duration curve specifies the nature of
electrical demand in any system ■ A screening curve compares the supply
technologies available to meet that demand ■ Combining these tools helps planners
determine the best “technology mix” to meet their anticipated system demand
■ Activity...
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Intercept = capital cost Slope = operating cost
Peak Intermediate Base load
Load (% of max)
Time (8760 hours)
Obtain from aggregating daily load curves
Screening Curve + LDC
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Sample Screening Curve
Technology Screening Curve
0
500
1000
1500
2000
2500
3000
0 50 100
150
200
250
300
350
400
450
MWh
Tota
l Cos
t
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Determining Optimal Technology Mix
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Determining Optimal Technology Mix
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Interpreting the Screening Curve Technology / Capacity (MW)
Capacity factor range (fraction)
Normalized load range (fraction)
Best technology mix
(fraction) Gas Turbine 50 MW
0.0 – 0.0635
0.8689 – 1.0
13.11% (i.e., if peak demand were
1000MW, then 130MW of gas turbine capacity should be built)
Coal 600 MW
0.0635 – 0.4866
0.6362 – 0.8689
23.27%
Nuclear 1000 MW
0.4866 – 1.0
0.0 – 0.6362
63.62%
(Screening Curve x-axis à LDC y-axis)
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System Planning Criteria ■ Meet system demand into the future ■ Low cost ■ Highreliability■ Low environmental impacts (emissions) ■ Fuel diversity ■ Sustainability (inter-generational issues)
■ Every variable will have a time series ■ System planning implies questions for the future
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Define and Measure Reliability ■ How is reliability defined? ■ How do we measure reliability?
■ For reference – NERC: North American Electric Reliability Corporation:
http://www.nerc.com/ – NERC is overseen by FERC (Federal Energy Regulatory
Commission – same position in government as EPA, FCC…)
Resource Adequacy ■ Resource adequacy vs. power system reliability – Adequacy is a component of reliability.
■ A power system is reliable if it is: – Adequate: the electric system has sufficient resources –
generation, efficiency and transmission – to serve customers, taking account of scheduled and reasonably unscheduled outages (normal events)
– Secure: the electric system can withstand sudden disturbances, such as electric short circuits or unanticipated loss of system elements (extreme events)
22 - Pacific Northwest Planning Council
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Determining Resource Adequacy – Computer programs simulate the operation of the power
system over many different futures § Each future is simulated under a different set of
unknown parameters, such as: § Temperature, wind generation, water supply, fuel
prices, and generator performance – HOMER – next computer simulation model
§ Defining different “futures” allows you to perform sensitivity analyses
§ Helps to understand which system plans are likely to be best for a variety of future situations.
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Reliability ■ Reliability relates to total electric system
interruptions ■ Reliability indices typically consider – the number of customers affected – The magnitude, or connected load (MW) of the
interruption – the duration of interruptions measured in seconds,
minutes, hours, or days – the frequency of interruptions
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Reliability Measures – Generating Unit ■ Unit Reliability / Availability
– Forced outage rate, related to generating unit malfunctions
– Maintenance (planned outage) – availability – Also for renewable energy technologies (RETs):
availability of the resource ■ The ‘effective load carrying capability’ or ELCC
is often used to indication reliability of RETs
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■ System Reliability – Reserve margin ■ Installed capacity (generators that have been built)
above the expected system peak demand – Loss of load probability (LOLP) – Loss of load expectation (LOLE) – Cost of unmet energy – SAIFI (System average interruption frequency
index) ■ And SAIDI, CAIFI, CAIDI (D = duration, C = customer)
Reliability Measures – System Level
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■ Input to computer models: – Targets desired by Planners and Society – Target or desired Reserve margin – Target or desired LOLP
■ Output of computer modeling (all of them) – Achieved Reserve margin – Achieved LOLP – LOLE – Cost of unmet energy – Indices: SAIFI, SAIDI, CAIFI, CAIDI
Reliability Measures – for Computer Models
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FYI: Loss Of Load Probability, LOLP
§ The probability that in a given hour available generating capacity is less than load.
§ LOLP for hour i, or LOLPi
LOLPi = Pr (∑ Cj < Li),
– where Cj is a stochastic variable representing the expected capacity of generator j in hour i ■ Forced outage rate, FOR
– Li is the system electrical load in hour i
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FYI: Loss of Load Expectation
§ The annual LOLE index is defined over all hours of the year as § The sum of the 365 daily max LOLP’s
LOLE = ∑ LOLPi
FYI: Effective Load Carrying Capability § ELCC is the amount of load, ∆L, that can be added to a
system at the initial LOLE, after a new unit with capacity ∆Cmax is added.
§ Can determine LOLE via LOLE = ∑ Pr (∑ (Cj + ∆Cmax) < (Li + ∆L))
§ After some rearranged this becomes… ELCC = ∆L/∆Cmax
§ ELCC is sensitive to the concentration of LOLE in time; § i.e. is 95% of LOLE in the top 20 hours or the top 50 hours, or
other questions you might be interested in...
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Forced Outage Rates (old data for fossil fuel generating technologies)
Prime Mover MTTF (days) MTTR (days) Steam Turbine (coal) 122.5 3.4
Steam Turbine (oil) 18.75 2.9
Combustion Turbine (oil)
82.5 0.83
Nuclear 45.8 8.5 Hydro 81.7 2.3
(MTTF: Mean Time To Failure)
Grand Challenge for the Future Grid, PSERC
■ Design an electric power system that takes full advantage of the convergence of energy, communications, sensing, and computing technologies in a cyber-physical system that enables society to reach its diverse energy objectives, such as 50% renewables or 80% carbon reduction by 2050. ■ Part of the challenge is to make the transition to high levels
of renewable resources transparent to users of electric energy – where this transparency relates to both reliability of the electric
supply as well as its economy.
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NOVA Smart Grid Video ■ http://www.pbs.org/wgbh/nova/tech/power-grid.html ■ Use this to – Identify elements of the power system (brought up in the video) that can be
improved, fixed, solved with the “smart grid solution” – Identify how the smart grid will solve these problems
■ Smart Grid Discussion Questions – What problems are being addressed by or solved by the smart grid? – Time scale separation analysis framework
■ What elements of a smart grid would be implemented at – used to solve problems, concerns, obstacles at – each time scale of system planning and operations
EPRI Smart Grid case studies
■ Main point or lesson ■ A new idea ■ Something that was surprising ■ Something to use for Puerto Rico planning ■ Something you learned
http://smartgrid.epri.com/Demo.aspx
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Microgrid ■ A group of interconnected controllable loads
and distributed energy resources (DER) ■ …with clearly defined electrical boundaries ■ …that acts as a single controllable entity with
respect to the grid ■ …[and can] connect and disconnect from the
grid to enable it to operate in both grid-connected or island mode.
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■ Cogeneration – Focus on providing energy close to the load to allow for co-
generation of heat & electricity – For northern regions
■ Photovoltaic systems (& solar hot water…) – Warm, sunny climates
■ Islanding of the micropower system à improved reliability ■ Total energy efficiency objective
Microgrid
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