LITERATURE SURVEY IN DEREGULATED POWER SYSTEM TO REDUCE CONGESTION USING … · 2019-03-23 ·...

Journal of Analysis and Computation (JAC) (An International Peer Reviewed Journal), www.ijaconline.com, ISSN 0973-2861

International Conference on Knowledge Discovery in Science and Technology 2019,

ICKDST '19, Pune

Pawan C. Tapre , Dr. Dharmendra kumar Singh, Dr. Sudhir Paraskar 1

LITERATURE SURVEY IN DEREGULATED POWER SYSTEM TO REDUCE

CONGESTION USING DIFFERENT TECHNIQUE

Pawan C. Tapre

Department of

Electrical Engineering

CVRU, Ph.D. Scholar

Bilaspur (C.G.), India

pawan.tapre25@rediffmai

l.com

Dr. Dharmendra kumar Singh

Department of Electronics

Engineering

Associate Professor,

CVRU, Bilaspur

(C.G.),India

dmsingh2001@rediffmai.

com

Dr. Sudhir Paraskar

Department of

Electrical Engineering, Professor,

SSGMCE, Shegaon(M.S.),

India

[email protected]

Abstract—In competitive electricity market, congestion is a

serious economic and reliability concern. Congestion is a

common problem that an independent system operator

faces in open access electricity market. This paper presents

a literature survey of different technique (algorithm) used

to solve the congestion of transmission line in deregulated

power system like FFA, ALO, PSO, HNM-FAPSO, PSO-

ITVAC, CS, GA, SA, DE, CCP, LA and , FACTs devices

like STATCOM, TCSC, SSSC, UPF.

Keywords—FFA, ALO, PSO, PSO-ITVAC, HNM-PSOTCSC,

LA, STATCOM, TCSC,SSSC, Congestion Management

I. INTRODUCTION

An overview literature and also the review of

literature of the different algorithm technique

to reduce congestion management in

deregulated power system. This paper

described also categorization, description of

works, problem statement, features and

challenges of diverse methodologies for

congestion management, research gaps and

challenges of different technique used in

literature.

II. LITERATURE SURVEY

Verma Sumit and Mukherjee V. (2016),

“Firefly algorithm for congestion management

in deregulated environment”, In this paper

demonstrates a novel optimization technique

for solution of the CM problem in open access

electricity market. FFA is, successfully,

implemented to minimize the rescheduling cost

for alleviating congestion completely.

Contingencies like line outage and sudden load

variation are considered in this work. The

proposed method is implemented on modified

IEEE 30- and IEEE 57-bus systems and the

results are compared with random search

method, simulated annealing and PSO. It is

observed that the proposed FFA effectively

relieves congestion, and rescheduling cost

obtained is much lower than the costs reported

by the other approaches. Moreover, total

amount of rescheduling and losses are also

found to be lower. From all the considered

simulated cases, it may be observed that FFA is

a potential tool to solve a non-linear,

multimodal problem. Compared to other

optimization algorithms like PSO, SA and

RSM, FFA has added advantage of random

reduction, lesser time to produce optimum

value and automatic subdivision among the

fireflies. Apart from the self improving process

within the current space, the FFA also includes

the improvement among its own space from the

previous stages. Thus, it may be concluded that

FFA is a powerful and strong approach to solve

optimization problems, providing most

economical, reliable and secure operating

conditions. Use of sensitivity analysis for

selection of participating generators along with

rescheduling may be the direction of future

research work. FFA may be recommended as

an effective optimization tool for some other

power engineering optimization applications.

mailto:[email protected]





LITERATURE SURVEY IN DEREGULATED POWER SYSTEM TO REDUCE CONGESTION USING

DIFFERENT TECHNIQUE


Verma Sumit and Mukherjee V. (2016),

“Optimal real power rescheduling of generators

for congestion management using a novel ant

lion optimizer”, In this paper a generation

rescheduling-based approach for CM of power

system in power market is presented in this

paper. A novel ALO algorithm is utilised for

this purpose. Contingencies like line outage

and abrupt load variation are considered here.

Congestion in the overloaded lines is managed

by rescheduling the generations while

minimizing CM cost. The proposed ALO

method is, successfully, implemented on

modified IEEE 30-bus, modified IEEE 57-bus

and IEEE 118-bus test power systems for CM

of power system. The proposed ALO

algorithm-based outcomes are compared to

several well-known and recent algorithms (like

PSO, RSM, SA, EP, RCGA, HPSO, DE, BA,

CBA, FPA and FFA) reported in the recent

state-of-the-art literature. The comparative

analysis shows that the proposed ALO-based

cost of generation rescheduling is less as

compared to the other algorithms for all the

considered test cases. Moreover, the total

system loss has been also reduced after the

application of CM. The presented values of the

CR of various adopted algorithms for the

considered test cases show that the

convergence mobility of the proposed ALO

algorithm is the fastest one. Thus, the proposed

ALO algorithm provides a new and effective

approach to solve the CM problem of power

system in deregulated regime. The proposed

ALO algorithm may be recommended for

future researchers as an effective optimisation

tool to deal with multi-objective large-scale

power systems problems with the future

researchers.

Nesamalar J. Jeslin Drusila et al.

(2016),“Managing multi-line power congestion

by using Hybrid Nelder–Mead – Fuzzy

Adaptive Particle Swarm Optimization (HNM-

FAPSO)", have suggested the new method

called hybrid Nelder-Mead – Fuzzy Adaptive

Particle Swarm Optimization (HNM-FAPSO)

in order to manage the congestion in the multi-

line environment of electrical market. The

concerned operation was performed based on

selecting the generators which are responsive

to the congested line, through the

determination of Apparent Power Sensitivity

Factor (APSF). Moreover, the fuzzy

interference system was utilized to overcome

the limitation of PSO algorithm like the issue

of premature convergence. The test was carried

on IEEE 30 and IEEE 118 benchmark test bus

systems and has compared the results of the

proposed method with the conventional

algorithms like FAPSO, NM, Genetic

Algorithm (GA) and adaptive bacterial

foraging algorithm with Nelder–Mead

(ABFNM) and PSO algorithm. Thus the

proposed algorithm have reached its maximum

performance by attaining less cost , loss of

power and time for computation.

Gope Sadhan et al. (2016),

"Rescheduling of real power for congestion

management with integration of pumped

storage hydro unit using firefly algorithm", have developed the firefly algorithm to

accomplish the congestion management in the

transmission network. This experiment has

performed by taking an account of dual factors

like generator sensitivity factor (GSF) and bus

sensitivity factor (BSF). In addition, this

method has also concern the total count of

generators utilized in the network.

Subsequently, this experiment was carried on

IEEE 39 test bus system and has proved the

supremacy of the proposed method by proving

maximum security to the network with reduced

congestion cost.

Chellam S. et al (2016) "Power flow

tracing based transmission congestion pricing

in deregulated power markets", have propose a

simple transmission congestion pricing scheme

based on tracing principle by considering

generator fixed cost, cost for incurring loss and

transmission congestion cost. Restructuring has

brought about considerable changes by the

virtue of which electricity is now a commodity

and has converted into deregulated type. Such a

competitive market has paved way for

innumerable participants. This concept of

restructuring has led to overloading of



ICKDST '19, Pune


transmission lines. In this power flow tracing

has been employed by using suitable

optimization algorithm, where the real power

generation has been maximized. Congestion in

the transmission line has been produced in a

new fashion by maximizing the real power

demand. The power flow under normal

operating condition and congestion is

determined and hence the difference in power

flow is estimated. Based on the estimated

power flow difference, the transmission line

congestion cost is computed. Pool model and

bilateral model has been considered in

simulation study to introduce the concept of

deregulation. The proposed method is tested

and validated on Modified IEEE 30 bus test

system and Indian utility 69 bus test system.

Mishra Akanksha and Nagesh Kumar

G.V. (2017), "Congestion Management of

Deregulated Power Systems by Optimal

Setting of Interline Power Flow Controller

using Gravitational Search Algorithm", have

propose a Disparity Line Utilization Factor for

the optimal placement and Gravitational Search

Algorithm based optimal tuning of IPFC to

control the congestion in transmission lines.

DLUF ranks the transmission lines in terms of

relative line congestion. The IPFC is

accordingly placed in the most congested and

the least congested line connected to the same

bus. Optimal Sizing of IPFC is carried using

Gravitational Search Algorithm. A

multiobjective function has been chosen for

tuning the parameters of the IPFC. This method

is implemented on an IEEE-30 bus test system.

Graphical representations have been included showing reduction in LUF of the transmission

lines after the placement of an IPFC. A

reduction in active power and reactive power

loss of the system by about 6% is observed

after an optimally tuned IPFC has been

included in the power system. The

effectiveness of the proposed tuning method

has also been shown through the reduction in

the values of the objective functions.

Sarwar Md. and Siddiqui Anwar

Shahzad (2016), "An approach to locational

marginal price based zonal congestion

management in deregulated electricity market”,

In this paper, a novel approach to zonal

congestion management in pool market is

proposed. The identification of different

congestion zones is based on the LMP

difference between buses connecting a line.

The most sensitive congestion zone is one

which groups the buses connecting lines of

high and non-uniform LMP difference across

them. The congestion is managed by optimally

allocating the DG in the most sensitive

congestion zone. The optimal allocation of DG

is also based on LMP difference. To analyze

the effectiveness of zonal based congestion

management, the DG is also allocated to other

zones which are considered as less sensitive to

congestion. The robustness of the proposed

methodology is tested on IEEE 14-bus system

and IEEE 57-bus system and it is found to be

efficient for both small and large power

systems.

Esfahani Mohammad Mahmoudian and

Yousefi Gholam Reza (2016) , "Real Time

Congestion Management in Power Systems

Considering Quasi-Dynamic Thermal Rating

and Congestion Clearing Time", In this paper,

we proposed an optimal real time transmission

congestion management algorithm by taking

quasi-dynamic thermal rates of transmission

lines into account. It led to defining the

congestion clearing time with respect to the

short term and emergency thermal ratings of

the transmission lines. Considering generators ramp rates along with using the sensitivity of

the congested lines current with respect to the

power system generators and loads made it

possible to find a very fast and feasible solution

for congestion management problem.

Furthermore, subdividing the clearing time into

subsequent subintervals allowed system

operators to adapt the congestion management

procedure with regard to loads, generations or

system configuration variations during

rescheduling process. This allows system


DIFFERENT TECHNIQUE


operators to fully exploit the capability of

conductors to withstand different current flows

according to temperature, initial amperage and

weather conditions when the system is faced

with an emergency situation. Numerical results

showed that the congestion mitigation and

reduction of the congestion costs and load

shedding is possible through the fast solution

of the proposed method.

Nesamalar J. Jeslin Drusila et al.

(2016), "Energy management by generator

rescheduling in congestive deregulated power

system", This article presents the energy

management methodology by employing

Cuckoo Search Algorithm. In order to get a

wider picture of energy management, the real

time congestion scenarios such as during peak

load, addition of bilateral and multilateral

power transactions, generation failure and

outage of transmission line are analyzed for a

duration of 24 h. Case study is performed on

IEEE 30-bus system and real time Tamilnadu

106-bus system. Results show that by optimal

rescheduling of generators for each scenario,

energy loss can be reduced by 17.71% and the

energy rescheduling cost can be reduced by

4.23% for 24 h. On an average, about 17,443 $

can be saved annually, which can be utilized

for strengthening the existing power system,

addition of new transmission lines, extract

more renewable energy, for involving in more

research analysis on energy generation and

transmission and so on. For all congested

cases, the amount of power rescheduled,

selection of generators, power loss, energy

generation cost, energy rescheduling cost and

slack bus contribution are observed. By

mimicking the breeding behavior of cuckoo,

CSA has been applied successfully for energy

management to get optimized energy savings

and cost savings and it serves as a guide for

ISO to get maximum savings and achieving

system stability in a shorter span of time.

However, the seasonal changes will have

impact on the congestion cost.

Hosseini Seyyed Ahmad et al. (2016) ,

"A new multi-objective solution approach to

solve transmission congestion management

problem of energy markets”, Congestion

management is an important operation function

of power markets as the operating conditions

obtained from the market clearing may not be

feasible in terms of security limits and stability

margins of the power system. The congestion

management problem involves different

competing objective functions consisting

congestion management cost and stability

margins. While a straight forward way for

tackling with this problem is formulating it as a

single objective optimization model including

the stability margins enforced through the

constraints, this approach may not be able to

implement an efficient compromise among

different objectives and lead to a vulnerable

power system or unreasonable congestion

management cost. Thus, in this paper,

following some recent research works in the

area, congestion management is modeled as a

MMP problem. The main contribution of this

paper is to propose a new MMP solution

method for solving multi-objective congestion

management problem. The main advantages of

the proposed NNC-based MMP solution

method are its systematic approach for

reducing the feasible design space and effective

covering of the objective space through a

uniform distribution of the Pareto solutions.

These capabilities enable the proposed

approach to find more preferred multi-

objective solutions compared to the other MMP

methods, such as weighting MMP, ordinary e-

constraint, augmented e-constraint and

modified augmented e-constraint, which have

been recently presented in the other research

works for solving multi-objective congestion

management problem. Additionally, an

optimality-based decision maker has also been

proposed to select the most preferred solution,

among the generated Pareto set for the MMP

problem, considering the relative importance of

the objective functions.

Rastgou Abdollah and Moshtagh Jamal

(2016), "Application of firefly algorithm for

multi-stage transmission expansion planning

with adequacy-security considerations in

deregulated environments", In this paper, by

expanding firefly algorithm, as one of the latest



ICKDST '19, Pune


meta-heuristic algorithms, a new methodology

was presented for solving transmission

expansion planning problem. In the applied

model in addition to construction’s costs,

which is a fundamental part of TEP, congestion

cost and security cost are also considered. The

proposed methodology and GA, PSO, SA and

DE are applied on the IEEE 24-Bus and IEEE

118-Bus and Iran 400-KV transmission grid

test systems. The transmission expansion plans

resulted from each algorithm are also presented

and compared. According to obtained results

the proposed algorithm has a less investment

cost rather than the GA, PSO, SA and DE. It is

worth mentioning that the proposed method is

a better algorithm regarding its convergence

rate. Simulation results show that the proposed

approach his accurate and efficient, and has the

potential to be applied to large scale power

system planning problems.

Siddiqui Anwar Shahzad Siddiqui and

Md. Sarwar (2015), "An efficient particle

swarm optimizer for congestion management

in deregulated electricity market”, This paper

focuses on use of PSO-ITVAC based algorithm

in minimizing the active power rescheduling

cost of generators. A congestion management

methodology by optimal selection of

generators based on their magnitude of

generator sensitivities has been discussed.

PSO-ITVAC is proposed to minimize the cost

of active power rescheduling of the selected

generators. The proposed algorithm has been

tested on IEEE 30-bus system, IEEE 118 bus

system and33-bus Indian network and it has

been found that active power rescheduling cost using PSO-ITVAC is more efficiently

minimized as compared to PSO-TVAC for

small as well as large networks. Also, PSO-

ITVAC converges to optimal solution more

rapidly than PSO-TVAC.

Hojjat Mehrdad and Javidi Mohammad

Hossein (2015), "Chance-constrained

programming approach to stochastic

congestion management considering system

uncertainties", This paper proposed a new

approach for probabilistic CM based on the

CCP. Moreover, an analytical approach was

developed to solve the stochastic optimisation

problems including single and joint chance

constraint models. The main contribution of

this paper is modelling the CM problem in a

probabilistic framework using CCP. Recently,

the CCP has been widely used to deal with

system uncertainties in power system studies .

The main difference between our work and the

mentioned references arises from proposing an

analytical approach to solve the CCP-based

problem, while the other studies employed

numerical methods, such as Monte–Carlo

based GA, as presented in. Furthermore, the

proposed CCP-based CM includes the joint

model for line flow constraints which

guarantees the accuracy of the solution since it

considers the whole constraints simultaneously.

In our work, besides proposing an analytical

approach for the joint model, an innovative

method is adopted based on the Monte–Carlo

technique to evaluate the accuracy of the

solution. Comparison of the results showed that

the introduced framework for stochastic CM

has more flexibility and generates more reliable

solutions compared with the scenario based

method. In fact we have shown in this paper

that the proposed framework for the stochastic

CM outperforms the scenario-based methods.

In addition, the analytical solving approach

implemented in this work benefits from both

single and joint models while other CCP-based

studies apply numerical methods with high

complexity in modelling and performance.

Ghorani Rohim et al. (2015), "Identifying critical components for reliability

centred maintenance management of

deregulated power systems", In this paper, a

new methodology was introduced to derive the

importance of composite power system

components based on the expected outage costs

imposed to different system participants when

an outage occurs. A future market was run first

followed by a balancing market for the main

sake of modelling real market interactions and

participants’ bids and offers. The state


DIFFERENT TECHNIQUE


enumeration method was pursued through

which it could be possible for the system status

to be analysed in each probable outage state.

Having calculated the probability and

frequency of each system state, the expected

additional cost associated with each state was

then determined. The proposed mapping

method could eventually allocate the outage

costs to the involved components and

accordingly prioritise the composite power

system components to be dealt with in RCM

and asset management applications. The results

presented are observed to be more trustworthy

since a comprehensive market model has been

employed, AC analysis has been pursued and

higher order contingencies have been taken

care of, as well. One of the major advantages

of the proposed method is the monetary

language that can be of great use in several

decision making processes and cost/worth

analysis of the maintenance plans. On the other

hand, its ability to use parallel processing to

speed up the calculation process together with

its limited dependency on the conventional

time consuming steps provides the users and

operators with an awesome possibility to

analyse the reliability of large-scale composite

power systems much easier.

Khan Mohd Tauseef and Siddiqui

Anwar Shahzad (2014), "Congestion

management in deregulated power system

using FACTS device", In this paper problem

of congestion is solved by finding the optimal

location of TCSC using sensitivity analysis

technique and OPF is solved using Newton–

Raphson Technique. This technique is

employed on Delhi 33-bus system and

congestion is successfully relieved from the

line which was heavily loaded. Delhi 33-bus

system is a practical network in which some

buses having less importance in the network

are eliminated to reduce the effort and time to

solve the problem of Congestion Management.

Here Transmission is open-access and

distribution is deregulated, so this method can

be employed to any other practical network

also.

Kumar Ashwani and Mittapalli Ram

Kumar (2014) "Congestion management with

generic load model in hybrid electricity

markets with FACTS devices”, In this work,

the generators’ rescheduling based congestion

management with three bid block structure

offered by the Gencos has been implemented

for hybrid market model. The impact of ZIP

load model and load variations have been

incorporated taking load scaling factor. The

congestion cost for each hour of day has been

calculated without and with FACTS controllers

and comparison has been provided with out

and with FACTS devices considering constant

P, Q and ZIP load model. The economic load

dispatch results are obtained for base case data

with three bid block structure for each Gencos.

It is observed from the results that the

congestion cost obtained with ZIP load model

is lower compared to the congestion cost

obtained for constant P, Q load model. The

congestion cost reduces with all FACTS

controllers compared to the case without

FACTS controllers. With UPFC and SSSC the

cost is lower compared to the case with

STATCOM. The congestion cost reduces with

FACTS devices as the generators are subjected

to lower up and down regulation. The ZIP load

model has considerable impact on the

congestion cost and the ISO should analyze the

system for congestion management with

realistic load model.

Rajakumar B.R. (2014), "Lion

algorithm for standard and large scale bilinear

system identification: A global optimization

based on Lion's social behavior", We have

introduced LA for solving nonlinear system

identification problem for which Bilinear series

model was used. Experiments were carried out

to estimate the behavior model of a nonlinear

rationale benchmark digital system. In the first

case, standard bilinear model was used in

which LA dominated over the standard GA and

DE. In the second case, large scale bilinear

model was used to test the algorithms in which

LA outperformed GA and proved as equivalent

to DE. The obtained results are encouraging, if

the depth of experimentation is not considered.

Hence, the future work has to be conducted



ICKDST '19, Pune


with wide experimental study in terms of large

scale problems along with systematic

comparisons. Further, we have planned to

extend the work for other nonlinear models

such as volterra series, cognitive systems, etc.

Kumar Ashwani et al [2013],

"Congestion management with FACTS devices

in deregulated electricity markets ensuring

loadability limit", In this work, the congestion

management based on generators’ rescheduling

with three bid block structure has been carried

out ensuring static security and voltage stability

limits. The 24 h variation of load has been

incorporated taking load scaling factor into

account. The congestion cost for each hour of

day has been calculated without and with

FACTS controllers and comparison has been

made. The economic load dispatch results are

obtained as base data during congestion

management. The results shows the congestion

cost reduces with FACTS controllers compared

to the case without FACTS controllers. The

congestion cost reduction is found lowest with

UPFC compared to other FACTS devices. The

comparison has been made on total congestion

cost of day, real power loss, and reactive power

loss and loadability factor. With UPFC, the

loadability margin of the system is higher

compared to other devices. The three bid

blocks offered by Gencos for congestion

management will be helpful to the ISO with

renewable energy sources integration in the

system. The authors are working in this

direction with more renewable energy sources

in the system and offering themselves for

congestion control during congestions hours.

Karthikeyan S. Prabhakar et al. (2013),

"A review on market power in deregulated

electricity market", This paper gives an

overview of the various work carried out in the

area of market power. The evolution of

different indices which are used to measure the

market power in the last 30 years and their

importance are discussed with a bibliographical

survey of necessary background. Some

researchers have given emphasize to the market

power measurement in terms of reactive power

and the impact of visualizing the degree of

market power. Review has also been made on

the application of Game theory and various

algorithms used in analyzing market power

issues. Many countries like Argentina,

Australia, Canada, Chile, Columbia, England,

Italy, Peru, New Zealand and United States

have already taken their electricity market

towards the deregulated environment, it is

necessary for the power system engineers to

focus on various issues pertaining to market

power. It is also very important that the

developing countries have to learn from the

experience had by the developed countries like

US. The authors also believe that the

discussion had under various sections in this

paper will help the research community who

has already oriented their research toward

market power.

Amjady Nima and Hakimi Mahmood

(2012), "Dynamic voltage stability constrained

congestion management framework for

deregulated electricity markets”, Congestion in

a power market happens because of network

limits. In a congested power system,

transactions are not feasible unless the system

operator uses a method to relieve the

congestion. In a deregulated power market, the

system operator has to pay to market

participants for altering their powers to

mitigate the congestion and finally make

feasible all power transactions. After applying

congestion management, the system security

level may be low because of hitting some

network limits. Such a network is highly vulnerable against even any little disturbance.

Thus, it is really important for the system

operator to use a method to mitigate congestion

ensuring system security after congestion

management. Using the previously introduced

congestion management methods to ensure

security, the system operator has to pay a

considerable fee to relieve congestion. Besides,

the previous methods do not consider dynamic

behavior of the power system for evaluating its

security level.


DIFFERENT TECHNIQUE


This paper proposes a novel congestion

management method considering dynamic

voltage stability of the power system. At first,

dynamic voltage stability of power system is

formulated based on bifurcation theory. Then,

the dynamic voltage stability formulation is

incorporated into the congestion management

framework. Extensive testing of the proposed

method confirms its validity. The proposed

method is compared with several other

congestion management methods presented in

the previous research works in the area. It is

shown that the proposed method can result in a

more robust power system, especially in

response to contingencies, with a lower

congestion management cost. Besides, the

proposed congestion management method can

be applied to power systems including static,

dynamic and composite load models.

Vijayakumar K. and Jegatheesan R.

(2012), "Optimal Location and Sizing of DG

for Congestion Management in Deregulated

Power Systems”, In this paper two efficient

methods are proposed for solving congestion

management problem in a day ahead electricity

market. This paper presents a simple method

for optimal sizing and optimal placement of

distributed generators. The first method gives

only one compromised solution considering

both the objectives, which does not provide any

choice to the operators. When this method is

used to find multiple solution, it has to be run

many times for finding a different solution in

each simulation run. It is time consuming and

cannot be used for real time problems. Though

the second multi-objective optimization does

not guarantee global optimal solution, it

provides a very close suboptimal solution. This

method also provides a set of pareto optimal

solutions for the congestion problem, giving

the system operator options for judicious

decision in solving the congestion.

Sood Yog Raj and Singh Randhir

(2010), "Optimal model of congestion

management in deregulated environment of

power sector with promotion of renewable

energy sources", In this paper a new optimal

model of congestion management has been

analyzed with IEEE-30 bus test system which

include conventional (thermal) as well

renewable (i.e. wind, solar and biomass based

generation). Test results reveal that proposed

model can be effectively used for combined

dispatch of transactions and pool. There is a

sufficient profit surplus of 1167.04 $/h for real

power demand and 275.68 $/h for real

generation using LMP approach as compared

with actual bid price approach. So LMP pricing

method provides social benefit to almost all

GENCOs and load centers depending upon

their allocation in the transmission network.

The SRMC of wheeling for non-firm

transaction 2 is negative. It means they are

favoring the transmission network i.e. reducing

congestion and losses. The transactions

involving RES are not curtailed at all (i.e. firm

transactions) moreover these are charged on the

basis of locational marginal pricing (LMP).

Similarly there is no curtailment of generation

from RES in the proposed model as depicted in

Table 6. So this optimal model of congestion

management is considering the promotion of

RES in the deregulated environment of power

sector and hence environmental friendly.

However, the net social benefit with LMP is

444.99 $/h whereas with actual bid price

approach is 1981.54 $/h. So it has been

observed that actual bid price approach

provides more social benefit. This benefit can

be utilized as subsidies for installing new

renewable energy plants, or subsidies to the

farmers, or defense or education sector as per

the policy of a particular country.

Esmailli Masoud et al. (2009),

"Congestion management considering voltage

security of power systems", Congestion in a

power market happens because of network

limits. In a congested power system,

transactions are not feasible unless the system

operator uses a method to relieve the

congestion. In a deregulated power market, the

system operator has to pay to market

participants to alter their powers to mitigate the

congestion and finally to make feasible all

power transactions. After applying congestion

management, the system security level may be

low because of hitting some network limits.



ICKDST '19, Pune


Such a network is highly vulnerable against

disturbances. Thus, it is really beneficial for the

system operator to use a method to mitigate the

congestion so that the system security is more

retained after congestion management. Using

the previously introduced methods to retain

security, the system operator has to pay a

considerable fee to relieve congestion.

However, the proposed method, employing the

sensitivities of voltage stability margin,

provides both a higher level of security and

much lower security cost to mitigate

congestion.

From results of testing the proposed

and the previous methods on the New-England

test system, the proposed method has

discernible advantages on all other methods. It

provides more security with a much lower

price; that is, it reduces the cost of providing

security. It not only provides the system with a

greater voltage stability margin but also results

in a better voltage profile. Furthermore, the

proposed method makes the network more

robust against severe contingencies.

Dutta Sudipta and Singh S. P. (2008),

"Optimal Rescheduling of Generators for

Congestion Management Based on Particle

Swarm Optimization”, The present paper

focuses on demonstrating a technique for

optimum selection of generators for congestion

management and additionally the application of

PSO in the solution of the congestion

management problem. Generators from the

system are selected for congestion management

based on their sensitivities to the power flow of

the congested line followed by corrective rescheduling. The problem of congestion is

modeled as an optimization problem and

solved by particle swarm optimization

technique. The method has been tested on 39-

bus New England system, IEEE 30-bus and

118-bus systems successfully. Results obtained

on the 39-bus New England system has been

compared with the results reported using three

other techniques. The appropriateness of the

generator selection methodology has also been

compared with reported techniques on IEEE

30-bus and 118-bus systems. PSO algorithm

has many advantages such as simple concept

and easy understanding; the entire complex

decision making is modeled by two simple (1)

and (2). The robustness of the algorithm is

demonstrated by solving three different

networks of different sizes and complexities

with equal performance. Since the convergence

of the PSO algorithm depends on the

appropriate selection of particle size, inertia

weight and maximum velocity of particles,

improper choice of these parameters may lead

to inferior results or nonconvergence.

However, test results reveal that the proposed

implementation is effective in managing

congestion and outperforms.

Besharat Hadi and Taher Seywd

Abbas (2008), "Congestion management by

determining optimal location of TCSC in

deregulated power systems", Congestion

management is an important issue in

deregulated power systems. FACTS devices

such as TCSC by controlling the power flows

in the network can help to reduce the flows in

heavily loaded lines. Because of the

considerable costs of FACTS devices, it is

important to obtain optimal location for

placement of these devices. In this paper, two

sensitivity-based methods have been developed

for determining the optimal location of TCSC

in an electricity market. In a system, first two

optimal locations of TCSC can be decided

based on the sensitivity factors aij and bij and

then optimal location is selected based on

minimizing production cost plus device cost. Test results obtained on two 5-bus power

systems show that sensitivity factors along with

TCSC cost could be effectively used for

determining optimal location of TCSC. The

effect of TCSC on line outage in order to relive

congestion has also been studied. It can be

observed from the results of line outage that we

can relieve congestion by setting the installed

TCSC.


DIFFERENT TECHNIQUE


Acharya Naresh and Mithulananthan N.

(2007), “Locating series FACTS devices for

congestion management in deregulated

electricity markets", LMP difference and

congestion rent contribution methodologies are

proposed for locating series FACTS devices to

manage congestion in deregulated electricity

markets. The proposed methodologies are

based on LMPs that are by-products of OPF

problem formulation. The proposed methods

are tested on three test systems with different

sizes and complexities, namely IEEE 14, IEEE

30 and IEEE 57, and validated through look-up

tables formed by exhaustive search for each

test case. Result shows that proposed methods,

unlike sensitivity methods where non-linearity

in not captured, correctly capture the best

locations for series FACTS devices for

congestion management in deregulated

electricity market.

Mendez Roberto and Rudnick Hugh

(2004), "Congestion management and

transmission rights in centralized electric

markets”,A static simulation model is proposed

and developed for nodal and zonal dispatching

implementing marginal theory to incorporate

CMS under FTR and FGR. The transmission

rights systems are defined under a centralized

electric market, with the main contribution of

this work being the FGR valuation, which is

directly obtained from the centralized ZLMP

differences contained in the respective FG

defined from the nodal dispatch. Then,

compatibility in implementation between FTR

and FGR are defined, so that both financial

instruments against price congestions are

evaluated for a possible implementation under

the same market structure. Although the FGR

model outlined in this work presents certain

advantages in relation to the FTR, the

instability of zonal definition and the poor

performance of a hybrid CMS, made

unattractive the zonal price modeling

complemented with FGR, as compared to a

nodal model with FTR, where there is

experience in actual implementation. The

proposal is of interest in centralized dispatch

pool markets.

Kumar Ashwani ey al. (2004), "A zonal

congestion management approach using real

and reactive power rescheduling”, In this

paper, a new zonal-based congestion

management approach has been presented. The

zones have been formed based on the

combined effect of real and reactive line power

flow sensitivity indexes. An optimal power

flow model minimizing the congestion cost for

redispatch of generators and capacitors

considering a general market structure with

pool, bilateral, and multilateral contracts has

been studied. The test results on a 39-bus New

England system and 75-bus Indian system

reveal the following.

The congestion costs in all of the cases

based on the proposed method are found

to be quite less compared with those

obtained from a dc model .

The congestion costs for cases employing

reactive power support from generators and

capacitors are considerably less than the

cases without any reactive support.

The reactive power support utilized from an

optimally located capacitor in the system is

more effective in reducing congestion cost

as compared to additional reactive power

support taken from the generators.

The amount of rescheduling of real power

transactions is reduced in the presence of

reactive support considered in the system

for congestion management.

The proposed approach is computationally

efficient and simple as it utilizes the

sensitivity factors, which can be easily

updated.

Yamina H.Y. and Shahidehpour S.M.

(2003), "Congestion management coordination

in the deregulated power market", This paper

presents new model to generate Benders cuts

by the ISO in case of any congestion

management infeasibility is detected. Also, it

explains how to include transmission security

Benders cuts in the GENCOs’ price-based unit

commitment problem in a deregulated power

market structure. The proposed model can be

used in deregulated power markets such as

New England, California, Australia and New

Zealand power markets where GENCOs are



ICKDST '19, Pune


taking the risk of committing their units and the

ISO is responsible for the system security. The

test on the 36 unit GENCOs shows the

effectiveness of the proposed model in solving

the problem of infeasibility in congestion

management through a cooperative process

between the ISO and the GENCOs.

Singh S.N. and A. K. David A.K.

(2000), "Towards dynamic security-

constrained congestion management in open

power market", An optimal transmission

dispatch methodology that takes into account

consumer willingness to pay to avoid

curtailment and uses sensitivity information of

TEM with respect to the change in generation

from critical generators to noncritical

generators has been proposed in this letter. The

case studies illustrate that the critical and

noncritical generator pair that has the highest

sensitivity is the first choice suitable for

scheduling. However, depending on contractual

and price obligations, other pairs with high

sensitivity may be preferentially selected.

It was also observed that with some priority

arrangement coordination among generators

would reduce the power curtailment in both

pool and bilateral transactions. The most

significant result of these findings is that

different philosophies of curtailment

management, rescheduling in response to static

and dynamic security concerns, and mixes of

these strategies can be explored using these

methodologies.

III. PROBLEM STATEMENT

After observing the features and challenges of

the literature review, it reveals significance of

adopted stochastic search methodologies for

congestion management in a deregulated

electrical market. Those meta-heuristic

methods include Firefly algorithm , PSO and

ALO . Although these aforementioned

algorithms are applied for congestion

management, it needs to adopt significant

improvements to meet the challenges yet.

Firefly algorithm is reliable, secure and

inexpensive algorithm, however, in some cases

it gets struck into local minima. Moreover, the

parameters of the algorithm are independent of

time and memory power is very low.

Subsequently, PSO algorithm is highly utilized

for reducing cost of rescheduling of generators

and it have the ability to handle the congestion

management under small and large networks

with less computational time, but the premature

convergence is a leading issue under this

algorithm. On the other hand, ALO requires

only less number of fitness evaluations which

provides effective convergence; however, it

may cause complexity in solving discrete

problems. Therefore, it is essential to maintain

the congestion management in a deregulated

electrical environment through the

implementation of an effective optimization

algorithm.

IV. RESEARCH GAPS AND

CHALLENGES

The examination of features and challenges of

the models that specified in literature is

analyzed. It exposes the importance of

espoused stochastic search modalities for

managing the congestion in a deregulated

electrical market. The meta-heuristic models

comprise Firefly algorithm Md Sarwar and

Anwar Shahzad Siddiqui (2015), Sadhan Gope,

Arup Kumar Goswami, Prashant Kumar

Tiwari and Subhasish Deb (2016), PSO Sumit

Verma and V. Mukherjee (2016), J. Jeslin

Drusila Nesamalar, P. Venkatesh and S.

Charles Raja (2016) and ALO S. Verma and V.

Mukherjee (2016). Even though the aforesaid

algorithms are successfully smeared in

managing the congestion, still, it needs some

significant improvement in rectifying certain

challenges. It is observed that Firefly algorithm

is more reliable, protective as well as

inexpensive. However, for some situation; it

becomes struck into some local minima.

Further, it has some parameters like time

independence, low memory power.


DIFFERENT TECHNIQUE


Consequently, PSO algorithm is effectively

exploited for cost minimization in generator

rescheduling. It also has the capacity of

handling the congestion management in minor

and high networks even in less computational

time. However, premature convergence is a

principal issue in this algorithm. In contrast to

this, ALO needs only minimum fitness

evaluations that grant efficient convergence.

However, it often suffers from intricacy in

resolving the discrete problems. Hence to solve

all the mentioned issues, it is vital to maintain

the congestion in a deregulated power

environment via the application of a

resourceful optimization algorithm.

TABLE-1 FEATURES AND CHALLENGES

Author

[Citation]

Adopted

Methodology

Features Challenges

Sarwar

and Anwar

Firefly

algorithm

Provide economical, reliable

and secure operating

conditions

Reduced rescheduling cost

Get trapped into several local

optima

Parameters of algorithm do

not change with time

Sumit and

Mukherjee

Particle

Swarm

Optimization

Reduced rescheduling cost

Able to handle small as well

as large networks

Slow convergence in refined

search stage

Trapped in local area

Verma and

Mukherjee

Ant lion

optimisation

Need to find less number of

fitness function

Not trapped in local minima

Effective convergence

Complexity in solving

discrete problems

Jeslin et

al.

Particle

Swarm

Optimization

Less cost

Less computational time

Less power loss

problem of premature

convergence

Tendency to a fast and

premature convergence in

mid optimum points

Sadhan et

al.

Firefly

algorithm

Provide maximum security to

the network

Reduce the congestion cost

Get trapped into several local

optima

Lack of exploration



ICKDST '19, Pune


V. CONCLUSION

In this paper after reviewing of literature

related to congestion management in

deregulated power system features and

challenges of diverse methodologies for

congestion management, research gaps and

challenges were studied and need to implement

new LA and LPGW method to remove

congestion and reduce rescheduling cost.

VI. REFERENCES

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deregulated environment", Engineering Science and

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congestion management using a novel ant lion

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DIFFERENT TECHNIQUE


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review on market power in deregulated electricity

market", International Journal of Electrical Power &

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"Locating series FACTS devices for congestion

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