Price area congestion management in radial system under de regulated environment

INTERNATIONAL JOURNAL OF ELECTRICAL ENGINEERING
International Journal of Electrical Engineering and Technology (IJEET), ISSN 0976 –
6545(Print), ISSN 0976 – 6553(Online) Volume 4, Issue 1, January- February (2013), © IAEME
& TECHNOLOGY (IJEET)
ISSN 0976 – 6545(Print)
ISSN 0976 – 6553(Online)
Volume 4, Issue 1, January- February (2013), pp. 100-108
IJEET
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PRICE AREA CONGESTION MANAGEMENT IN RADIAL SYSTEM
UNDER DE-REGULATED ENVIRONMENT- A CASE STUDY

N. G. Savagave
Lecturer, Electrical Engg. Dept.Walchand College of Engg., Sangli
Prof. DR. H. P. Inamdar
Retd. Professor and Head of
Electrical Engg. Dept., Walchand College of Engg., Sangli

ABSTRACT

Under de-regulated environment, due to liberalization, electric utility is having
competition at different levels, except the transmission and distribution, as they remain
monopoly franchise. Due to this structure, there are number of issues raised which are to be
managed, congestion management (CM) is one of them. Out of different methods of CM,
Price Area CM (PACM) is used in open access, bilateral, de-centralized, day-ahead type
electricity market which is present in Nordic countries and in India where, it will be in very
near future. This paper aims to develop a flowchart and software for a-priori bid area
formation and PACM in MATLAB using MATpower tool, which has been validated by
obtaining the simulated results for Western Region Grid, 73-Bus system of India, as a case
study.

Keywords: De-regulated environment; Bid area; Loctional Marginal Price (LMP); PACM

INTRODUCTION

In the past decades, electricity markets have significantly restructured1 throughout the
world, India also has not been an exception. The vertically integrated electricity utility has
been segregated into different independent entities like Genco, Transco, Disco and Resco
companies, devoted to their functions. Due to liberalization, there is competition at Genco
and Resco level. Whereas, Transco and Disco are monopoly franchise. Competition provides
electric power at low cost to the customer along with the better services. In developing
countries, the trend of electricity market is heading towards transmission open access in multi

100


seller/multi buyer system. They make their transaction over the same transmission system. This may
cause the violation of one of the transmission network limit, there by facing it the congestion
problem2,3. There are various methods of alleviating the congestion, which varies depending upon the
structure and nature of electric market available in different countries, worldwide.
The PACM method is mainly used in the Nordic countries like Norway, Sweden, Finland and
Denmark, known as ‘Nordpool’ where, open access, bilateral, de-centralized, day-ahead type
electricity market is exist4. In India also, the Electricity Act 2003 has initiated to undertake
comprehensive market reforms in the sector which is tending towards in the same manner, in very
near future. PACM is based on the zonal pricing which is done by applying market splitting
mechanism.

Figure 1Flowchart for Bid Area Determination

101


NEED OF THE BID AREAS DETERMINATION TECHNIQUE, A-PRIORI

In this paper, PACM is carried out for the radially interconnected power system. In any
system as a whole, considering one area which consists number of generators and loads with their
bids and offers. Considering their aggregated generator and load curves, a market clearing price
(MCP) and corresponding market clearing volume (MCV) or quantity (MCQ) are found under
unconstraint condition.
In case of any violation of transmission limit, for easy prediction of congestion in the tie-line
between the two zones or areas, it is necessary to form first, the bid areas/zones a-priori. For a
radially inter-connected system, the power would flow from low price area to high price area. In
other words, the economic dispatch would take place taking into account the network constraints.
Thus, the area formation is essentially based upon cheaper generation surplus across the
bottleneck. Ideally, the area price would be decided by the original generation in each area. Thus,
the bid area formation is based upon the cheapest marginal generation available in each area. The
Loctional Marginal Price (LMP) is an indicator of this fact5. Thus, to establish the bid areas for a
system, LMPs are used.
Here, for WRG 73-bus system, a flowchart and software have been developed in MATLAB using
MATpower tool for bid area determination a-priori. The Flowchart is as shown below.

WRG 73- BUS SYSTEM- SIMULATED RESULTS

This requires different input data like bus data, branch data, generator data, and generator
cost data. After running optimum power flow (OPF) in MATpower it gives different outputs
consisting generator schedules, load dispatches and graph of LMPs on all buses, injections on
each buses and different bid areas along with the range of values of LMPs.
Thus, the numbers of bid areas are formed using cluster analysis6, depending upon the values of
LMPs which are nearly equal to each other in a particular bid area. It may happen that the buses
having nearly equal LMPs may be situated far apart geographically. Hence, those buses in single
clustered zones picked up that are geographically contiguous and no other bid area encroaches
into the same. The LPM plot is given in the following figure number 1. Also, the LMPmin,
LMPmax and the bar chart is given for different loadability factors.

LMPs
136
LMP std
134 LMP mean
LMP max
132
LMP min
130

128
Ms
L P

126

124

122

120

118

116

0 10 20 30 40 50 60 70
BUS No

Figure 1: LMP Plot

102

January

Table 1: Zones Formation
Zone LMP Range Bus Nos. No. Of buses
No. Rs/MW
/MW
1 115.54 – 115.99 1-34,67-69,71-73 40
2 119.97 – 127.03 35-49,50-66,70 33

Table 2: WRG
Loadability LMP LMP
Factor Min Max LMP Min LMP Max

350
1 109.86 127.04
300
1.1 116.26 135.83
1.2 122.66 144.79 L 250
1.3 129.08 153.91 200
1.4 135.52 164.81 M
150
1.5 141.99 176.88
P 100
1.6 148.5 190.15
1.7 155.07 205.05 50

1.8 161.72 222.28 0
1.9 169.58 244.64 1 1.1 1.2 1.3 1.4 1.5 1.6 1.7 1.8 1.9 2 2.1
2 178.66 274.87 Loadability Factors
2.1 187.75 317.32
Figure 2: Bar Chart
Discussion
From the results it can be seen that total numbers of 40 buses belongs to a single bid area by
n f
virtue of having comparable LMP values. Similarly, 33 Buses for the other bid area. The
establishment of two bid areas essentially underlines the fact that the network takes the shape of
radially inter connected system then it comes to market splitting. Thus, the algorithm established
further can be used to resolve congestion by market splitting.
splitt

With the application of PACM on 73-bus WRG system, the elegant nature of such problem
73 bus
formulation can be demonstrated. In other words, though the practical system is meshed system, the
establishment of two area system makes it radially inter connected so long as price zones are
connected
concerned. This reduces the problem size drastically, improves simplicity many folds, when compared
to conventional OPF based calculation. The results for PACM are provided in the next section.

PACM FOR RADIAL SYSTEM

In Market splitting, bid areas are defined a priori depending upon potentially congested lines
rket
as seen in the earlier section. In a simple two bid area system, there are two types of bid areas as high
price (load surplus) and low price (generation surplus). All generators and loads in each area bid into
the power exchange. After this system operator and power exchange (market operator) are
coordinating among each other for market splitting operation. Within the network two bid areas have
been identified, as transmission line connecting them may be subjected to the congestion. The Figure
smission
3 shows that there are two bid areas identified within the network, as the transmission line connecting
the areas may be subjected to the congestion.

103


Figure 3: Two bid area system

The transmission line has a maximum capacity of Pabmax. In area A generation facilities with
low marginal cost are located, whereas in area B there are major loads with little supply. Thus area A
is a low price area and area B is high price area. In first action of market splitting, market is cleared as
there is no transmission constraint, thus there will be a unique system price Psys for the whole market.
In this operation of unconstraint market clearing respective schedules for the generators and the loads
are determined in each bid area depending upon the selected bids and offers. Thus line flows in the
network are also known. Figure 4 illustrate the whole process as in case of unconstraint market
clearing process line flow on the line between area A & area B is Pab, which is more than the
maximum limit of line(Pabmax), So this flow should be kept at the maximum flow limit of the line (i.e.
Pabmax). Thus market will split into two price areas. So the market operator now maximizes the
arbitrage trade i.e. fully utilizes the line capacity up to its maximum flow limit. It seems as market
operator purchase the amount Pabmax from the generator surplus area and sells it back in the load
intense area. This activity could be simulated in the market scenario as shift in demand and supply
curves in area A and area B respectively. Shift in the demand curve in area A is by amount of Pabmax
in the right direction while in area B supply curve would have to shift in right direction (along the x-
axis) as shown in the figure below.

Figure 4: Two zone price area example

104


As prices in area A (PAN) and area B (PBN) increased and decreased respectively due to virtual
shift in demand and supply curves of the areas, the social welfare is maximized in net. Since market
operator has done the complete activity to settle the trade and purchased power at lower price while
selling at higher price thus will earn the net profit, which is nothing but the network rental or
congestion rental (cost). This rental may be used to invest in the transmission system expansion or
may be allocated among the participants in terms of the tariff relief or other. [133].

The flowchart for PACM is as shown below:

105


INPUT DATA OF WRG SYSTEM FOR PACM:
Table 3: Generator Bid Data Table 5: Line Data
Area Bid a b c Q
No. No. (MW) From To X Line
1 1 0 0.086 45 30 Area Area (in pu) flow
1 2 0 0.015 20 300 limit
(MW)
1 3 0 0.052 30 80 1 2 0.0466 100
1 4 0 0.088 35 40
1 5 0 0.720 40 20
1 6 0 0.098 90 10 OUTPUT DATA OF WRG SYSTEM FOR PACM:
2 1 0 0.094 45 50 Table 6: Generator Bid Selected
2 2 0 0.076 55 60
2 3 0 0.082 90 15 Area Bid Q
2 4 0 0.088 40 40 No. No. (MW)
2 5 0 0.085 90 40 1 1 0
1 2 300
2 6 0 0.095 95 20
1 3 77
1 4 0
Table 4: Load Offer Data 1 5 0
Area Bid a b c Q 1 6 0
No. No. (MW) 2 1 50
1 1 0 0 85 20 2 2 25
1 2 0 0 80 10 2 3 0
1 3 0 0 76 10 2 4 40
2 5 0
1 4 0 0 64 6
2 6 0
1 5 0 0 72 8
1 6 0 0 60 10
1 7 0 0 85 10
1 8 0 0 88 10
1 9 0 0 86 5
1 10 0 0 74 10
1 11 0 0 62 20
1 12 0 0 70 10
1 13 0 0 75 10
1 14 0 0 78 5
1 15 0 0 82 4
1 16 0 0 83 3
1 17 0 0 60 3
1 18 0 0 61 7 PA1
1 19 0 0 64 9 Rs.
33.99
PA2
1 20 0 0 65 10 Rs.
56.87
1 21 0 0 72 5
1 22 0 0 71 5
1 23 0 0 73 8
1 24 0 0 77 9
1 25 0 0 67 7
1 26 0 0 69 2
1 27 0 0 73 3
1 28 0 0 34 5

106


1 29 0 0 32 10 Table 7: Load Offer Selected
1 30 0 0 30 5
1 31 0 0 45 5 Area Bid Q Area Bid Q
No. No. (MW) No. No. (MW)
1 32 0 0 38 10
1 33 0 0 36 10 1 1 20 1 37 5
1 34 0 0 34 5 1 2 10 1 38 5
1 3 10 1 39 20
1 35 0 0 32 7
1 4 6 1 40 10
1 36 0 0 30 8 1 5 8 2 1 10
1 37 0 0 45 5 1 6 10 2 2 60
1 38 0 0 38 5 1 7 10 2 3 20
1 39 0 0 36 20 1 8 10 2 4 10
1 40 0 0 34 10 1 9 5 2 5 5
2 1 0 0 85 10 1 10 10 2 6 10
2 2 0 0 82 60 1 11 20 2 7 10
2 3 0 0 88 20 1 12 10 2 8 5
2 4 0 0 86 10 1 13 10 2 9 8
1 14 5 2 10 5
2 5 0 0 83 5
1 15 4 2 11 10
2 6 0 0 81 10
1 16 3 2 12 10
2 7 0 0 78 10 1 17 3 2 13 5
2 8 0 0 72 5 1 18 7 2 14 6
2 9 0 0 71 8 1 19 9 2 15 2
2 10 0 0 80 5 1 20 10 2 16 8
2 11 0 0 73 10 1 21 5 2 17 10
2 12 0 0 70 10 1 22 5 2 18 4
2 13 0 0 75 5 1 23 8 2 19 0
2 14 0 0 62 6 1 24 9 2 20 10
2 15 0 0 66 2 1 25 7 2 21 0
1 26 2 2 22 0
2 16 0 0 64 8
1 27 3 2 23 0
2 17 0 0 67 10 1 28 5 2 24 5
2 18 0 0 69 4 1 29 0 2 25 0
2 19 0 0 49 5 1 30 0 2 26 0
2 20 0 0 59 10 1 31 5 2 27 0
2 21 0 0 53 20 1 32 10 2 28 0
2 22 0 0 45 9 1 33 10 2 29 0
2 23 0 0 53 10 1 34 5 2 30 0
2 24 0 0 57 5 1 35 0 2 31 0
2 25 0 0 46 5 1 36 0 2 32 0
2 33 0
2 26 0 0 41 6
2 27 0 0 43 2
2 28 0 0 42 8 Table 8: MCPs Table 9: Line Flows
2 29 0 0 50 10
2 30 0 0 49 4 Price Bid MCP Line Flow
2 31 0 0 40 10 Area Areas Rs/MWh No. (MW)
2 32 0 0 35 10 in PA
1 1 33.99 1 100
2 33 0 0 39 10
2 2 56.87

107


CONCLUSION

From the results, it can be seen that the market splitting has taken place across the
congested corridor, whose flow is limited to Pmax of the corridor. Area 1 has cheaper surplus
generation while area 2 is dominant in load. This is the reason why area 2 price is higher
compare to area 1.

ACKNOWLEDGEMENT

Authors are thankful to the Electrical Department of IIT, Delhi for providing all data
for completion of this paper.

REFERENCES

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Volume 3, Issue 1, 2012, pp. 210 - 225, Published by IAEME

AUTHORS’ INFORMATION

N. G. Savagave is senior lecturer in Department of Electrical engineering of Walchand
College of Engineering, sangli pursuing PhD in Shivaji University, Kolhapur;

Prof. Dr. H. P. Inamdar, Retd. Professor and HOD of Electrical Engineering Department of
Walchand College of Engineering, Sangli. He has guided many students from MTech, PhD
and published many papers in international journals.

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Price area congestion management in radial system under de regulated environment

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