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Price area congestion management in radial system under de regulated environment
Price area congestion management in radial system under de regulated environment
Price area congestion management in radial system under de regulated environment
Price area congestion management in radial system under de regulated environment
Price area congestion management in radial system under de regulated environment
Price area congestion management in radial system under de regulated environment
Price area congestion management in radial system under de regulated environment
Price area congestion management in radial system under de regulated environment
Price area congestion management in radial system under de regulated environment
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Price area congestion management in radial system under de regulated environment

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  • 1. 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© IAEME: www.iaeme.com/ijeet.aspJournal Impact Factor (2012): 3.2031 (Calculated by GISI) ©IAEMEwww.jifactor.com 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
  • 2. International Journal of Electrical Engineering and Technology (IJEET), ISSN 0976 –6545(Print), ISSN 0976 – 6553(Online) Volume 4, Issue 1, January- February (2013), © IAEMEseller/multi buyer system. They make their transaction over the same transmission system. This maycause the violation of one of the transmission network limit, there by facing it the congestionproblem2,3. There are various methods of alleviating the congestion, which varies depending upon thestructure and nature of electric market available in different countries, worldwide.The PACM method is mainly used in the Nordic countries like Norway, Sweden, Finland andDenmark, known as ‘Nordpool’ where, open access, bilateral, de-centralized, day-ahead typeelectricity market is exist4. In India also, the Electricity Act 2003 has initiated to undertakecomprehensive market reforms in the sector which is tending towards in the same manner, in verynear future. PACM is based on the zonal pricing which is done by applying market splittingmechanism. Figure 1Flowchart for Bid Area Determination 101
  • 3. International Journal of Electrical Engineering and Technology (IJEET), ISSN 0976 –6545(Print), ISSN 0976 – 6553(Online) Volume 4, Issue 1, January- February (2013), © IAEMENEED OF THE BID AREAS DETERMINATION TECHNIQUE, A-PRIORI In this paper, PACM is carried out for the radially interconnected power system. In anysystem as a whole, considering one area which consists number of generators and loads with theirbids 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 underunconstraint condition.In case of any violation of transmission limit, for easy prediction of congestion in the tie-linebetween the two zones or areas, it is necessary to form first, the bid areas/zones a-priori. For aradially inter-connected system, the power would flow from low price area to high price area. Inother 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 thebottleneck. 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. TheLoctional Marginal Price (LMP) is an indicator of this fact5. Thus, to establish the bid areas for asystem, LMPs are used.Here, for WRG 73-bus system, a flowchart and software have been developed in MATLAB usingMATpower 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 generatorcost data. After running optimum power flow (OPF) in MATpower it gives different outputsconsisting generator schedules, load dispatches and graph of LMPs on all buses, injections oneach 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 ofLMPs which are nearly equal to each other in a particular bid area. It may happen that the buseshaving nearly equal LMPs may be situated far apart geographically. Hence, those buses in singleclustered zones picked up that are geographically contiguous and no other bid area encroachesinto 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
  • 4. International Journal of Electrical Engineering and Technology (IJEET), ISSN 0976 –6545(Print), ISSN 0976 – 6553(Online) Volume 4, Issue 1, January- February (2013), © IAEME 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 ChartDiscussion From the results it can be seen that total numbers of 40 buses belongs to a single bid area by n fvirtue of having comparable LMP values. Similarly, 33 Buses for the other bid area. Theestablishment of two bid areas essentially underlines the fact that the network takes the shape ofradially inter connected system then it comes to market splitting. Thus, the algorithm establishedfurther 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 busformulation can be demonstrated. In other words, though the practical system is meshed system, theestablishment of two area system makes it radially inter connected so long as price zones are connectedconcerned. This reduces the problem size drastically, improves simplicity many folds, when comparedto 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 rketas seen in the earlier section. In a simple two bid area system, there are two types of bid areas as highprice (load surplus) and low price (generation surplus). All generators and loads in each area bid intothe power exchange. After this system operator and power exchange (market operator) arecoordinating among each other for market splitting operation. Within the network two bid areas havebeen identified, as transmission line connecting them may be subjected to the congestion. The Figure smission3 shows that there are two bid areas identified within the network, as the transmission line connectingthe areas may be subjected to the congestion. 103
  • 5. International Journal of Electrical Engineering and Technology (IJEET), ISSN 0976 –6545(Print), ISSN 0976 – 6553(Online) Volume 4, Issue 1, January- February (2013), © IAEME Figure 3: Two bid area system The transmission line has a maximum capacity of Pabmax. In area A generation facilities withlow marginal cost are located, whereas in area B there are major loads with little supply. Thus area Ais a low price area and area B is high price area. In first action of market splitting, market is cleared asthere 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 loadsare determined in each bid area depending upon the selected bids and offers. Thus line flows in thenetwork are also known. Figure 4 illustrate the whole process as in case of unconstraint marketclearing process line flow on the line between area A & area B is Pab, which is more than themaximum 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 thearbitrage trade i.e. fully utilizes the line capacity up to its maximum flow limit. It seems as marketoperator purchase the amount Pabmax from the generator surplus area and sells it back in the loadintense area. This activity could be simulated in the market scenario as shift in demand and supplycurves in area A and area B respectively. Shift in the demand curve in area A is by amount of Pabmaxin 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
  • 6. International Journal of Electrical Engineering and Technology (IJEET), ISSN 0976 –6545(Print), ISSN 0976 – 6553(Online) Volume 4, Issue 1, January- February (2013), © IAEME As prices in area A (PAN) and area B (PBN) increased and decreased respectively due to virtualshift in demand and supply curves of the areas, the social welfare is maximized in net. Since marketoperator has done the complete activity to settle the trade and purchased power at lower price whileselling at higher price thus will earn the net profit, which is nothing but the network rental orcongestion rental (cost). This rental may be used to invest in the transmission system expansion ormay be allocated among the participants in terms of the tariff relief or other. [133].The flowchart for PACM is as shown below: 105
  • 7. International Journal of Electrical Engineering and Technology (IJEET), ISSN 0976 –6545(Print), ISSN 0976 – 6553(Online) Volume 4, Issue 1, January- February (2013), © IAEMEINPUT DATA OF WRG SYSTEM FOR PACM:Table 3: Generator Bid Data Table 5: Line DataArea 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 0Table 4: Load Offer Data 1 5 0Area Bid a b c Q 1 6 0No. 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
  • 8. International Journal of Electrical Engineering and Technology (IJEET), ISSN 0976 –6545(Print), ISSN 0976 – 6553(Online) Volume 4, Issue 1, January- February (2013), © IAEME 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
  • 9. International Journal of Electrical Engineering and Technology (IJEET), ISSN 0976 –6545(Print), ISSN 0976 – 6553(Online) Volume 4, Issue 1, January- February (2013), © IAEMECONCLUSION From the results, it can be seen that the market splitting has taken place across thecongested corridor, whose flow is limited to Pmax of the corridor. Area 1 has cheaper surplusgeneration while area 2 is dominant in load. This is the reason why area 2 price is highercompare to area 1.ACKNOWLEDGEMENT Authors are thankful to the Electrical Department of IIT, Delhi for providing all datafor completion of this paper.REFERENCES 1. Y.R. Sood, N.P. Padhye, and H.O. Gupta, “Restructuring of power industry – a bibliographical survey”, in proceeding of IEEE power Engineering Society Winter Meeting, Vol. 1, January 27-31 2002, pp.163-167. 2. R.S. Fang, A.K. David, “Transmission congestion management in an electricity market”, IEEE Trans. Power Syst. 14 (August (2)) (1999) 877–883. 3. R.D. Christie, B.F. Wollenberg, I. Wangstien, “Transmission management in the deregulated environment”, Proc. IEEE 88 (February (2)) (2000) 170–195 4. R.D. Christie, I. Wangensteen, “The energy market in Norway and Sweden: introduction”, IEEE Power Eng. Rev. (February) (1998) 44–45. 5. D. Sun, “LMP and FTR in the standard market design”, in: Proceedings of IEEE PES Summer Meeting, vol. 3, July 21–25, 2002, pp. 1269–1270. 6. C.-N. Yu, M. Ilic, “Congestion clusters-based markets for transmission management”, in: Proceedings of IEEE PES, Winter Meeting, New York, NY, January 1999, pp. 821–832. 7. The Electricity Act 2003 from http://www.cercind.gov. In. 8. Suresh J. Thanekar, Waman Z. Gandhare and Anil P. Vaidya, “Voltage Stability Assessment Of A Transmission System -A Review” International Journal of Electrical Engineering & Technology (IJEET), Volume 3, Issue 2, 2012, pp. 182 - 191, Published by IAEME 9. Thanhlong Duong, Jiangang Yao and Vietanh Truong, “Optimal Placement Of Tcsc Based On Min-Cut Algorithm For Congestion Management In Deregulated Electricity Market” International Journal of Electrical Engineering & Technology (IJEET), Volume 3, Issue 1, 2012, pp. 210 - 225, Published by IAEMEAUTHORS’ INFORMATIONN. G. Savagave is senior lecturer in Department of Electrical engineering of WalchandCollege of Engineering, sangli pursuing PhD in Shivaji University, Kolhapur;Prof. Dr. H. P. Inamdar, Retd. Professor and HOD of Electrical Engineering Department ofWalchand College of Engineering, Sangli. He has guided many students from MTech, PhDand published many papers in international journals. 108

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