Re-Dispatch Approach for Congestion Relief in Deregulated Power Systems

Transcription

1 Re-Disatch Aroach for Congestion Relief in Deregulated ower Systems Ch. Naga Raja Kumari #1, M. Anitha 2 #1, 2 Assistant rofessor, Det. of Electrical Engineering RVR & JC College of Engineering, Guntur , A., INDIA Abstract In the cometitive ower market environment, congestion is an indicator for the need of transmission system reconfiguration by comensation devices or its exansion with new lines erection. Due to economic considerations, the short time solution like re-disatch is also laying a key role in the resent scenario. In some inevitable cases, moderating the congestion by load shedding is the only solution which is not good in ractice. Hence this aer addresses a solution for congestion relief, i.e. re-scheduling of generators if required simultaneously with load reduction. In re-schedule method, some of the generators are required to increase/decrease their actual market schedule which causes to increase/decrease transmission losses. Simultaneously, the increase in roduction cost so called congestion cost. The IEEE-6 bus IEEE 14 bus test systems are used to show the effectiveness of the roosed method. Keywords Deregulated ower system, Congestion relief, Day- Ahead electricity market, Re-disatch, Load curtailment. I. INTRODUCTION In the deregulated ower system, the system oerator would like to schedule more generation from the cheaest available sources with the objective of roduction cost minimization. But the cometition among ower roducers causes to change their bidding methodologies frequently. The scheduling for this roducer s strategic bidding leads to allocate high MW quantity at lower rice offered utility low MW quantity at higher rice offered utility. By the frequently changing schedules, the ossibility unsecured state due to anyone of the transmission line overloading condition will increase. In deregulated environment, this situation is termed as congestion can avoid with suitable techniques. In [1], the congestion management aroaches have been exlored significantly. Among all these aroaches, the redisatch is one of the short-term solutions which can easily imlement in the day-ahead energy market since the schedules will decide one day rior to the schedule day. Sometimes, congestion relief is not ossible only with reschedule hence the load curtailment is become one of the otion. In this aer, the generation schedule has been cleared by the assumtion of all GENCOS are matory to articiate ool oeration they should adjust their schedule according to the system oerator signals. The system is oerating as day-ahead market with single sided auction mechanism. In this mechanism, only generators will articiate in the market a common aggregate suly curve will develo based on the submitted bids. The intersecting oint with forecasted dem will decide the generation quantities for each market articiants. After market schedule, the ISO will check for congestion feasibility in the system. If system is insecured due to congestion, the remedial actions will take lace. This situation can haen frequently in the cometitive environment. In cometitive market, the GENCOS are ermitted to alter their bid curves before market settling time. To obtain unconstrained cleared quantities in strategic bidding environment, ISO is always exlore to get an idea about GENCOs bid curves which will change frequently with the market signal. The change in bids due to cometition real time incremental cost curves can interrelate in robabilistic manner [2]. In [3], an AC-OF based re-disatch roblem has been roosed to alleviate congestion along with congestion cost allocation. A comutationally simle method for cost efficient generation rescheduling load shedding for congestion management is roosed in [4]. In [5], review of existing congestion management methods with their ros cons in Sanish market based on security constrained unit commitment algorithm, ISSN: htt:// age 1776

2 security constrained otimal ower flow algorithms is resented. In [6], the comrehensive literature survey on congestion management has been given. According this survey, whatever the aroach, the security margin maintenance is the major objective of the ISO. The aer is organized as follows: After the introduction, the Day-Ahead energy market clearing mechanism under erfect mechanism is exlained in Section II. The Section III exlores the congestion relief by using re-disatch in Section IV, load curtailment are exlained. In Section V, case study later conclusions are deduction based on the results. II. DAY-AHEAD ENERGY MARKET SETTLEMENT In this aer, the DA market is organized as a sequence of twenty-four indeendent hourly singlesided auctions, under the uniform ricing rule. The objective function of DA settlement is: Minimize (1) d If the market oerates on a erfect comletion, then the bids submitted by the GENCOs can related with incremental cost curve of that unit. Under this assumtion, the schedule will decide simly economic load disatch without transmission loss [7]. According to this concet, the market clearing rice (MC), generation at a bus G, for a known dem d, can determine analytically as follows: d b (2) b (3) Subjected to the constraint G, d (4) 1 It is required to verify the ossibility of congestion in the network for the above market schedule. In general, the network loading its security level can easily underst with erformance index [8]. The real ower flow based erformance index is given by I l l f l, 2x f (5) where l is the number of transmission lines, f l is the absolute flow of line l f l, is its MVA rating. In case studies, the x is taken as 5. III. COESTION MARKET MODELLI In this market, the ower roducers may submit their incremental decremented bidding rices in a real-time balancing market to relieve congestion. These can then be imlemented in the scheduling roblem to required change in the generator oututs. [9]. In order to achieve the social welfare imization, ISO selects bids from the submitted bids decides the amount of deviations from the referred schedule. The objective function for the congestion management roblem can be formulated as, Minimize C (6) 1 Subjected to balance equation: ND (7) D, 1 1 (8) min where D, is the ower taken at node C is the total congestion cost, are vectors of incremental decremented bids submitted by the generators at node i for re-disatch during congestion, are be the changes in referred schedule is the total generators in the system. ISSN: htt:// age 1777

3 IV. LOAD CURTAILMENT AROACH In this aroach, the system load will reduce until system constraints to satisfy. In order to maintain, ower factor as constant, the real reactive owers both are reduced simultaneously. The Newton-Rahson load flow considered to simulate the system. According to load flow roblem, the changes in injection owers at all the buses can be linearized with the following equations: J Q V s cal cal D, (9) (10) s cal cal D, Q Q Q Q Q Q (11) where Q residual ower injections s cal s Q G, D, D, secified ower injections cal Q calculated owers Q real reactive generations Q real reactive loads load reduction factor The load is reduced on the system u to congestion relieved. This ste needs load flow solution reeatedly. V. RESULTS & DISCUSSIONS A. Test System IEEE 6 Bus System The case study has been erformed on IEEE 6 bus system [10]. In this test system, 11 transmission lines the buses 1, 2 3 are the generator buses they treated as GENCOs in the system. The buses 4, 5 6 are load buses they considered as DISCOs in the system. By assuming single sided market action, the DISCOs are not articiant in the system. The total load on every hour is considered as required market clearing quantity. The total load on the system is about 210 MW. The load is shared among the generators using Market clearing DA mechanism. Incremental cost of delivered ower (system lambda) = $/MWh the otimal disatch of generation: G1= MW; G2= G3= MW. Total generation cost = $/h. The market schedule suffers a loss of MW among 11 transmission lines, 3 lines are being overloaded. The system erformance index is about In order to overcome this situation, the ossibilities are: Case 1: Increment/decrement generation at bus-1 by decrement/increment at bus-2. Case 2: Increment/decrement generation at bus-1 by decrement/increment at bus-3. Case 3: Increment/decrement generation at bus-2 by decrement/increment at bus-3. Case 4: Load reduction on system. For all the above cases, the schedule system erformance is given in Table 1. TABLE I SYSTEM ERFORMANCE FOR VARIOUS CASE STUDIES Case # G1 G2 G3 Loss SI State Base Alert Alert Alert Alert Alert Safe In case 1, the decrement of generation bus-2 is not overcome the congestion roblem. And for the increment, the severity is further increasing. The same situation is haens to the case 2 case 3 also. Hence for this schedule, the re-disatch is not suitable for congestion relief. So the last otion is load curtailment or reduction u to system comes to normal or safe zone. For the 15% of load reduction the market schedule is as follows: Incremental cost of delivered ower (system lambda) = $/MWh the otimal disatch of generation: G1= MW, G2= MW G3= MW. Total generation cost = $/h. The cost of oortunity loss = =370.8 $/h. ISSN: htt:// age 1778

4 B. Test System IEEE 14 Bus System In IEEE 14 bus system, the total transmission lines are 20 generator buses are 5 (i.e. 1, 2, 3, 6 8) the remaining buses are load buses. The bus data line data can be found in [10]. The cost coefficients of each generator have been given in Table-2. Each GENCO has been assumed to submit bids in roortion to its limit. The bids are of 10%, 20%, 30% 40% of its imum limit. The generator bidding arameters are assumed to be constant for the entire day. Gen # TABLE III IEEE 14 BUS SYSTEM COST COEFFICIENTS a b min The exected load on the system over a eriod of 24 hours in the next day has been given in Fig.1. For each trading interval (in this work, we have considered one hour), the dem has been cleared as exlained in Section II. The SM or MC of the system over a eriod of 24 hours is illustrated in Fig.2. We can observe that the system marginal rice or market clearing rice is 3.85 $/MWh. The total roduction cost will be $. With this schedule, the transmission losses of the system has been comuted using Newton Rahson load flow method are equal to 3.463MW. The transmission system is also under normal oerating condition. The line loadings can be observed in Fig.3. The similar rocedure has been erformed for the eak hour also. The system load is equal to MW. We can observe that the system marginal rice or market clearing rice is 4.55 $/MWh. The total roduction cost will be $. With this schedule, the transmission losses of the system have been comuted using Newton-Rahson load flow method are equal to 6.488MW. The transmission system is subjected to over loading condition. The line loadings can be observed in Fig 4. L oa d S c a lin g F a c to r M ark et C learing rice ($ /MW h ) Fig. 1. Forecasted Load Curve of the Scheduled Day Fig. 2. MC or SM of the system for the eriod of 24 hours L ine L oa d in g (% M V A ) Line # Fig. 3. ercentage of Line loadings for Hour 1 ISSN: htt:// age 1779

5 From figure, the line # 14 has been hit its thermal limit. In deregulated environment, this situation is termed as transmission congestion. In order to relief this condition, the system oerator will follow certain market rules regulations. These rules will deendent on market tye country As long as system is under safe conditions, the market will run under economic cometitive conditions. If system is under congestion, the economics will deviate causes to market ower. In order to avoid the market rice hikes during eak hours under unexected disturbances, the need of system strength should be increased by integrating the advanced technologies like Flexible AC Transmission System (FACTS) devices, Distributed Generation etc. L in e lo a d in g (% M V A ) Line # Fig. 4. ercentage of Line loadings for the eak load VI. CONCLUSION This aer has been exlored the Day-Ahead market scheduling under normal as well as congestion states. The re-schedule load curtailment aroaches have been alied to the congestion relief. The case studies once again revels that the re-disatch is not ossible in all the cases. Under this mode, only load reduction will be the alternative solution which is not good in ractice. In order to kee reliability security, the need of transmission system loadability enhancement is also understable from this aer. roduc tion Cos t ($ ) Fig. 5. roduction cost as er SM AB The MC of each trading hour has been illustrated in Figure 5. Deending uon load quantity, the generators schedules are different for each interval. If the market oerates with ay-as- Bid olicy, then the roduction cost will be different. The difference between MC AB for the entire day can be observed in Fig. 5. The imortant thing is that the suliers will get more rofit in SM comare with AB. So in order to encourage market articiants, most of the systems are oerating with SM only. AB SM REFERENCES [1] Ashwani Kumar, S.C. Srivastava, S.N. Singh, Congestion management in cometitive ower market: A bibliograhical survey, Electric ower Systems Research, vol. 76, , July [2] T. Li S. M. Shahidehour, Strategic Bidding of Transmission Constrained GENCOs with Incomlete Information, IEEE Trans. on ower Systems, 20(1), 2005, [3] N.S. Rau, Transmission Loss Congestion Cost Allocation: An Aroach Based on Resonsibility, IEEE Trans. ower Syst. 15(4), 2000, [4] B.K. Talukdar, A.K. Sinha, S. Mukhoadhyay, A. Bose, A Comutationally Simle Method For Cost-Efficient Generation Rescheduling Load Shedding For Congestion Management, Electric ower Energy Syst. 27(5) 2005, [5] E.N. Miguelej, L.R. Rodriguej, A ractical Aroach To Solve ower System Constraints with Alication to the Sanish Electricity Market, IEEE Trans. ower Syst., 19(4), 2004, [6] E. Bomard,. Correia, G. Gross, M. Amelin, Congestion Management Schemes: A Comarative Analysis under A Unified Framework, IEEE Trans. ower Syst., 18(1), 2003, [7] Hadi Saadat, ower System Analysis, (Tata McGraw-Hill Education, 2002) [8] Allen J. Wood Bruce F. Wollenberg, ower Generation, Oeration, Control (J. Wiley & Sons, 1996) [9] Kennedy Mwanza, You Shi, Congestion Management: Re-disatch Alication of FACTS, Master s Thesis 2006, Chalmers University Of Technology, Sweden [10] ISSN: htt:// age 1780