复杂预想场景下电力系统备用优化模型_舒隽

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复杂预想场景下电力系统备用优化模型
舒隽 1，李春晓 2，苏济归 3，董伟 2
(1． 华北电力大学电气与电子工程学院， 北京市 昌平区 102206； 2． 廊坊供电公司， 河北省 廊ห้องสมุดไป่ตู้市 065000； 3．宜昌供电公司，湖北省 宜昌市 443000)
Optimal Reserve Dispatch Model Considering Complicated Contingency Scenarios
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rate. The scenario sets composed of single scenarios are introduced to express multiple scenarios. A scenario set consists of three subsets: generator malfunction subset, transmission equipment malfunction subset and load fluctuation subset. Based on the scenario set, an optimal reserve dispatch model considering complicated contingency scenarios is proposed. The objective is to minimize the sum cost of the electricity and reserve, and is subject to general SCUC constraints and some new introduced constraints related to different response rate reserves dispatch, such as capacity limits of generators, branches, and different response rate reserves under different contingency scenarios. The formulation of the optimal reserve dispatch model considering complicated contingency scenarios with nonlinear constraints is transferred to the mixed integer linear programming (MILP) problem, which is able to be solved by commercial MILP solvers. The case studies utilize the CPLEX 11 under the general algebraic modeling system (GAMS) 23 on a Pentium-4 2.53 GHz personal computer. The IEEE 30-bus system is applied to verify the proposed optimal reserve dispatch model. Six cases under contingency scenarios with different degrees of complexity are discussed in detail. The results given in Tab. 1 show that: 1) the optimal solution of reserve capacity and dispatch is determined by given scenario sets; 2) given complicated contingency scenarios, the proposed reserve dispatch model can derive more reliability solutions than the ordinary reserve capacity allocation model considering constant reserve capacity constraint.
第 32 卷 第 10 期 2012 年 4 月 5 日 文章编号：0258-8013 (2012) 10-0105-06
中 国 电 机 工 程 学 报 Proceedings of the CSEE 中图分类号：TM 71 文献标志码：A
Vol.32 No.10 Apr.5, 2012 ©2012 Chin.Soc.for Elec.Eng. 学科分类号：470·40
Extended Summary
正文参见 pp.105-110
Optimal Reserve Dispatch Model Considering Complicated Contingency Scenarios
SHU Jun1, LI Chunxiao2, SU Jigui3, DONG Wei2
Tab. 1
Case 1 2 3 4 5 6 Total cost/$ 12987.253 13013.319 12956.853 13035.354 13119.187 13129.188
Cost in cases
Energy cost/$ 12947.900 12979.958 12952.928 13005.624 13054.136 13057.516 Reserve cost/$ 39.354 33.361 3.925 29.730 65.051 71.672
Enough reserve capacity should be purchased by independent system operator (ISO) to ensure the security operation of power systems considering random load fluctuations and equipment malfunction. It is important to study reasonable reserve capacity and dispatch. As well as unit commitment and economic dispatch, the reserve capacity and dispatch is determined by contingency scenarios. If generator malfunction is considered, the reserve capacity cannot be sufficiently allocated on some generators. If transmission equipment malfunction is considered, the reserve dispatch cannot result in power flow violation on transmission equipment. Besides, considering network constraints, the reserve capacity allocation is also affected by load forecast errors come from loads on different nodes. Furthermore, the high response rate reserve is needed to maintain security operation of power systems for generator malfunction, transmission equipment malfunction and high speed load fluctuation, and the low response rate reserve is allocated for low speed load fluctuation. Consequently, the following efforts are essential to build a reserve dispatch model: 1) reserve allocation is combined with power energy dispatch; 2) the effect of network constraints on reserve allocation is considered; 3) the response rate of reserve demanded by different scenarios is taken into account. To address the above issues, an optimal reserve dispatch model is built considering complicated contingency scenarios based on security constrained unit commitment (SCUC). Integrated with unit commitment, power dispatch, reserve capacity optimization and the reserve dispatch, the optimization model is to minimize the sum cost of the electricity and reserve while being subjected to the security constraints of base case and contingency scenarios. By introducing scenarios classification and the scenarios set, the demand and dispatch of reserves with different response rates are decided by the requirement of different scenarios. Likewise reserve capacity, contingency scenarios are divided into several categories according to changing