电网技术
電網技術
전망기술
POWER SYSTEM TECHNOLOGY
2011年
11期
43-49
,共7页
张节潭%苗淼%范宏%程浩忠%张洪平%姚良忠%Bazargan Masoud
張節潭%苗淼%範宏%程浩忠%張洪平%姚良忠%Bazargan Masoud
장절담%묘묘%범굉%정호충%장홍평%요량충%Bazargan Masoud
风电场%电源规划%二层规划%调频%调峰%环保%模拟植物生长算法
風電場%電源規劃%二層規劃%調頻%調峰%環保%模擬植物生長算法
풍전장%전원규화%이층규화%조빈%조봉%배보%모의식물생장산법
wind farm%generation expansion planning%bi-level planning%frequency regulation%peak regulation%environment protection%plant growth simulation algorithm
按分解协调的思想,建立了考虑调峰、调频及环保约束的净收益最大化双层电源规划模型,计及了上网电价差异对电源规划的影响。上层规划为电源投资决策问题,以发电商总收益最大为目标函数,决策变量是待选电厂的投建时间和台数以及已有电厂的退役时间和台数;下层规划为生产优化决策问题,其又可以分成机组检修计划和随机生产模拟2个子问题,决策变量分别为发电机组的检修时段以及各发电机组在负荷曲线上的运行位置。提出了模拟植物生长算法、最小累积风险度法、等效电量频率法相结合的求解方法。算例结果验证了所建模型的合理性和有效性。
按分解協調的思想,建立瞭攷慮調峰、調頻及環保約束的淨收益最大化雙層電源規劃模型,計及瞭上網電價差異對電源規劃的影響。上層規劃為電源投資決策問題,以髮電商總收益最大為目標函數,決策變量是待選電廠的投建時間和檯數以及已有電廠的退役時間和檯數;下層規劃為生產優化決策問題,其又可以分成機組檢脩計劃和隨機生產模擬2箇子問題,決策變量分彆為髮電機組的檢脩時段以及各髮電機組在負荷麯線上的運行位置。提齣瞭模擬植物生長算法、最小纍積風險度法、等效電量頻率法相結閤的求解方法。算例結果驗證瞭所建模型的閤理性和有效性。
안분해협조적사상,건립료고필조봉、조빈급배보약속적정수익최대화쌍층전원규화모형,계급료상망전개차이대전원규화적영향。상층규화위전원투자결책문제,이발전상총수익최대위목표함수,결책변량시대선전엄적투건시간화태수이급이유전엄적퇴역시간화태수;하층규화위생산우화결책문제,기우가이분성궤조검수계화화수궤생산모의2개자문제,결책변량분별위발전궤조적검수시단이급각발전궤조재부하곡선상적운행위치。제출료모의식물생장산법、최소루적풍험도법、등효전량빈솔법상결합적구해방법。산례결과험증료소건모형적합이성화유효성。
The impacts of wind farms on system peak regulation, frequency regulation, and environmental protection are analyzed. To take above-mentioned impacts of wind farms into account and the impact of different generation price on investment decision, based on the idea of decomposition coordination, a bi-level generation expansion planning model for power grid containing large-scale wind farms is built. In this model the net earning maximization and the constraints of peak regulation, frequency regulation and environment protection are considered, in addition the influence of the differences among pool purchase prices on generation expansion planning is taken into account. The upper-level planning is a power source investment decision-making problem, so the total revenue maximization of gencos is taken as objective function and the decision variables are the construction time of the power plants to be build and the numbers of the generators to be installed in these plants, the retirement time of existing power plants and numbers of generators in these plants; the lower-level planning is a production optimization decision problem that can be divided into two subproblems, namely the maintenance scheduling and stochastic production simulation, and the decision variables are maintenance time intervals of generating units and the operating positions of generating units on load curve. To solve the proposed model, the plant growth simulation algorithm is integrated with minimum cumulative risk algorithm and equivalent energy and frequency function method is adopted. The feasibility and efficiency of the proposed model are verified by the results of numerical example.