电力系统自动化
電力繫統自動化
전력계통자동화
AUTOMATION OF ELECTRIC POWER SYSTEMS
2012年
8期
38-44
,共7页
蔡秋娜%文福拴%丁剑鹰%洪晖虹%李承军
蔡鞦娜%文福拴%丁劍鷹%洪暉虹%李承軍
채추나%문복전%정검응%홍휘홍%리승군
备用市场%竞价模型%可靠性%多目标粒子群优化算法%熵权决策法
備用市場%競價模型%可靠性%多目標粒子群優化算法%熵權決策法
비용시장%경개모형%가고성%다목표입자군우화산법%적권결책법
Key words: reserve market%bidding model%reliability%multi-objective particle swarm optimization algorithm%entropy weightdecision-making method
针对电力市场环境,发展了综合考虑经济性、可靠性和排放因素的多目标备用竞价模型。为描述与备用供给相关的可靠性,定义了备用不足期望值,其也可用于区分发电机组与可中断负荷在提供备用过程中的差异性。在此基础上,提出了求解多目标备用竞价模型的2阶段求解算法。首先,基于改进的多目标粒子群算法,求解最小化备用容量成本、备用不足期望值和碳排放量3个目标的多目标竞价模型,获得一组Pareto解。之后,采用熵权决策法评价这些Pareto解,从中得到备用最优购买方案。最后,以包含12个竞价机构(包括发电机组和可中断负荷相关机构)的电力市场/系统为例,说明了所发展的备用竞价模型的基本特征和求解算法的有效性。
針對電力市場環境,髮展瞭綜閤攷慮經濟性、可靠性和排放因素的多目標備用競價模型。為描述與備用供給相關的可靠性,定義瞭備用不足期望值,其也可用于區分髮電機組與可中斷負荷在提供備用過程中的差異性。在此基礎上,提齣瞭求解多目標備用競價模型的2階段求解算法。首先,基于改進的多目標粒子群算法,求解最小化備用容量成本、備用不足期望值和碳排放量3箇目標的多目標競價模型,穫得一組Pareto解。之後,採用熵權決策法評價這些Pareto解,從中得到備用最優購買方案。最後,以包含12箇競價機構(包括髮電機組和可中斷負荷相關機構)的電力市場/繫統為例,說明瞭所髮展的備用競價模型的基本特徵和求解算法的有效性。
침대전력시장배경,발전료종합고필경제성、가고성화배방인소적다목표비용경개모형。위묘술여비용공급상관적가고성,정의료비용불족기망치,기야가용우구분발전궤조여가중단부하재제공비용과정중적차이성。재차기출상,제출료구해다목표비용경개모형적2계단구해산법。수선,기우개진적다목표입자군산법,구해최소화비용용량성본、비용불족기망치화탄배방량3개목표적다목표경개모형,획득일조Pareto해。지후,채용적권결책법평개저사Pareto해,종중득도비용최우구매방안。최후,이포함12개경개궤구(포괄발전궤조화가중단부하상관궤구)적전력시장/계통위례,설명료소발전적비용경개모형적기본특정화구해산법적유효성。
In view of the electricity market, a comprehensive multi-objective reserve bidding model is developed considering the factors of economics, reliability and emissions. To describe the supply reliability associated with reserves, the expected reserve deficiency is defined. They can be used to distinguish the capability of a generator and that of an interruptible load in providing the reserve service. On this basis, a two-stage algorithm is presented to solve the multi-objective bidding model. Firstly, the improved multi-objective particle swarm optimization algorithm is employed to find the Pareto solutions of the multi objective bidding model which minimizes the reserve capacity cost, the expected reserve deficiency and the emissions separately. Then, the entropy weight decision-making method is used to evaluate the Pareto solutions, and obtains the optimal reserve allocations among the bidders. Finally, an example of the electricity market with 12 bidders including generators and interruptible loads is employed to illustrate the essential feature of the developed model and its efficiency.