摘要
在南方区域现货市场两级运作阶段,仅有部分省份开展现货市场交易,因此需要综合考虑不同省份市场化改革所处的不同阶段,在充分考虑全网新能源发电消纳、负荷预测、水电计划和检修计划的基础上,采用多目标发电控制方法对新能源发电的最大化消纳。在进行搜索多代理均衡解时间内,智能体个数的增长往往会导致DCEQ(λ)算法呈几何数增加,其结果将会导致在电网里面的应用范围十分局限,同时也限制了控制性能的发展和提升。为此,为了解决该问题,采用了一种基于WoLF-PHC和资格迹构成的狼爬山算法。其算例结果表明了该算法的有效性,较其他多目标发电控制方法而言,具有快速收敛速率的狼爬山算法更能适应环境的变化。
In the two-level operation stage of the southern regional spot market,only some provinces carry out spot market transactions.Therefore,it is necessary to comprehensively consider the different stages of the market-oriented reform in different provinces.On the basis of fully considering the new energy generation consumption,load forecasting,hydropower plan and maintenance plan of the whole network,the multi-objective generation control method is adopted to maximize the consumption of new energy generation.In the time of searching multi-agent equilibrium solution,the increase of the number of agents will often lead to the geometric increase of DCEQ(λ)algorithm,which will result in a very limited application scope in the power grid,and also limit the development and improvement of control performance.Therefore,in order to solve this problem,a wolf climbing algorithm based on WoLF-PHC and qualification trace is adopted.The simulation results show the effectiveness of the algorithm.Compared with other multi-objective generation control methods,wolf mountain climbing algorithm with fast convergence rate can adapt to the change of environment better.
作者
胡亚平
赵化时
朱文
杨爱洲
孙宇
HU Ya-ping;ZHAO Hua-shi;ZHU Wen;YANG Ai-zhou;SUN Yu(China Southern Power Grid,Guangzhou 510000 China;Dongfang Electronics Corporation,Yantai 264000 China)
出处
《自动化技术与应用》
2020年第7期114-118,共5页
Techniques of Automation and Applications
关键词
现货市场
多目标发电控制
智能体
狼爬山算法
spot market
multi-target power generation control
agent
Wolf Climbing Algorithm
