电力市场环境下基于多智能体的多目标电网规划方法

网络阻塞费用是表征电力市场竞争程度的指标之一。提出了一种以网络阻塞费用、线路投资和由于传输容量不足引起负荷缺失最少为目标的多目标网络规划模型,依据分层求解的思想设计了基于多智能体的网络规划体系结构并用其对模型进行求解。初始规划层的母线智能体以降低阻塞为目标相互协商形成初始规划集并将其传送给决策规划层;决策规划层采用遗传算法在初始规划集中搜索规划方案,并进行N-1安全校验和阻塞校验,得到优化可行解。该网络规划体系是开放式结构,可以在知识库中考虑各种不确定因素。通过IEEE RTS-14节点算例仿真表明,考虑阻塞的网络规划能够以最少的投资费用为市场参与者提供公平的电能输送平台,最大限度地满足电力传送。

Multi-Agent based multi-objective network planning in power market environment

Congestion cost is an index of competitiveness in power market.A multi-objective network planning model is proposed,which takes the least congestion cost,investment and load loss caused by insufficient transmission capacity as its objectives.A multi-layer network planning struc-ture based on multi-Agent is designed to resolve the multi-objective planning model.The bus agents of the original planning layer take the less congestion as its objective and negotiate with each other to form the original planning set,which is then transferred to the decision-making planning layer.There,the genetic algorithm is used to search the planning schemes in the original planning set and the N-1 security check and congestion check are carried out to get the optimal feasible solution.The network planning system is of open structure and various uncertain factors are considered in knowledge base.The proposed model is tested with IEEE RTS-14 system and results show that it provides a fair platform to meet the power transmission requirements as more as possible with the least investment.