考虑源荷不确定性的配电网风光储综合规划

Comprehensive planning of wind-PV-storage in distribution network considering uncertainty of source and load

中文关键词: 风光荷不确定性  概率潮流  综合规划  食肉植物算法  协同进化算法

英文关键词: wind-PV-load uncertainty  probabilistic power flow  comprehensive planning  carnivorous plant algorithm  coevolutionary algorithm

中文摘要:

      针对考虑分布式电源和负荷不确定性的配电网风光储综合规划问题,首先以概率模型表征分布式电源和负荷不确定性,并基于改进半不变量法求解概率潮流；然后考虑投资成本、碳成本、经济收益和电压改善等,以综合效益最大为目标,建立考虑无功补偿装置的风光储综合规划模型,并提出基于食肉植物算法（carnivorous plant algorithm,CPA）和协同进化算法（coevolutionary algorithm,CA）进行求解。该算法将待求解的多主体综合规划问题分解为分布式电源、储能和无功补偿装置3个子规划问题,并基于CPA对每个子问题进行求解,然后通过生态系统协调各种群进化,获取最优规划方案；最后在IEEE33节点和IEEE69节点算例中验证了模型的合理性和求解算法的高效性、普适性。

英文摘要:

      Aiming at the integrated WG- PV- ESS planning problem of distribution network considering the uncertainty of distributed power and load. Firstly, the uncertainty of distributed power and load is characterized by a probabilistic model, and the probabilistic power flow was solved based on the improved semi-invariant method. Then, considering the investment cost, carbon cost, economic benefits and voltage improvement, and aiming at maximize the comprehensive benefit, the comprehensive planning model of WG- PV- ESS comprehensive planning model considering reactive power compensation device is established. A carnivorous plant algorithm based coevolutionary algorithm is proposed to solve the model. In this algorithm, the multi-agent comprehensive planning problem to be solved is decomposed into three sub-planning problems:distributed generation, energy storage and reactive power compensation devices, and each sub-problem is solved based on CPA, and the optimal planning scheme is obtained by coordinating the evolution of various groups through the ecosystem. Finally, the rationality of the proposed model and the efficiency and universality of the solution algorithm are verified by IEEE33 and IEEE69.