基于改进麻雀算法的分布式电源优化配置

Optimal Configuration of Distributed Power Generation Based on Improved Sparrow Search Algorithm

近年来,利用风能、太阳能发电的分布式电源(Distributed Generation,DG)规模与数量在电网中呈现增长的趋势,然而其并网后会对系统潮流分布、电压水平、可靠性和安全稳定性等造成显著影响。因此,考虑DG优化配置问题显得尤为重要。提出了一种DG优化配置模型。该模型以分布式发电系统的年综合成本最小为目标,并且由于其他智能算法对于控制参数依赖性过高问题,在求解方面提出了一种改进的麻雀算法(SSA),验证了模型以及所提出算法的有效性,即在配电网中对DG进行优化配置,可以有效降低配电网的投资成本,并且减小网络损耗,改善电压质量。

In recent years,the scale and number of distributed generation(DG)using wind and solar power have shown an increasing trend in the power grid.However,the grid connection will affect the power flow distribution,voltage level,reliability,safety and stability of the system,etc.,thus causing a significant impact.Therefore,it is particularly important to consider the optimal configuration of DG.A DG optimal configuration model is proposed,which aims to minimize the annual comprehensive cost of the distributed power generation system.Because other intelligent algorithms rely too much on control parameters,an improved Sparrow Algorithm(SSA)is proposed in terms of solving the problem,which verifies the model and all results.The optimal configuration of DG in the distribution network can effectively reduce network losses and the investment cost of the distribution network,and improve voltage quality,and the effectiveness of the proposed algorithm is validated.