考虑风电与光伏机组出力下农村微网系统运行优化模型研究

Robust Optimization Model for Multi-Grid Scheduling in Rural Micro Grids Based on Uncertainty of Wind Power and Photovoltaic Output

我国农村电网架构薄弱,限制了光伏扶贫等政策的开展,造成了可再生能源中弃风、弃光、弃水等现象的出现,如何将农村丰富的生物质能与风电、光伏构建成具有多能互补特性微网系统是解决上述问题主要途径.因此,本文建立了包含风力机组、光伏发电、蓄能系统和生物质能的农村微网系统,考虑了风电与光伏出力的不确定性,满足机组运行、系统备用、系统负荷平衡多能约束条件,构建了基于不确定性多情景下农村微网多能调度鲁棒优化模型.针对传统启发式算法早熟、容易陷入局部最优的问题,运用GAMS求解农村多能流微能网调度模型.算例结果表明,算法有效降低系统日运行成本,证明了模型的正确性.农村多能流微网系统的建设能够有效消纳富裕的风、光可再生能源及秸秆粪便等生物质能,对改善农村环境污染问题具有重要意义.

China’s weak rural power grid structure restricts the development of photovoltaic poverty alleviation policies,resulting in the emergence of wind,photovoltaic and water curtailment.How to construct a micro-grid system with multi-energy complementarity including abundant biomass energy in rural areas,wind and photovoltaic generation is the main way to solve these issues.Therefore,a rural micro-grid system including wind turbine,photovoltaic power generation,energy storage system and biomass energy is established in this paper.Considering the uncertainty of wind power and photovoltaic output,the multi-energy constraints of unit operation,system reserve and system load balance are satisfied,and the multi-energy dispatch of rural micro-grid based on multiple uncertain scenarios is constructed.In order to solve the problem of premature and easy to fall into local optimum in traditional heuristic algorithm,the gold search method of Pareto solution set is used to solve the rural multi-energy flow micro-energy network scheduling model.The Golden Section method mainly solves the negotiation solution of the search model by narrowing the range containing the extreme value until the search area is less than the given error.The example shows that the algorithm effectively reduces the daily running cost of the system,and proves the correctness of the model.The construction of rural multi-energy micro-grid system can effectively consume abundant biomass energy,such as straw manure,and renewable energy,such as wind and photovoltaics,which is of great significance to improve rural environmental pollution.