Research On Multi-objective Operation Optimization Of Microgrid

With the growing number of controllable appliances and optimization objectives,developing a fast and efficient approach of microgrid optimization has become one of the current research focuses.Taken a typical community microgrid with smart electric appliances,household photovoltaic and distributed energy storage system as research subject,this thesis studies its optimization control structure,mathematic optimization model,multi-objective optimization algorithm and multi-time scale optimization strategy.The main research contents and results are shown as follows:(1)Study the modelling of community microgrid and its multi-agent system.For a community microgrid with public energy storage system and households,which is equipped with photovoltaic battery,storage battery and smart appliances,the photovoltaic output forecast model,SOC update model,load model as well as microgrid model is developed.Based on the analysis of electric appliance relation,a three-layer MAS with local level,coordination level and central level is established.The function of each agent is designed together with the information flow structure of MAS.(2)To address the problem that existent algorithms are not efficient when dealing with multi-objective long-term dynamic optimization,combine MAS with optimization model and propose a layered optimization algorithm based on NSGA-II.The proposed algorithm decomposes the complicated microgrid comprehensive optimization into several less complex household optimizations and one microgrid central optimization.Household optimization model has objectives of electricity bill and charge-discharge cycle of energy storage battery minimization is developed.The microgrid optimization model aims to minimize operation cost,photovoltaic shedding time and peak-valley rate.Household operation is optimized first using NSGA-II.The central optimization problem is then solved based on household operation mode set.(3)To address the incapability of existent two-stage operation in meeting the demand of current microgrid,a short-term operation adjustment approach is proposed.One-day-ahead operation plan is given by NSGA-II-based layered optimization algorithm.In real operation,when the accumulative deviation is below threshold,allocate the deviation proportionally to each energy storage battery using SOC and nominal capacity as weight in order to minimize the SOC deviation of each battery and to maximize safety margin.When the accumulative deviation is beyond allowable limit,regenerate operation plan.The test results on an eco-city community grid show that the proposed layered optimization algorithm and multi-time scale optimization approach is effective and satisfying.An optimization system platform is also developed and put into operation.The proposed optimization algorithm is based on multi-agent system.Due to the plug-and-play characteristic of MAS,when microgrid structure change occurs,only the corresponding agent change is needed.