Techno-economic And Energy Storage Configuration Optimization For Grid-tied Micro-grids Considering Demand Side Management

With the continuous development of economy and society,people’s demand for energy is also increasing.Renewable energy is regarded as one of the most effective solutions to the problem of fossil energy shortage and environmental pollution,and has received great attention.The solar energy had been used widely as a typical distributed power generation technology.Due to its stochastic and intermittent nature,it is usually used in conjunction with energy storage systems.With the continuous develop ment of human society,people has new demands on the quality and form of energy,and the modularized and functional micro grid system of power supply came into being,which has become the trend of future power grid development.Under such a background,this thesis investigates the design of a small grid connected micro-grid system for household power supply,and conducts the following research:In order to further tap the potential of the user side in energy saving and cost saving,based on the user’s demand and frequency of using of different electrical appliances,the electrical appliance usage of the user’s demand side is classified and modeled.The design and energy scheduling strategy of the system are optimized for this purpose.Based on the system’s energy consumption indicators,economic indicators and user satisfaction,a techno economic optimization model for the optimal energy scheduling scheme of the system is established,and the effectiveness of the new energy scheduling strategy is verified through the simulation,revealing the potential incorporating demand side management.On the basis of the above system,a study on the optimal configuration of the system’s energy storage module capacity is carried out.With the goal of maximizing the solar energy exploitation models and economic benefits of the system,single-objective and multi-objective optimization are established for different design needs,and the effectiveness of the model is verified through the simulation.On the basis of the case study,the effect of different prices of household batteries on the selection of system energy storage modules is investigated.Some improvements have been made to the optimization algorithm used in the thesis.Aiming at the difficulty of using a single meta-heuristic algorithm to obtain satisfactory results in single-objective optimization problems,a knowledge-based hybrid optimization algorithm is designed inspired by the idea of hybrid optimization algorithms and with the combination of the knowl-edge background of practical problems.In view of the difficulty of obtaining the Pareto front in the Multi-objective Evolutionary Algorithm Based on Decomposition(MOEA/D)used in the multi-objective optimization problem,some improvements are made to the particle update strategy in the algorithm.To demonstrate the improvements of the algorithms,comparative studies are carried out to verify the effectiveness of the improved algorithms.