Research On Optimal Scheduling Of Microgrid Based On Interior Search Algorithm

Since the industrial Revolution,machines have increased the efficiency of people's work,and they have consumed a wealth of fossil energy which providing abundant material products.Human excessive dependence on fossil energy not only destroys the ecological environment,but also causes local conflicts.In order to solve the contradiction between these problems and the increase of the demand of per capita energy,human have developed renewable energy such as wind,light,ocean energy and biomass energy.Renewable energy is environmentally friendly and non-polluting,but its output power is highly volatile and fluctuates greatly with environmental changes such as seasons and climate.At present,the existing power grid structure cannot effectively adapt to the changes brought about by renewable energy,but microgrid technology can effectively solve these problems.The microgrid is a small-scale power distribution system that splits the power grid into many small parts,and it is composed of distributed power sources in a certain area.The renewable energy can be consumed within a certain area,reducing the amount of power transmitted to the grid.When the microgrid fails,it can be isolated from the external power grid in time,reducing the cost of rotating spares and maintaining voltage stability.At present,since the microgrid is in the initial stage,it has a high comprehensive cost.The optimization of microgrid research can allocate distributed power output more reasonably,reducing system operating costs and improving environmental benefits.This paper establishes a microgrid model,including photovoltaic cells,wind turbines,diesel generators,fuel cells,and batteries,and then optimizes the scheduling of the grid.Considering that the peak-to-valley difference of the load is large,it may lead to insufficient power supply at the peak of power consumption and abandonment of wind and light when the power is low.Therefore,a demand response strategy based on time-of-use electricity price is introduced,which effectively shifts the load demand and reduces the fluctuation range of the load.In this paper,two objective functions,namely the lowest operating cost and the lowest pollution cost,are set in the optimal scheduling.According to the characteristics of each power supply,the corresponding constraints are established.Based on this,the internal search algorithm is used to optimize the model and get the power output values of the grid-connected mode and the islanding operation.In order to improve the performance of the internal search algorithm,the adaptive coefficients are introduced into the algorithm parameters,and the effects of the algorithm are verified by three test functions.Finally,combined with the power model established in this paper,the typical scheduling strategy is developed in the grid-connected mode and the island mode,and the calculation results are compared with the numerical values of the optimized scheduling strategy.The results show that the optimal scheduling strategy can effectively reduce the operating cost of the micro-grid and achieve better environmental benefits.