Research Of Microgrid Optimal Scheduling Based On Improved Bacterial Foraging Algorithm

As a new kind of energy supply and management system, the microgrid not only has high flexibility and reliability, but also reduce the environmental pollution, improve the utilization rate of energy. The advantages of flexible and reliable, clean and environmental protection, high efficiency and energy saving can be fully played only when the distributed generations in the microgrid are optimized in a reasonable scheduling strategy.The construction of microgrid optimal scheduling model of power generating units mainly include photovoltaic cells, wind turbines, micro gas turbine, fuel cell, diesel engine and battery, starting from the target of the lowest comprehensive power generation cost of microgrid, the fuel consumption cost, operation and maintenance cost, environmental pollution control cost, heating and cooling benefit of the micro sources and the interactive power gains with grid are extensively studied, the BPSO-GA algorithm is proposed by combining the velocity formula of the particle swarm optimization algorithm and the arithmetic crossover of genetic algorithm with the bacterial foraging algorithm. We study the operating characteristics and output curve of distributed generations in the microgrid under different distributed power combination in the simulation, then use BPSO-GA algorithm to optimize the model and the results are compared with the outcome which optimized by bacterial foraging algorithm, the results proved BPSO-GA algorithm had significant advantages in search speed and precision; then the conditions of optimal scheduling of microgrid are studied respectively in time-of-use electricity price, fixed price and real-time price under three different climate conditions which include summer, winter, spring and autumn season, by analysising the status of power supply and output cost of the nine cases suggested that the development of real-time price helps to reduce the comprehensive power generation cost of microgrid, and the result showed that the BPSO-GA algorithm has significant effect on microgrid optimal scheduling and again the rationality and validity of the proposed algorithm and model are verified.