Abstract
The integration of energy storage facilities into existing structures will result in increased costs. Therefore, it is of great significance to optimize the configuration of integrated power systems with multienergy flows to reduce the cost of the comprehensive utilization of energy. This study established a wind-solar-battery-fuel cell integrated power supply system to optimize the grid-connected regional power supply. First, the load is given with a known daily energy demand. The optimization goal is to minimize the average annual cost and the loss of power supply probability. The cost model includes the constraints of transportation costs and the benefits of selling hydrogen and oxygen. Then, an improved genetic algorithm is developed to optimize the structure of the wind-solar-battery-fuel cell integrated power supply system. The basic idea of the improved genetic algorithm is to change the coordination mode of the crossover operator and the mutation operator according to the size of the initial population fitness. Finally, according to the calculation results of the improved genetic algorithm, the optimal configuration of the capacity of devices in the system is obtained, verifying the effectiveness of the improved genetic algorithm. The cost calculation result of the genetic algorithm is 18.7% higher than that of the improved genetic algorithm, and it completely converges at approximately 70 steps. The cost calculation result of the particle swarm optimization is 17.1% higher than that of the improved genetic algorithm, and it completely converges at approximately 75 steps. The cost calculation result of the nondominated sorting genetic algorithm is 9.6% higher than that of the improved genetic algorithm, and it completely converges at approximately 58 steps. The system established in this research can fully meet the power demands for a given area and effectively reduce the local curtailment of wind energy and solar energy.
Highlights
With the rapid growth of the global economy and population, energy demand is becoming increasingly
1) In order to optimize the grid-connected regional power supply, a wind-solar-battery-fuel cell integrated power supply system is established. This system can fully meet the power demand for a given area and effectively reduce the local curtailment of wind energy and solar energy caused by poor power generation due to equipment capacity configurations
When the output electricity of the system cannot meet the load demand, hydrogen enters the proton exchange membrane fuel cells (PEMFCs) to continue the power supply
Summary
With the rapid growth of the global economy and population, energy demand is becoming increasingly. This paper uses an improved genetic algorithm (IGA) to optimize the wind-solar-batteryfuel cell multienergy flow integrated power supply system configuration to ensure that the load power shortage rate is zero while at the same time reducing the transportation cost and average cost and providing a configuration scheme for a regional power supply, proving the adaptability and effectiveness of the proposed algorithm, which can be used as a reference for future values. This improvement can make the algorithm jump out of the local optimal solution and allow the choice of whether to perform a crossover operation or mutation operation first according to the size of the individual fitness gap This system can fully meet the power demand for a given area and effectively reduce the local curtailment of wind energy and solar energy. 2) Considering the shortcomings of traditional genetic algorithms, we proposed an improved genetic algorithm to optimize the structure of the wind-solar-battery-fuel cell integrated power supply system.
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