Application of Particle Swarm Optimization Algorithm Based on Matlab in Microgrid Scheduling
Particle Swarm Optimization (PSO) is an optimization algorithm based on swarm intelligence, which simulates the behavior of birds foraging, and searches for the optimal solution through collaboration and information exchange. Microgrid scheduling refers to the reasonable allocation and scheduling of various energy sources in the microgrid under the premise of considering the reliability and economy of power supply to meet the needs of users. This article will introduce how to use Matlab-based particle swarm optimization algorithm for microgrid scheduling, and give the corresponding source code.
First, we need to define the objective function and constraints of the microgrid scheduling problem. In a microgrid, the production, storage and consumption of energy includes multiple elements, such as solar photovoltaic power generation, wind power generation, fuel power generation, storage batteries, etc. Our goal is to minimize the total cost of the grid while satisfying user demands and system constraints. Here we can define the total cost as:
Cost = w1 * Cost_fuel + w2 * Cost_battery + w3 * Cost_demand
Among them, Cost_fuelrepresents the cost of fuel, Cost_batteryrepresents the cost of energy storage equipment, Cost_demandrepresents the cost of user demand, w1, w2and w3are the corresponding weight coefficients.
Before microgrid scheduling, we first need