Optimal Scheduling of Microgrid Considering the Interruptible Load Shifting Based on Improved Biogeography-Based Optimization Algorithm

Bo Li,Jue Wang,Hongsheng Deng

doi:10.3390/sym13091707

Abstract

A microgrid is an efficient method of uniting distributed generations. To ensure the applicability and symmetry of the microgrid, the environmental benefits and economic costs are considered to comprehensively model the optimal operation of the microgrid under the grid-connected operation mode, at the same time, considering the effect of interruptible load on the operating cost of the microgrid, the power shifting for interruptible load is attempted on the basis of battery storage capacity. By adaptively adjusting the migration rate using the habitat suitability index of a normalized individual and adding a certain differential perturbation to the migration operator of the migration mechanism, an improved biogeography-based optimization algorithm is proposed and the microgrid optimization dispatching algorithm based on the improved biogeography-based optimization is applied. The advancement and effectiveness of the proposed algorithm and model is verified by the example, and the simulation results indicate that the implementation of the power dispatching scheme proposed in this paper can effectively reduce the total cost of the system. Moreover, the proper consideration of shifting interruptible load, the effective load management and guiding the electricity consumption behavior of users are of certain significance for optimizing the utilization of renewable energy and improving the system efficiency and economy.

Highlights

With global warming and the depletion of energy, renewable clean energy, which includes wind and solar power, has gradually attracted people’s attention
The number of convergence iterations of the optimization algorithm proposed in this paper is significantly less than the other three algorithms. This is mainly due to the fact that the improved BBO (IBBO) algorithm normalizes the individuals of each generation on the basis of the biogeography-based optimization (BBO) algorithm and adds disturbance processing to the migration mechanism to speed up the optimization speed and reduce convergence iterations of the algorithm, which makes it easier to obtain the optimal value of the operating cost from the IBBO algorithm
This paper proposes a multi-objective optimal dispatching model of distributed power generation in the microgrid grid-connected mode that combines operating costs and environmental benefits

Summary

Introduction

With global warming and the depletion of energy, renewable clean energy, which includes wind and solar power, has gradually attracted people’s attention. In [12], the optimization model of a microgrid, considering the economy, environment and system operation risks, is built, and a multi-objective particle swarm algorithm based on niche technology is used to deal with this model. In [17], the optimal configuration model is established, which included the investment cost of equipment, environmental protection cost, operation cost, maintenance cost and fuel cost, and the improved bacterial foraging algorithm (BFA) is used to deal with the problem of optimal configuration for the hybrid island operation of a microgrid. In [18], considering several objectives including economic benefits, network loss and environmental costs, by introducing elite strategy, reverse learning mechanism and global memory, a microgrid optimization operation method based on advanced gravitational search algorithm is applied. A multi-objective optimization strategy considering interruptible load shifting is proposed in this paper

Methods

Results

Conclusion