Incorporating energy storage and user experience in isolated microgrid dispatch using a multi-objective model

TL;DR

This paper presents a multi-objective dispatch model for isolated microgrids that integrates energy storage and user satisfaction, optimizing economic, environmental, and user experience factors.

Contribution

It introduces a novel multi-objective optimization framework incorporating energy storage and user experience metrics for microgrid dispatch.

Findings

The proposed model effectively balances multiple objectives in microgrid operation.

The -dominance evolutionary algorithm provides well-distributed Pareto solutions.

Simulation demonstrates improved decision-making for microgrid dispatch.

Abstract

In order to coordinate multiple different scheduling objectives from the perspectives of economy, environment and users, a practical multi-objective dynamic optimal dispatch model incorporating energy storage and user experience is proposed for isolated microgrids. In this model, besides Microturbine units, energy storage is employed to provide spinning reserve services for microgirds; and furthermore, from the perspective of demand side management, a consumer satisfaction indicator is developed to measure the quality of user experience. A two-step solution methodology incorporating multi-objective optimization (MOO) and decision analysis is put forward to address this model. First, a powerful heuristic optimization algorithm, called the {\theta}-dominance based evolutionary algorithm, is used to find a well-distributed set of Pareto-optimal solutions of the problem. And thereby, the best compromise solutions (BCSs) are identified from the entire solutions with the use of decision analysis by integrating fuzzy C-means clustering and grey relation projection. The simulation results on the modified Oak Ridge National Laboratory Distributed Energy Control and Communication lab microgrid test system demonstrate the effectiveness of the proposed approach.