Optimal Operating Schedule for Energy Storage System: Focusing on Efficient Energy Management for Microgrid

Sooyoung Jung,Yong Tae Yoon

doi:10.3390/pr7020080

Abstract

A microgrid is a group of many small-scale distributed energy resources, such as solar/wind energy sources, diesel generators, energy storage units, and electric loads. As a small-scale power grid, it can be operated independently or within an existing power grid(s). The microgrid energy management system is a system that controls these components to achieve optimized operation in terms of price by reducing costs and maximizing efficiency in energy consumption. A post-Industry-4.0 consumer requires an optimal design and control of energy storage based on a demand forecast, using big data to stably supply clean, new, and renewable energy when necessary while maintaining a consistent level of quality. Thus, this study focused on software technology through which an optimized operation schedule for energy storage in a microgrid is derived. This energy storage operation schedule minimizes the costs involved in electricity use. For this, an optimization technique is used that sets an objective function representing the information and costs pertaining to electricity use, while minimizing its value by using Mixed Integer Linear Programming or a Genetic Algorithm. The main feature of the software is that an optimal operation schedule derivation function has been implemented with MATLAB for the following circumstances: when the basic operation rules are applied, when operating with another grid, when the external operating conditions are applied, and when the internal operating conditions are applied.

Highlights

A microgrid is a small-scale power grid consisting of a series of small-scale distributed energy resources (DER) and loads, such as solar/wind energy sources, diesel generators, and energy storage, operating independently or within an existing power grid(s) [1]
This study focuses on the operation and control of a microgrid in a zero-energy smart city, dealing in particular with software technology that derives an optimal operation schedule for city, dealing in particular with software technology that derives an optimal operation schedule for energy storage storage in in aa microgrid microgrid [2]
The results of the simulation are described where Python 3.7.1 and MATLAB R2018b were used in Windows OS 10 using an Intel i7-770 CPU 3.6 GHz with 16 GB RAM

Summary

Introduction

A microgrid is a small-scale power grid consisting of a series of small-scale distributed energy resources (DER) and loads, such as solar/wind energy sources, diesel generators, and energy storage, operating independently or within an existing power grid(s) [1]. In the era of post-Industry-4.0, optimal design and control of energy storage based on an accurate demand forecast using big data is essential to stably supply clean, new, and renewable energy when necessary, while maintaining a consistent level of quality, whereas energy producers are required to efficiently and stably manage integrated energy resources produced from new and renewable energy production facilities, and existing nuclear, thermal, co-generation, and gas-turbine power plants. For energy consumers, an accurate power demand forecast that takes into account various types of power consumption patterns depending on their housings, and the Processes 2019, 7, 80; doi:10.3390/pr7020080 www.mdpi.com/journal/processes Processes. This study focuses on the operation and control of a microgrid in a zero-energy smart is needed. This study focuses on the operation and control of a microgrid in a zero-energy smart city, dealing in particular with software technology that derives an optimal operation schedule for city, dealing in particular with software technology that derives an optimal operation schedule for energy storage storage in in aa microgrid microgrid [2]

Objectives

Methods

Results

Conclusion