Application of Control Algorithms for Battery Scheduling in Grid-Connected Energy Prosumers

This paper proposes an innovative approach in managing prosumer batteries using a rule-based control algorithm. The main information used in this work to develop actions on a Battery Energy Storage System (BESS) are the price of energy on the day-ahead electricity market, the prosumer consumption/pr...

Full description

Saved in:
Bibliographic Details
Published in2024 IEEE 22nd Mediterranean Electrotechnical Conference (MELECON) pp. 932 - 937
Main Authors Becchi, Lorenzo, Bindi, Marco, Intravaia, Matteo, Grasso, Francesco, Pasqui, Mattia, Carcasci, Carlo
Format Conference Proceeding
LanguageEnglish
Published IEEE 25.06.2024
Subjects
Battery Energy Storage System
Economics
Electricity supply industry
Energy Management System
Optimization Algorithms
Optimization methods
Prediction algorithms
Processor scheduling
Production
Renewable Energy Communities
Renewable energy sources
Online AccessGet full text

Cover

More Information
Summary:This paper proposes an innovative approach in managing prosumer batteries using a rule-based control algorithm. The main information used in this work to develop actions on a Battery Energy Storage System (BESS) are the price of energy on the day-ahead electricity market, the prosumer consumption/production forecasts and the effect of charging/discharging operations on battery degradation. In order to evaluate the performance of the rule-based approach, a comparison with other optimization algorithms commonly used in the literature is proposed. Performance is evaluated in terms of economic gain and energy exchanged between prosumer and network. The rule-based algorithm proposed in this paper exploits a neural predictor to forecast load and production forecasts and processes the trend of the electricity market in order to find the best management of the BESS. The results obtained show the best performance of the proposed algorithm compared to the most common optimization methods and the possibility of easily extending this logic to control a large number of users. This is possible also thanks to the extremely low computational cost of the proposed approach, around twenty times faster than a Mixed-Integer Linear Programming (MILP) algorithm. This fact is very interesting regarding the diffusion of modern Renewable Energy Communities (RECs).
ISSN:2158-8481
DOI:10.1109/MELECON56669.2024.10608734