International Journal of Computer Science and Technology

International Journal of Computer Science and Technology | Vol. 4, No. 3, March 2023 | pp. 1–8

DOI: 10.46882/2023/IJCST/000218

Article Type: Original Research Paper

Title: Optimizing Energy Usage in Smart Grids via Distributed Multi-Agent Reinforcement Learning

Names of Authors: Aleksei Ivanov¹, Chidi Okoro²

Authors’ Affiliations: ¹Power Systems Computing Lab, Saint Petersburg Tech University, Saint Petersburg, Russia; ²Department of Electrical Engineering, University of Ibadan, Ibadan, Nigeria

Abstract: Modern electrical grids struggle to balance dynamic consumer power demands with highly volatile renewable energy sources like wind and solar. Centralized grid management models face communication delays and scalability bottlenecks when coordinating millions of independent endpoints. This paper presents a decentralized energy management framework that uses a Multi-Agent Deep Deterministic Policy Gradient (MADDPG) model. In this setup, independent software agents represent localized residential neighborhoods and regional solar generation grids. These agents learn to coordinate energy storage allocations and balance localized loads by exchanging minimal peer-to-peer state messages. We simulated this multi-agent architecture using a 120-node electrical distribution setup. The empirical results show a 24.3% reduction in peak-hour grid stress along with an 18.5% optimization in local battery utilization. The decentralized architecture maintained operational stability even during sudden 40.0% generation drops caused by shifting weather conditions. This multi-agent coordination approach provides a resilient method to scale green energy integration across municipal utility networks.

Keywords: Smart Grids, Multi-Agent Systems, Reinforcement Learning, Renewable Energy, Load Balancing, Energy Storage

Manuscript Timeline: Received: June 10, 2022; Revised: July 15, 2022; Accepted: August 05, 2022; Published: March 05, 2023

Subscribe to read the full article: https://internationalscholarsjournals.org/subscribe-to-read