Optimal Unit Commitment for Renewable Energy and Energy Storage Integrated Power System

Abstract

As the demand for electricity rises, effective management of generating units becomes essential for ensuring a reliable and sustainable energy supply. The Unit Commitment Problem (UCP) plays a critical role in scheduling generation units to meet fluctuating load demands while minimizing operational costs. Concurrently, the Combined Economic Emission Dispatch (CEED) problem addresses the dual objectives of reducing fuel costs and harmful emissions from power plants. This research focuses on optimizing these interconnected problems within the IEEE 39-bus system, featuring 10 generating units, while incorporating renewable energy sources (RESs) and energy storage systems (ESSs).

The study employs the African Vulture Optimization Algorithm (AVOA) for solving the UCP to achieve an operational cost of $559,791.23 and emissions totalling 26,608.40 tons per day without considering the associated transmission losses. Utilizing the Multi-Objective African Vulture Optimization Algorithm (MOAVOA) for the CEED problem resulted in a significant reduction of emissions to 22,748.63 tons per day, illustrating the trade-offs between economic efficiency and environmental impact. Additionally, the integration of PV systems at 10% and 20% penetration levels showed substantial emissions reductions, even as operational costs increased slightly. The research further explores the role of ESSs in managing variability in PV output, thereby enhancing grid reliability and reducing the risk of load shedding.

Overall, this study highlights the importance of developing balanced strategies that integrate cost considerations, emissions reduction, and renewable technologies. It advocates for continued investment in innovative energy solutions and supportive regulatory frameworks to facilitate the transition to cleaner, more resilient energy systems.