Optimizing DG Units and EV Charging Stations for Sustainable Cities

Transforming Urban Power Grids: A New Approach to Distributed Energy and Electric Vehicle Integration

With the global push towards electrification and decarbonization, cities are witnessing a transformative shift in their power grid architectures. The fusion of distributed energy resources with the rise of electric mobility is redefining how power systems function. Distributed Generation (DG) technologies, such as solar panels, wind turbines, and fuel cells, are now pivotal in minimizing transmission losses and boosting energy reliability. Concurrently, the surge in electric vehicle (EV) usage is altering demand patterns, challenging existing distribution networks.

This raises a crucial question for smart city development: how can Distributed Generation units and fast Electric Vehicle Charging Stations (EVCS) be strategically placed within power networks to enhance performance and minimize negative impacts? A recent study proposes a unified optimization framework that determines the optimal placement and sizing for both DG units and fast EVCS. This approach addresses the intricate balance between generation and load introduced by high EV penetration, which can result in increased power losses, voltage instability, and network stress.

Two bio-inspired algorithms—Particle Swarm Optimization (PSO) and Artificial Bee Colony (ABC)—are employed to tackle this complex optimization challenge. These algorithms are inspired by collective behaviors in nature, allowing for efficient exploration of vast solution spaces. Their effectiveness was tested on the IEEE 69-bus test system and a real-world 33 kV network in Ghana’s Ashanti region, providing both theoretical and practical evidence.

The results showcase a significant improvement in network performance when DG units and fast EVCS are optimally co-located. Under scenarios with up to 40% integration, there was a remarkable reduction in active power losses by as much as 68%. This surpasses many traditional planning strategies, emphasizing the benefits of coordinated allocation. Moreover, voltage profiles were stabilized within the strict ±5% limits set by international standards. PSO proved superior in minimizing voltage deviation indices, highlighting its better convergence behavior and solution quality.

Beyond these technical gains, the findings have broader societal implications. Reduced power losses lead to improved energy efficiency and lower operating costs, while better voltage stability ensures reliable electricity delivery. This is crucial for rapidly urbanizing regions, particularly in emerging economies. Furthermore, enabling higher penetration of renewable DG sources alongside EV infrastructure contributes to significant reductions in greenhouse gas emissions, aligning with global climate objectives.

Looking forward, this integration strategy offers new avenues for smart city energy planning. The simultaneous optimization of DG and EVCS can be expanded to include dynamic elements like real-time load variability, renewable generation intermittency, and vehicle-to-grid (V2G) interactions. Advanced forecasting and adaptive control mechanisms could further enhance system resilience. Additionally, employing hybrid or next-generation metaheuristic algorithms could further optimize performance, especially in large-scale networks.

For utility providers, policymakers, and urban planners, this research offers a scalable framework for designing future-ready energy systems. By demonstrating the benefits of coordinated deployment strategies, it challenges the traditional siloed approaches to infrastructure planning.

This work represents a shift in the conception of energy systems: from static networks to dynamic ecosystems where generation, consumption, and mobility are interconnected. Through the application of swarm-based optimization, it provides a forward-thinking solution to one of the key challenges in sustainable urban development, paving the way for cleaner, smarter, and more resilient cities.

Reference

Author: Isaac Prempeh^a, Albert K. Awopone ^a, Patrick N. Ayambire ^a, Ragab A. El-Sehiemy ^b

Title of original paper: Optimal allocation of distributed generation units and fast electric vehicle charging stations for sustainable cities

Article link: https://www.sciencedirect.com/science/article/pii/S2773153725000313

Journal: Green Energy and Intelligent Transportation

DOI: 10.1016/j.geits.2025.100281

Affiliations:

a Department of Electrical and Electronics Engineering, Akenten Appiah-Menka University of Skills Training and Entrepreneurial Development, Kumasi, Ghana

b Electrical Engineering Department, Kafrelsheikh University 33516, Kafrelsheikh, Egypt