Computer Science editorial
Open AccessOA2025
A Multi-Objective Optimization Dynamics for Sustainable Smart Grid Design of Engineering Disciplines
This study develops an integrated multi-objective optimization model for sustainable smart grid design, incorporating power generation, demand, reliability, efficiency, maintenance costs, material lifespan, and emissions. The model addresses critical challenges across multiple engineering disciplines to minimize total cost while maximizing environmental sustainability and energy efficiency.
Albert Shikongo; L. Matsebula· Engineering Headway· 2025· DOI 10.4028/p-Gvd5vt
The core problem
The rapid advancement of smart technologies has increased the demand for reliable, cost-effective, and environmentally sustainable energy systems. This study recognizes the need for a multi-disciplinary approach to design and optimize modern power grids. The authors propose an integrated mathematical optimization model for sustainable smart grid development that engages electrical, mechanical, metallurgical, civil, and control engineering disciplines. The objective is to minimize the total cost of energy generation, distribution, and infrastructure while sustaining the environment and maximizing energy efficiency and reliability.
Innovation
The study derives an integrated mathematical optimization model that incorporates power generation, energy demand, reliability, efficiency, maintenance costs, material lifespan, and emissions. The model is subject to a set of constraints that ensure system balance, capacity limits, minimum reliability, efficiency, and compliance with environmental regulations. The optimization variables are designed to address critical challenges faced by various engineering fields: electrical engineering focuses on efficient distribution and reliability of energy; mechanical engineering on performance and longevity of turbines and power systems; metallurgical engineering on material durability and efficiency; civil engineering on infrastructure required to support the grid; and control engineering contributes automated solutions for load balancing and integration of renewable energy sources. The model is formulated as a multi-objective optimization framework that provides a comprehensive solution.
Introduction
The rapid advancement of smart technologies has increased the demand for reliable, cost-effective, and environmentally sustainable energy systems. This study recognizes the need for a multi-disciplinary approach to design and optimize modern power grids. The authors propose an integrated mathematical optimization model for sustainable smart grid development that engages electrical, mechanical, metallurgical, civil, and control engineering disciplines. The objective is to minimize the total cost of energy generation, distribution, and infrastructure while sustaining the environment and maximizing energy efficiency and reliability.
Why it matters
The study demonstrates the importance of a multi-disciplinary approach in designing sustainable smart grids. The integrated optimization model effectively addresses the complex trade-offs between cost, reliability, efficiency, and environmental impact. The involvement of electrical, mechanical, metallurgical, civil, and control engineering disciplines ensures that the model captures the diverse requirements of modern power grids. The authors hope that by optimizing these variables, the model will contribute to the development of smart grids that are not only cost-effective but also environmentally sustainable and reliable. Future research could extend the model to include additional factors such as social acceptance and policy constraints.
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