A Review of Metaheuristic Optimization Techniques for Effective Energy Conservation in Buildings

Abstract

The built environment is a significant contributor to global energy consumption and greenhouse gas emissions. Advancements in the adoption of environmentally friendly building technology have become crucial in promoting sustainable development. These advancements play a crucial role in conserving energy. The aim is to achieve an optimal design by balancing various interrelated factors. The emergence of innovative techniques to address energy conservation have been witnessed in the built environment. This review examines existing research articles that explore different metaheuristic optimization techniques (MOTs) for energy conservation in buildings. The focus is on evaluating the simplicity and stochastic nature of these optimization techniques. The findings of the review present theoretical and mathematical models for each algorithm and assess their effectiveness in problem solving. A systematic analysis of selected algorithms using MOT is conducted, considering factors that influence wellbeing, occupant health, and indoor environmental quality. The study examines the variations among swarm intelligence MOTs based on complexity, advantages, and disadvantages. The algorithms’ performances are based on the concept of uncertainty in consistently providing optimal solutions. The paper highlights the application of each technique in achieving energy conservation in buildings.

Modeling CO2 Emission Forecasting in Energy Consumption of the Industrial Building Sector under Sustainability Policy in Thailand: Enhancing the LISREL-LGM Model

“…Vidal, Minguillón, and Otaegi [25] present a long-term analysis of energy consumption and thermal comfort in a Passivhaus apartment, emphasizing the challenge of overheating in milder climates and advocating for adaptive design strategies. In fact, metaheuristic optimization techniques for energy conservation in buildings are reviewed by Pillay and Saha [26] in highlighting the role of swarm intelligence in optimizing building energy performance. Pierozan, Scolaro, Watzko, and Ghisi [27] evaluate the technical and economic feasibility of nearly zero-energy buildings in Brazil, emphasizing the importance of energy efficiency measures and on-site renewable energy generation.…”