Optimization Strategies in Energy Management Systems
Summary
Energy management systems encompass hardware, software and control layers that govern the generation, storage, distribution and consumption of electrical power. Optimisation strategies within these systems seek to balance conflicting objectives such as cost minimisation, emission reduction and reliability enhancement. Classical approaches rely on mathematical programming techniques, including linear, mixed‐integer and non‐linear formulations, to determine optimal dispatch schedules for generation units, storage devices and flexible loads. In recent years, metaheuristic algorithms—such as genetic, swarm-intelligence and bio-inspired methods—have been widely adopted to tackle large-scale, non-convex problems with multiple objectives. Parallel advances in machine learning have enabled predictive control frameworks that adaptively forecast demand and renewable output, while blockchain and digital-twin technologies are enhancing transparency and resilience in data exchange. Applications span microgrids, building energy management, combined cooling, heating and power systems, and freight transport, reflecting a global drive towards decarbonisation and smart-grid integration. The practical significance of these strategies is demonstrated by reductions in operational costs, peak-load shaving, improved renewable integration and enhanced grid stability under variable conditions.
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Optimization Strategies in Energy Management Systems publication trend
The graph below shows the total number of articles in optimization strategies in energy management systems across all publications each year (not limited to Nature Index journals).
Technical terms
Metaheuristic algorithm: A high-level problem-solving framework that exploits stochastic or rule-based search methods to find near-optimal solutions in complex, non-convex optimisation tasks.
Microgrid: A localized grouping of electricity sources and loads that can operate autonomously or connected to the main grid, enhancing resilience and integrating distributed renewables.
Combined Cooling, Heating and Power (CCHP): A cogeneration system that simultaneously delivers electrical power and thermal energy outputs for cooling and heating, improving overall energy utilisation.
Blockchain: A decentralised ledger technology that ensures secure, tamper-proof recording of transactions, facilitating trust and data integrity among multiple parties in energy networks.
References
- Efficient design of energy microgrid management system: A promoted Remora optimization algorithm-based approach. Heliyon (2023).
- Evaluating the efficiency of CCHP systems in Xinjiang Uygur Autonomous Region: An optimal strategy based on improved mother optimization algorithm. Case Studies in Thermal Engineering (2024).
- Blockchain-Based Securing of Data Exchange in a Power Transmission System Considering Congestion Management and Social Welfare. Sustainability (2020).
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