Optimization Techniques for Economic Dispatch in Power Systems

Economic dispatch in power systems addresses the allocation of generation among available units so as to minimise total operating cost while satisfying demand and operational constraints. Traditional methods have relied on analytical and gradient‐based techniques such as quadratic programming and Lagrange multipliers, but these approaches often struggle with non-convexities introduced by valve-point effects, prohibited operating zones and renewable integration. In response, a broad spectrum of optimisation techniques has emerged. Deterministic algorithms, including interior-point and Newton-Raphson variants, deliver rapid convergence under smooth conditions but may fail in the presence of discontinuities or multiple local minima. Metaheuristic algorithms—such as particle swarm optimisation, genetic algorithms, differential evolution and gravitational search—offer greater flexibility by balancing global exploration with local exploitation, making them well suited to complex, non-differentiable dispatch problems. Hybrid paradigms further combine metaheuristics with deterministic refinements to accelerate convergence and enhance solution quality. Recent work has extended these methods to multi-area dispatch, integrated emission constraints and stochastic renewable sources, thereby reinforcing the global significance of economic dispatch optimisation for cost reduction, emission control and system reliability.

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Optimization Techniques for Economic Dispatch in Power Systems publication trend

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Technical terms

Economic dispatch: The process of determining the optimal output of multiple generation units so that the total operating cost is minimised under power balance and system constraints.

Metaheuristic algorithm: A high-level problem-independent framework that guides subordinate heuristics to explore and exploit the search space, suitable for complex, non-convex optimisation problems.

Valve-point effects: Non-smooth ripples in generator fuel cost curves caused by steam admission valves, introducing multiple local minima into the dispatch problem.

Combined economic and emission dispatch (CEED): An extension of economic dispatch that simultaneously minimises fuel cost and pollutant emissions, typically modelled as a multi-objective optimisation.

Exploration and exploitation: Dual phases in optimisation where exploration seeks new regions of the search space and exploitation refines solutions within promising areas, critical for avoiding premature convergence.

References

1. A memory-based gravitational search algorithm for solving economic dispatch problem in micro-grid. Ain Shams Engineering Journal (2021).
2. Recent Methodology-Based Gradient-Based Optimizer for Economic Load Dispatch Problem. IEEE Access (2021).
3. Performance of Osprey Optimization Algorithm for Solving Economic Load Dispatch Problem. Mathematics (2023).