Applications of differential evolution in electric power systems. (English) Zbl 1512.90054
Vinoth Kumar, B. (ed.) et al., Differential evolution: from theory to practice. Singapore: Springer. Stud. Comput. Intell. 1009, 265-296 (2022).
Summary: The state-of-the-art power systems have extremely intricate, outsized and broad range distribution. The most favorable process of power system has become essential, in the face of escalating cost of power generation, limited sources of power generation and growing demand for electricity. It is essential to trim down the cost of fuel, active transmission power loss, deviation in voltage stability index of voltage and cost of reactive power sources, to gain appreciable value of savings. In addition, generator scheduling and load curtailment have participated in a critical position to reduce the sternness of the electric networks against the violation of system constraints. Hence, competent optimization algorithms are needed to make sure the optimal operation. Evolutionary-based optimization techniques have proved to be superior to traditional and artificial intelligence-based approaches, which are rooted in deprived convergence and complexity of computation, to handle numerous constraints in multi-objective functions. Differential evolution (DE) is the most familiar member in the group of evolutionary algorithms, owing to its simple construction, fast operation, least number of parameters, easier to implement and significantly robust. Numerous engineering optimization problems have been studied and proved by DE, as a leading contender to solve in hypothetical and real situations. The applications of DE and its versions or variants related to power system problems like reactive power planning, congestion management, available transfer capability, load dispatch in economical way, commitment of generating units, optimization of power flow and optimal reactive dispatch of electric power were discussed in this chapter.
For the entire collection see [Zbl 1480.90003].
For the entire collection see [Zbl 1480.90003].
MSC:
| 90B10 | Deterministic network models in operations research |
| 90C59 | Approximation methods and heuristics in mathematical programming |
Keywords:
power dispatch; voltage stability; unit commitment; reactive power; power loss; optimizationReferences:
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