Multi-region dynamic economic dispatch of solar–wind–hydro–thermal power system incorporating pumped hydro energy storage. (November 2019)

• Record Type: Journal Article
• Authors: Basu, M.
• Is Part Of: Engineering applications of artificial intelligence. Volume 86(2019)
• Page Start: 182
• Page End: 196
• Publication Date: 2019-11
• Subjects: Cascaded reservoirs -- Wind power uncertainty -- Solar power uncertainty -- Pumped hydro energy storage -- Ramp-rate limits -- Proscribed workable area; Engineering -- Data processing -- Periodicals; Artificial intelligence -- Periodicals; Expert systems (Computer science) -- Periodicals; Ingénierie -- Informatique -- Périodiques; Intelligence artificielle -- Périodiques; Systèmes experts (Informatique) -- Périodiques; Artificial intelligence; Engineering -- Data processing; Expert systems (Computer science); Periodicals; 620.00285
• DOI: 10.1016/j.engappai.2019.09.001
• Languages: English
• ISSNs: 0952-1976

Abstract

Abstract: This paper suggests chaotic fast convergence evolutionary programming (CFCEP) for solving multi-region dynamic economic dispatch (MRDED) problem, multi-region economic dispatch (MRED) problem and economic dispatch (ED) problem. MRDED problem is based on multi-reservoir cascaded hydro plant with time delay, thermal plants with nonsmooth fuel cost function, wind and solar power units with uncertainty and pumped hydro energy storage. MRED problem deals with tie line constraints, transmission losses, valve point effect and proscribed workable area of thermal generators. ED problem deals with valve point effect, proscribed workable area and ramp rate limits of thermal generators. In the recommended technique, chaotic sequences have been pertained for acquiring the dynamic scaling factor setting in fast convergence evolutionary programming (FCEP). The efficacy of the proposed technique has been verified on convoluted three-area system for MRDED problem, four-area system for MRED problem and 140-unit Korean system for ED problem. Test results acquired from the suggested CFCEP technique have been fit to that acquired from FCEP, differential evolution (DE) and particle swarm optimization (PSO). It has been observed from the comparison that the recommended CFCEP technique has the capability to bestow with better-quality solution. Highlights: This work recommends CFCEP for solving MRDED, MRED and ED problem. The solar–wind–hydro–thermal power system is taken into consideration. Wind and solar power uncertainty and pumped hydro energy storage are considered. Simulation outcomes of the test system are matched up by FCEP, DE and PSO.