Abstract
ED (Economic Dispatch) problem is one of the vital step in operational planning. It is a nonconvex constrained optimization problem. However, it is solved as convex problem by approximation of machine input/output characteristics, thus resulting in an inaccurate result. Reliable, secure and cheapest supply of electrical energy to the consumers is the prime objective in power system operational planning. Increase in fuel cost, reduction in fossil-fuel assets and ecological concerns have forced to integrate renewable energy resources in the generation mix. However, the instability of wind and solar power output affects the power network. For solution of such solar and wind integrated economic dispatch problems, evolutionary approaches are considered potential solution methodologies. These approaches are considered as potential solution methodologies for nonconvex ED problem. This paper presents CEED (Combined Emission Economic Dispatch) of a power system comprising of multiple solar, wind and thermal units using continuous and binary FPA (Flower Pollination Algorithm). Proposed algorithm is applied on 5, 6, 15, 26 and 40 thermal generators by integrating several solar and wind plants, for both convex and non-convex ED problems. Proposed algorithm is simulated in MATLAB 2014b. Results of simulations, when compared with other approaches, show promise of the approach.
Highlights
Ein this world played a significant role for enhancement and growth of sustainable, reliable and clean energy systems for satisfying the necessities of large number of people and to minimize the usage of fossil fuels
Total cost of each hour reported in [2], where only solar plants were integrated to thermal generators, is compared with the total cost of each hour found using proposed FPA
This comparison proves that the integration of wind plant to the system considerably reduces the operational cost to its minimum. existing algorithms
Summary
Ein this world played a significant role for enhancement and growth of sustainable, reliable and clean energy systems for satisfying the necessities of large number of people and to minimize the usage of fossil fuels. Key goal of ED problem is to allocate power to the generators, to minimize operational fuel and emission cost, subject to all related operational constraints. It is a nonconvex constrained optimization problem. It has been addressed comprehensively in MP (Mathematical Programming) environment by converting it into convex problem. This is due to inability of the MP approaches to tackle nonconvex problems, except dynamic. In the start of 1930s, EICC (Equal Incremental Cost Criterion) was applied to obtain the best possible solutions. An overview of various methods, which were applied for the period of 1977-1988, for the solution of ED is presented in [2]
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