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A modified bacteria foraging based optimal power flow framework for Hydro-Thermal-Wind generation system in the presence of STATCOM

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  • Panda, Ambarish
  • Tripathy, M.
  • Barisal, A.K.
  • Prakash, T.

Abstract

Considering the importance of clean energy, the combined operation of hydro-thermal-wind (HTW) system is formulated in optimal power flow (OPF) framework. The objective is to find an optimal generation schedule for the HTW system where the system will work economically and in a voltage secure manner with reduced loss during normal as well as stressed system operation. As system voltage may be vulnerable especially during under estimation (UE) situation, provision of additional reactive power (Q) support is essential as a possible solution. This is achieved by installing shunt facts devices i.e. (STATCOM) at the weak nodes of the power network. A comparative assessment between wind-thermal (WT) and HTW system operation with STATCOM at different wind penetration levels is also depicted. The optimum operational paradigms are obtained by optimizing the objective with Genetic Algorithm (GA), Hybrid Algorithm (HA) and modified bacteria foraging algorithm (MBFA). After several tests, superiority of MBFA optimization over HA and GA is revealed so that the IEEE30-bus system operates in a voltage secure and cost-effective manner.

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  • Panda, Ambarish & Tripathy, M. & Barisal, A.K. & Prakash, T., 2017. "A modified bacteria foraging based optimal power flow framework for Hydro-Thermal-Wind generation system in the presence of STATCOM," Energy, Elsevier, vol. 124(C), pages 720-740.
    • Handle: RePEc:eee:energy:v:124:y:2017:i:c:p:720-740
    DOI: 10.1016/j.energy.2017.02.090
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    7. Li, Shuijia & Gong, Wenyin & Hu, Chengyu & Yan, Xuesong & Wang, Ling & Gu, Qiong, 2021. "Adaptive constraint differential evolution for optimal power flow," Energy, Elsevier, vol. 235(C).
    8. Elattar, Ehab E. & ElSayed, Salah K., 2019. "Modified JAYA algorithm for optimal power flow incorporating renewable energy sources considering the cost, emission, power loss and voltage profile improvement," Energy, Elsevier, vol. 178(C), pages 598-609.
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    11. Papadimitrakis, M. & Giamarelos, N. & Stogiannos, M. & Zois, E.N. & Livanos, N.A.-I. & Alexandridis, A., 2021. "Metaheuristic search in smart grid: A review with emphasis on planning, scheduling and power flow optimization applications," Renewable and Sustainable Energy Reviews, Elsevier, vol. 145(C).
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