A modified bacteria foraging based optimal power flow framework for Hydro-Thermal-Wind generation system in the presence of STATCOM
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...
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Veröffentlicht in: | Energy (Oxford) 2017-04, Vol.124, p.720-740 |
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Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | 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.
•Modelling and optimal scheduling of HT system in the presence of wind power.•Incorporation of STATCOM in the system for enhancement of voltage security.•System operation during normal, stressed and different wind penetration scenario.•Comparative analysis of MBFA, HA and GA optimized schedule.•Validation of the approach in IEEE30-bus power network in a MO-OPF framework. |
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ISSN: | 0360-5442 1873-6785 |
DOI: | 10.1016/j.energy.2017.02.090 |