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Temperature dependent optimal power flow using g-best guided artificial bee colony algorithm
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DOI：10.1016/j.ijepes.2015.11.026.png)
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Resistance is an important element in power flow calculation. The accuracy of active power loss calculation depends upon resistance of that branch. Although resistance is a function of temperature rise for pure conductor, conventional power studies neglect temperature effect totally. To calculate exact losses in branch, it is necessary to consider temperature rise in calculation. In a deregulated electricity structure, optimal power flow has been an important tool to assess the economic operation of electricity market. So, the accuracy of optimal power flow is greatly influenced by temperature effect. This paper presents implementation of an efficient gbest-guided artificial bee colony algorithm to solve optimal power flow as well as temperature dependent optimal power flow. This method is tested on IEEE 30 bus system and IEEE 57 bus test system for statistical analysis of gbest-guided artificial bee colony algorithm. This paper also presents the temperature dependent optimal power flow on IEEE 30 bus test system. Effect of temperature rise is also analysed on IEEE 30 bus system, 2383 bus winter peak Polish system and 2736 bus summer peak Polish system. (C) 2015 Elsevier Ltd. All rights reserved.
Keyword:
Optimization
Optimal Power Flow (OPF)
gbest-Guided Artificial Bee Colony Algorithm (GABC)
Temperature Dependent Optimal Power Flow (TDOPF)
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1.1W
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3.1W
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