Hybrid weighted probabilistic neural network and biogeography based optimization for dynamic economic dispatch of integrated multiple-fuel and wind power plants
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- 作者：Umamaheswari krishnasamya ; uvembu@gmail.com" class="auth_mail" title="E-mail the corresponding author ; Devarajan Nanjundappanb ; drdevarajan@gct.ac.in" class="auth_mail" title="E-mail the corresponding author
- 关键词：Dynamic economic dispatch ; Wind speed prediction ; Weighted probabilistic neural network (WPNN) ; Biogeography based optimization (BBO)
- 刊名：International Journal of Electrical Power & Energy Systems
- 出版年：2016
- 出版时间：May 2016
- 年：2016
- 卷：77
- 期：Complete
- 页码：385-394
- 全文大小：1920 K
文摘
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Integration of wind into thermal system and its impact on the DEDP are explored here.
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WPNN is proposed to forecast a one-hour ahead wind power for reliable power supply.
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BBO algorithm is integrated with SQP to obtain the better solution for DEDP.
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DEDP considering valve-point effects and multiple-fuel options has been solved.
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The proposed WPNN–BBO method is applied for a test bench DEDP and a practical DEDP.