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:: Volume 7, Issue 13 (9-2018) ::
ieijqp 2018, 7(13): 84-92 Back to browse issues page
Market clearing price prediction using improved neural network with genetic algorithm in Iranian day ahead market for competitiveness clustering’s
Bakhtiar Ostadi Mr , Omid Motamedi Mr, Ali Husseinzadeh Kashan Mr, Mohamad Reza Amin Naseri Mr
Tarbiat Modares University
Abstract:   (200 Views)
In The deregulation in power market is lead to competition among market participant to increase efficiency. In electricity market generation is the best candidate for iterance in competition to improve productivity and efficiency in resource allocation and offer lowest price by highest quality will be yielded. In the pool-based electricity market, every Genco submits a bidding price in ten step offer to the Independent System Operator (ISO) for every hour of the next day. The ISO uses the bidding price and forecasting demand to determine the MCP. The resulting spot price series exhibit strong seasonality at the annual, weekly and daily levels, as well as mean reversion, very high volatility and abrupt, short-lived and generally unanticipated extreme price changes known as spikes or jumps. So in this article we cluster time horizon in three cluster then we applied improved neural network by genetic algorithm for all clusters. In compare of normal neural network, results of our model are more better by 95% Accuracy.
Keywords: neural network, genetic algorithm, competitive times Clustering, market clearing price prediction.
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Type of Study: Research |
Received: 2018/01/17 | Accepted: 2018/05/12 | Published: 2018/08/25


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ostadi B, motamedi O, Husseinzadeh Kashan A, Amin Naseri M R. Market clearing price prediction using improved neural network with genetic algorithm in Iranian day ahead market for competitiveness clustering’s. ieijqp. 2018; 7 (13) :84-92
URL: http://ieijqp.ir/article-1-498-en.html


Volume 7, Issue 13 (9-2018) Back to browse issues page
نشریه علمی- پژوهشی کیفیت و بهره وری صنعت برق ایران Iranian Electric Industry Journal of Quality and Productivity
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