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Optimal Sizing and Sitting of Smart Microgrid Units under Pool Electricity Market
This paper presents an approach for optimal sizing and sitting of distribution generation units in smart microgrid under pool electricity market to reduce total cost and power loss of whole smart microgrid. The costs comprise capital cost, replacement cost, operation and maintenance cost, fuel cost, reliability cost, power loss cost and selling and buying electricity cost. The new idea of this paper is the investigation of pool electricity market aspects in optimization of smart microgrid. On the other hand, cost minimization of smart microgrid is related to their bidding strategies. Therefore two different optimization tools are considered. First, a game-theoretical (GT) model has been used for bidding strategy of smart microgrid as a price-maker, in a long-term electricity market. Secondly, a particle swarm optimization (PSO) algorithm is employed to obtain the best cost value of smart microgrids construction. This study was performed for the Ekbatan residential complex in Tehran, Iran. It has three smart microgrids consist of renewable energy resources. They participate in a long-term electricity market as a price maker. The results show that the proposed method is more effective and has lower cost in finding optimum size and location of distribution generation in smart microgrids.
Optimal Sizing and Sitting of Smart Microgrid Units under Pool Electricity Market
This paper presents an approach for optimal sizing and sitting of distribution generation units in smart microgrid under pool electricity market to reduce total cost and power loss of whole smart microgrid. The costs comprise capital cost, replacement cost, operation and maintenance cost, fuel cost, reliability cost, power loss cost and selling and buying electricity cost. The new idea of this paper is the investigation of pool electricity market aspects in optimization of smart microgrid. On the other hand, cost minimization of smart microgrid is related to their bidding strategies. Therefore two different optimization tools are considered. First, a game-theoretical (GT) model has been used for bidding strategy of smart microgrid as a price-maker, in a long-term electricity market. Secondly, a particle swarm optimization (PSO) algorithm is employed to obtain the best cost value of smart microgrids construction. This study was performed for the Ekbatan residential complex in Tehran, Iran. It has three smart microgrids consist of renewable energy resources. They participate in a long-term electricity market as a price maker. The results show that the proposed method is more effective and has lower cost in finding optimum size and location of distribution generation in smart microgrids.
Optimal Sizing and Sitting of Smart Microgrid Units under Pool Electricity Market
Hakimi, Seyed Mehdi (author) / Hajizadeh, Amin (author)
2017-09-01
Hakimi , S M & Hajizadeh , A 2017 , ' Optimal Sizing and Sitting of Smart Microgrid Units under Pool Electricity Market ' , Industrial Engineering and Management Systems , vol. 16 , no. 3 , pp. 427-436 . < http://www.iemsjl.org/journal/article.php?code=54797 >
Article (Journal)
Electronic Resource
English
DDC:
690
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