Enhancing Aggregator profitability in the Electricity Market using modern metaheuristic optimization techniques

Sumit Banker

Makale detayları

Enhancing Aggregator profitability in the Electricity Market using modern metaheuristic optimization techniques

Yazarlar:

Sumit Banker

Yayıncı:

Murat YAKAR

Ana Başlıklar:

Electrical Energy Generation (Incl. Renewables | Excl. Photovoltaics)

Dergi:

Turkish Journal of Engineering Vol.9 Issue 4, pp.661-669

Belge Tipi:

Makale

Yayın Tarihi:

8/2025

Belge Dili:

İngilizce

Document ID (Org No.):

2001360055

pISSN:

2587-1366

Anahtar kelimeler:

Özet:

 Exponentially increasing use of the DERs Distributed Energy Resources has also increased the complexity and problems associated to the power system. This research paper is a step towards the profit maximization of the aggregator, which is a representative entity on behalf of the consumers and prosumers. To enhance the profit of aggregators, the operating cost of the Electricity Market needs to be minimized. In this research paper metaheuristic optimization techniques, RCEDUMDA Ring-Cellular Encode-Decode Univariate Marginal Distribution Algorithm and CSO Cuckoo Search Optimization are implemented to solve the aggregator profit maximization problem. The system adopted for the problem is the IEEE 30-bus test system with the inclusion of the DERs and considering the optimal dispatch of generation within the system constraints limits. The framework opted for this paper incorporates the cost-based objective function, including the income from the electricity sales and generator operational cost. Both the metaheuristic optimization techniques are tested on the mentioned framework on the bases of convergence characteristics, computational efficiency, and solution quality. Simulation results reflect that the RCEDUMDA significantly outperforms CSO by 12 higher aggregator profit with 35.5 less convergence time and better stability. The results point out the potential of RCEDUMDA metaheuristic optimization technique in enhancing the aggregator decision making and profit in Electricity Market.

 Exponentially increasing use of the DERs Distributed Energy Resources has also increased the complexity and problems associated to the power system. This research paper is a step towards the profit maximization of the aggregator, which is a representative entity on behalf of the consumers and prosumers. To enhance the profit of aggregators, the operating cost of the Electricity Market needs to be minimized. In this research paper metaheuristic optimization techniques, RCEDUMDA Ring-Cellular Encode-Decode Univariate Marginal Distribution Algorithm and CSO Cuckoo Search Optimization are implemented to solve the aggregator profit maximization problem. The system adopted for the problem is the IEEE 30-bus test system with the inclusion of the DERs and considering the optimal dispatch of generation within the system constraints limits. The framework opted for this paper incorporates the cost-based objective function, including the income from the electricity sales and generator operational cost. Both the metaheuristic optimization techniques are tested on the mentioned framework on the bases of convergence characteristics, computational efficiency, and solution quality. Simulation results reflect that the RCEDUMDA significantly outperforms CSO by 12 higher aggregator profit with 35.5 less convergence time and better stability. The results point out the potential of RCEDUMDA metaheuristic optimization technique in enhancing the aggregator decision making and profit in Electricity Market.

 Exponentially increasing use of the DERs Distributed Energy Resources has also increased the complexity and problems associated to the power system. This research paper is a step towards the profit maximization of the aggregator, which is a representative entity on behalf of the consumers and prosumers. To enhance the profit of aggregators, the operating cost of the Electricity Market needs to be minimized. In this research paper metaheuristic optimization techniques, RCEDUMDA Ring-Cellular Encode-Decode Univariate Marginal Distribution Algorithm and CSO Cuckoo Search Optimization are implemented to solve the aggregator profit maximization problem. The system adopted for the problem is the IEEE 30-bus test system with the inclusion of the DERs and considering the optimal dispatch of generation within the system constraints limits. The framework opted for this paper incorporates the cost-based objective function, including the income from the electricity sales and generator operational cost. Both the metaheuristic optimization techniques are tested on the mentioned framework on the bases of convergence characteristics, computational efficiency, and solution quality. Simulation results reflect that the RCEDUMDA significantly outperforms CSO by 12 higher aggregator profit with 35.5 less convergence time and better stability. The results point out the potential of RCEDUMDA metaheuristic optimization technique in enhancing the aggregator decision making and profit in Electricity Market.

 Exponentially increasing use of the DERs Distributed Energy Resources has also increased the complexity and problems associated to the power system. This research paper is a step towards the profit maximization of the aggregator, which is a representative entity on behalf of the consumers and prosumers. To enhance the profit of aggregators, the operating cost of the Electricity Market needs to be minimized. In this research paper metaheuristic optimization techniques, RCEDUMDA Ring-Cellular Encode-Decode Univariate Marginal Distribution Algorithm and CSO Cuckoo Search Optimization are implemented to solve the aggregator profit maximization problem. The system adopted for the problem is the IEEE 30-bus test system with the inclusion of the DERs and considering the optimal dispatch of generation within the system constraints limits. The framework opted for this paper incorporates the cost-based objective function, including the income from the electricity sales and generator operational cost. Both the metaheuristic optimization techniques are tested on the mentioned framework on the bases of convergence characteristics, computational efficiency, and solution quality. Simulation results reflect that the RCEDUMDA significantly outperforms CSO by 12 higher aggregator profit with 35.5 less convergence time and better stability. The results point out the potential of RCEDUMDA metaheuristic optimization technique in enhancing the aggregator decision making and profit in Electricity Market.

Makale detayları

Enhancing Aggregator profitability in the Electricity Market using modern metaheuristic optimization techniques

Yazarlar:

Sumit Banker

Yayıncı:

Murat YAKAR

Ana Başlıklar:

Electrical Energy Generation (Incl. Renewables | Excl. Photovoltaics)

Dergi:

Turkish Journal of Engineering Vol.9 Issue 4, pp.661-669

Belge Tipi:

Makale

Yayın Tarihi:

8/2025

Belge Dili:

İngilizce

Document ID (Org No.):

2001360055

pISSN:

2587-1366

Electricity market

Metaheuristic optimization

Aggregator

DERs

RCEDUMDA

CSO

Sayı

Makale detayları

Enhancing Aggregator profitability in the Electricity Market using modern metaheuristic optimization techniques

Yazarlar: Sumit Banker

Yayıncı: Murat YAKAR

Ana Başlıklar: Electrical Energy Generation (Incl. Renewables | Excl. Photovoltaics)

Dergi: Turkish Journal of Engineering Vol.9 Issue 4, pp.661-669

Belge Tipi: Makale

Yayın Tarihi: 8/2025

Belge Dili: İngilizce

Document ID (Org No.): 2001360055

pISSN: 2587-1366

Electricity market

Metaheuristic optimization

Aggregator

DERs

RCEDUMDA

CSO

Sayı

Yazarlar:

Sumit Banker

Yayıncı:

Murat YAKAR

Ana Başlıklar:

Electrical Energy Generation (Incl. Renewables | Excl. Photovoltaics)

Dergi:

Turkish Journal of Engineering Vol.9 Issue 4, pp.661-669

Belge Tipi:

Makale

Yayın Tarihi:

8/2025

Belge Dili:

İngilizce

Document ID (Org No.):

2001360055

pISSN:

2587-1366