A Cooperative Game Theory Approach for Usage and Reliability Margin Cost Allocation under Contingent Restructured Market

Khan, Baseem; Agnihotri, Ganga; Rathore, Pawan; Mishra, Anuprita; Naidu, Garima

doi:10.15866/iree.v9i4.1977

Cited by 2 publications

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“…Amongst several factors which impact consumption, there are two high level components which are highly significant [39][40][41][42][43][44][45]:…”

Section: Factorsmentioning

confidence: 99%

Short Term Load Forecasting of Distribution Feeder Using Artificial Neural Network Technique

Chane¹,

Gebru²,

Khan³

2021

J. Infor. Electr. Electron. Eng.

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This paper explains the load forecasting technique for prediction of electrical load at Hawassa city. In a deregulated market it is much need for a generating company to know about the market load demand for generating near to accurate power. If the generation is not sufficient to fulfill the demand, there would be problem of irregular supply and in case of excess generation the generating company will have to bear the loss. Neural network techniques have been recently suggested for short-term load forecasting by a large number of researchers. Several models were developed and tested on the real load data of a Finnish electric utility at Hawassa city. The authors carried out short-term load forecasting for Hawassa city using ANN (Artificial Neural Network) technique ANN was implemented on MATLAB and ETAP. Hourly load means the hourly power consumption in Hawassa city. Error was calculated as MAPE (Mean Absolute Percentage Error) and with error of about 1.5296% this paper was successfully carried out. This paper can be implemented by any intensive power consuming town for predicting the future load and would prove to be very useful tool while sanctioning the load.

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“…Amongst several factors which impact consumption, there are two high level components which are highly significant [39][40][41][42][43][44][45]:…”

Section: Factorsmentioning

confidence: 99%

Short Term Load Forecasting of Distribution Feeder Using Artificial Neural Network Technique

Chane¹,

Gebru²,

Khan³

2021

J. Infor. Electr. Electron. Eng.

Self Cite

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“…In this regard, the solution approaches of cooperative game theory behave well in terms of economic efficiency, fairness, and stability [16]. In [17], Shapley and Nucleolus approaches are utilized for transmission usage cost allocation. To accommodate all the loads in the pool market, Shapley value allocated the transmission usage cost to demands.…”

Section: Optimal Transmission Usage Cost Allocationmentioning

confidence: 99%

Game Theory Application in Smart Energy Logistics and Economy

Khan¹

2018

Game Theory - Applications in Logistics and Economy

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In many parts of the world, energy sectors are transformed from conventional to the smart deregulated market structures. In such smart deregulated market environment, cooperative game theory can play a vital role for analyzing various smart deregulated market problems. As an optimization tool, cooperative game theory is very useful in smart energy logistics and economy analysis problem. The economy associated with smart deregulated structure can be better optimized and allocated with the help of cooperative game theory. Initially, due to regulated structure, there is no cooperation between different entities of energy sector. But after new market structure, all the entities are free to take their own decisions as an independent entity. Transmission open access of energy logistics is also comes into the picture, as all the generators and demands have the same right to access the transmission system. In this market situation, multiple utilities are using the same energy logistic network. This situation can be formulated as a cooperative game in which generators and demands are represented by players. This chapter deals with energy logistic cost allocation problems for a smart deregulated energy market. It is cooperative in nature as all the agents are using the same energy logistic network.

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A Cooperative Game Theory Approach for Usage and Reliability Margin Cost Allocation under Contingent Restructured Market

Cited by 2 publications

References 0 publications

Short Term Load Forecasting of Distribution Feeder Using Artificial Neural Network Technique

Short Term Load Forecasting of Distribution Feeder Using Artificial Neural Network Technique

Game Theory Application in Smart Energy Logistics and Economy

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