Designing a decision model to assess the reward and penalty scheme of electric distribution companies

Ghasemi, Mostafa; Dashti, Reza

doi:10.1016/j.energy.2018.01.021

Cited by 8 publications

(16 citation statements)

References 20 publications

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“…Applying a dead zone with the mean of the historical reliability data as the center of the zone was recommended in Jooshaki (2014), Mohammadnezhad-Shourkaei andFotuhi-Firuzabad (2011), Modarresi and Fotuhi-Firuzabad (2012), Alvehag and Awodele (2014), Fumagalli et al (2007). Given this strategy, the dead zone size is two times the standard division with the end goal that the 'mean ?…”

Section: Comparative Analysis and Discussionmentioning

confidence: 99%

“…Thus, a cap value as a rate of the company's yearly income ought to be considered by the regulator to legitimize the risk of giving high rewards or penalties for improperly high-quality or low-quality reliability levels (Fumagalli et al 2007). In UK and Ireland (Fumagalli et al 2007(Fumagalli et al , 2015, maximum reward and maximum penalty are capped and set at 3% and 4% of price control incomes. Netherlands set 5% of capping in the adjustment of revenues (Fumagalli et al 2007).…”

Section: Comparative Analysis and Discussionmentioning

confidence: 99%

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Cubic reward penalty structure for power distribution companies

Sumesh

Potdar

Krishna

2019

Int J Syst Assur Eng Manag

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An important significance of restructuring in power industry is the emergence of regulatory performance indices in the power distribution companies. Reward-penalty scheme is a direct control method that regulators use to assure the performance regulatory controls such as system reliability, service efficiency, and customer interruption cost. It is used as a financial tool designed to prevent the service reliability and efficiency deterioration of power distribution companies. Reward penalty scheme rewards the distribution company which provides good reliable power and penalizes those who act otherwise. In this paper, we propose a Cubic Reward-Penalty scheme, to improve the service reliability of power distribution companies. The novel feature of this scheme is the use of cubic reward/ penalty formulation which varies in a cubic fashion based on the behavior of the performance-based reliability. In this paper, two methods of implementing Cubic Reward-Penalty scheme are explained: CRPS with no dead band and no reward/penalty capping and CRPS with dead band and reward/penalty capping. These proposed approaches are mainly intended for the regulators who are concerned about the customers affected by the outage duration. The significance of this research, lies in encouraging power distribution companies, to maintain, or even improve, customer service and satisfaction, by developing the Performance Regulatory Reward-Penalty schemes. This paper also provides most of the requirements and design rationale of Cubic Reward-Penalty Structure, its theoretical foundation and its prototype implementation.

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Section: Comparative Analysis and Discussionmentioning

confidence: 99%

Section: Comparative Analysis and Discussionmentioning

confidence: 99%

Cubic reward penalty structure for power distribution companies

Sumesh

Potdar

Krishna

2019

Int J Syst Assur Eng Manag

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“…Then, a nonlinear programming (NLP) model is generated for the optimization of investment costs and imposed costs incurred by the distribution company. The objective function (OF) for the distribution company i is determined as follows 37 :…”

Section: Rps Decision-making Modelmentioning

confidence: 99%

“…The optimal values of the imposed costs and investment costs of the TPEDC are presented in Table 5. 37 These parameters are determined using the decision-making model. The optimal values of the investment costs and imposed costs are 37.683 and 21.595 M$, respectively.…”

Section: Implementation Of the Rps Decision-making Modelmentioning

confidence: 99%

A hierarchical approach to designing an electricity distribution reward‐penalty scheme for service quality improvement

Ghasemi

Dashti

Amirioun

2021

Int Trans Electr Energ Syst

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In each regulatory period, the parameters of the reward and penalty scheme (RPS) vary based on the investment made by electricity distribution companies (EDCs) and imposed costs. In this paper, a novel dynamic model for determining the RPS parameters for each EDC is presented. This new model has three stages: (i) determination of the RPS parameters for the first regulatory period, (ii) the RPS decision-making model, and (iii) determination of the RPS parameters for the subsequent regulatory period. The proposed model was implemented for Iranian EDCs. Results verified the effectiveness of the proposed model in enhancing distribution system reliability.

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“…Nevertheless, this approach does not necessarily guarantee an equal reliability level for similar customers, which are located in different areas but are subject to identical external conditions 16‐18 . Traditional reliability incentive regulations identically treat different customers located in different geographic areas and even in the territory of diverse DISCOs 19,20 .…”

Section: Introductionmentioning

confidence: 99%

Reliability incentive regulation based on reward‐penalty mechanism using distribution feeders clustering

Khonakdar-Tarsi

Fotuhi‐Firuzabad

Ehsan

et al. 2021

Int Trans Electr Energ Syst

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Summary This paper proposes an approach to enhance the reliability regulation based on the relative performance. In the proposed approach, the distribution system feeders are clustered based on the parameters, which cannot be controlled by distribution companies. Afterward, a reliability incentive regulation is applied to each cluster so that the performance of each feeder is compared to its counterparts in the same cluster. The quality regulation is designed based on the reward‐penalty mechanism, which penalizes feeders whose performance is worse than a benchmark and rewards those providing a performance higher than the benchmark. Then, the reward and penalty associated to the electric distribution company are determined to summarize the rewards and penalties for all feeders. Having this approach implemented, utilities compete to make more profits by serving customers at higher reliability levels. To assess the effectiveness of proposed method, it is applied to a real distribution network containing 194 feeders.

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Designing a decision model to assess the reward and penalty scheme of electric distribution companies

Cited by 8 publications

References 20 publications

Cubic reward penalty structure for power distribution companies

Cubic reward penalty structure for power distribution companies

A hierarchical approach to designing an electricity distribution reward‐penalty scheme for service quality improvement

Reliability incentive regulation based on reward‐penalty mechanism using distribution feeders clustering

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