Peak demand contract for big consumers computed based on the combination of a statistical model and a mixed integer linear programming stochastic optimization model

•Peak demand simulation with a statistical model.•Optimization model to compute peak demand contract under uncertainty.•The method considers the Expected Value and the Conditional-Value-at-Risk.•Analysis performed for a real commercial consumer. One of the main objectives of Demand Response Programs...

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Vydané v:Electric power systems research Ročník 154; s. 122 - 129
Hlavní autori: Lima, Delberis A., Céspedes G., Andrés Maurício, Telles, Érica, Matias Bittencourt, Eidy Marianne
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Amsterdam Elsevier B.V 01.01.2018
Elsevier Science Ltd
Predmet:
Big consumer
Computer simulation
Consumers
Demand
Demand Response Program
Electric power demand
Electric power distribution
Electricity
Electricity consumption
Energy management
Integer programming
Linear programming
Mixed integer
Optimization
Optimization models
Parameter estimation
Peak demand contracted
Peak load
Statistical model
Statistical models
Stochastic models
Stochastic optimization model
Brazil
Big consumer
Statistical model
Stochastic optimization model
Peak demand contracted
Demand Response Program
ISSN:0378-7796, 1873-2046
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Popis
Shrnutí:•Peak demand simulation with a statistical model.•Optimization model to compute peak demand contract under uncertainty.•The method considers the Expected Value and the Conditional-Value-at-Risk.•Analysis performed for a real commercial consumer. One of the main objectives of Demand Response Programs is to mitigate the effect of peak electricity demand by inducing consumers to shift or reduce their electricity consumption in peak times. In Brazil, big energy consumers should contract peak demand for the upcoming months with the utility distribution companies under a set of rules defined by the System Regulator. Based on this, the utility will have more information to reinforce the system accordingly. The challenge for consumers is to compute the best value of the peak demand contracted before the peak demand realization. One way to solve this problem is to simulate future scenarios of peak demand and optimize the value of the peak demand contracted in compliance with the current rules. In this paper, a support decision system is proposed to help consumers in this task. The proposal is divided into two parts, which are a statistical model, for estimating and simulating future scenarios of peak demand, and a stochastic optimization model, to compute the value of the peak demand contracted. In the first part, a Box & Jenkins model is used to estimate the parameters of the statistical model and to simulate it based on the historical electricity bill data. In the second part, a stochastic optimization model is applied using a convex combination of the Expected Value and Conditional Value-at-Risk, as the risk metrics for the cost uncertainty, in order to obtain the monthly values of peak demand contracted. The results achieved corroborate the importance of using an appropriate mathematical model to address the problem. To illustrate the proposed approach, a real case study for a big consumer in Brazil is presented.
Bibliografia:ObjectType-Article-1
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ISSN:0378-7796
1873-2046
DOI:10.1016/j.epsr.2017.08.017