2018Unpublished venueRequires access

A contract for demand response based on probability of call

José Vuelvas, Fredy Ruíz, Giambattista Gruosso

Open publisher page 2 citations

Abstract

A useful tool for reducing energy consumption at peak times is through an incentive-based demand response program. Each participant user is paid for diminishing his energy requirement according to a baseline. However, this demand response program presents truthfulness and gaming concerns since consumers can alter their reported information in order to increase their well-being. Therefore, a novel contract is proposed to induce asymptotic incentive-compatibility (truthfulness) and individual rationality (voluntary participation) through the probability of call. In this approach, each consumer announces his baseline and reduction capacity; given the cost of electricity, incentive price and a penalty caused by any deviation between self-reported and actual energy consumption. A payment scheme is implemented for all participant consumers where an aggregator decides what users are called to perform the energy reduction. A two-stage stochastic optimization problem is formulated in order to understand the rational behavior of consumers that participate under this contract. As result, asymptotic truth-telling behavior in incentive-based DR is managed by the aggregator through the probability of call for each agent. Numerical optimization results show that the aggregator can limit gaming opportunities irrespective of consumer's private preferences by controlling user's participation.

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What this paper is about

A useful tool for reducing energy consumption at peak times is through an incentive-based demand response program. Each participant user is paid for diminishing his energy requirement according to a baseline. However, this demand response program presents truthfulness and gaming concerns since consumers can alter their reported information in order to increase their well-being. Therefore, a novel contract is proposed to induce asymptotic incentive-compatibility (truthfulness) and individual rationality (voluntary participation) through the probability of call. In this approach, each consumer announces his baseline and reduction capacity; given the cost of electricity, incentive price and a penalty caused by any deviation between self-reported and actual energy consumption. A payment scheme is implemented for all participant consumers where an aggregator decides what users are called to perform the energy reduction. A two-stage stochastic optimization problem is formulated in order to understand the rational behavior of consumers that participate under this contract. As result, asymptotic truth-telling behavior in incentive-based DR is managed by the aggregator through the probability of call for each agent. Numerical optimization results show that the aggregator can limit gaming opportunities irrespective of consumer's private preferences by controlling user's participation.

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Available abstract

A useful tool for reducing energy consumption at peak times is through an incentive-based demand response program. Each participant user is paid for diminishing his energy requirement according to a baseline. However, this demand response program presents truthfulness and gaming concerns since consumers can alter their reported information in order to increase their well-being. Therefore, a novel contract is proposed to induce asymptotic incentive-compatibility (truthfulness) and individual rationality (voluntary participation) through the probability of call. In this approach, each consumer announces his baseline and reduction capacity; given the cost of electricity, incentive price and a penalty caused by any deviation between self-reported and actual energy consumption. A payment scheme is implemented for all participant consumers where an aggregator decides what users are called to perform the energy reduction. A two-stage stochastic optimization problem is formulated in order to understand the rational behavior of consumers that participate under this contract. As result, asymptotic truth-telling behavior in incentive-based DR is managed by the aggregator through the probability of call for each agent. Numerical optimization results show that the aggregator can limit gaming opportunities irrespective of consumer's private preferences by controlling user's participation.

Key concepts: News aggregator, Incentive, Demand response, Computer science, Energy consumption, Incentive compatibility, Baseline (sea), Order (exchange)

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