Limiting gaming opportunities on incentive-based demand response programs

Abstract

Demand Response (DR) is a program designed to match supply and demand by modifying consumption profile. Some of these programs are based on economic incentives, in which, a user is paid to reduce his energy requirements according to an estimated baseline. Literature review and practice have shown that the counter-factual models of employing baselines are vulnerable for gaming. Classical solutions of mechanism design require that agents communicate their full types which result in greater difficulties for its practical implementation. In this paper, a novel contract is developed to induce individual rationality (voluntary participation) and asymptotic incentive-compatibility (truthfulness) through probability of call, where an agent does not require to report the marginal utility. In this approach, a consumer only announces the baseline and reduction capacity, given a payment scheme that includes cost of electricity, incentive price, and penalty caused by any deviation between self-reported and actual energy consumption. The aggregator decides randomly what users are called to perform the energy reduction. As result, asymptotic truth-telling behavior in incentive-based DR is managed by the aggregator through the probability of call for each agent. Mathematical proofs and numerical studies are provided to demonstrate the properties and advantages of this contract in limiting gaming opportunities and in terms of its implementation.

Uncertainy’s Indices Assessment for Calibrated Energy Models

“…To carry out this research, the model has been calibrated, using the ZEC methodology, in 16 different calibrated periods choosing the 20 best models, with the lower energy of each period, generating a total of 320 models. The models have been identified by Pk_Mj, where Pk is the calibration period (from [1][2][3][4][5][6][7][8][9][10][11][12][13][14][15][16] and Mj is the model with respect to its position in the energy ranking (from 1-20). These models are evaluated in a common checking period, obtaining the results of their indices of uncertainty and the energy consumed.…”

“…SABINA is a project that is looking for services on the grid based on the "demand response" concept [12] and the idea of increasing the amount of renewable energy consumed locally by buildings. To reach the EU's long-term objectives for reducing greenhouse gas emissions, this share should reach more than 30% in 2030, and almost 50% in some scenarios in 2050 [13]; new management systems are thus required.…”

Bargaining‐based cooperative game among multi‐aggregators with overlapping consumers in incentive‐based demand response

“…In the above researches, all enrolled consumers can participate in IBDR programs, which may increase uncertainty because of a substantial amount of consumers. The work in [20] proposed a limiting gaming opportunity model for IBDR where the chance of a consumer to be selected by the aggregator to serve as demand response resource at a given period. Authors in [21] investigated how to efficiently select customers for certain types of incentive-based DR programs with various objectives based on hourly energy consumption data.…”

Stochastic programming model for incentive‐based demand response considering complex uncertainties of consumers

“…The above research studies provided reasonable methods to model the uncertainty of responsiveness, but they did not take account of the uncertainty of participation. The work in [26] proposed a limiting gaming opportunity model for IBDR where the chance of a consumer to be selected by the aggregator to serve as DR resource at a given period. The authors in [27] investigated how to efficiently select customers for certain types of IBDR programmes with various objectives based on hourly energy consumption data.…”