Demand Response (DR) programs serve to reduce the consumption of electricity at times when the supply is scarce and expensive. The utility informs the aggregator of an anticipated DR event. The aggregator calls on a subset of its pool of recruited agents to reduce their electricity use. Agents are paid for reducing their energy consumption from contractually established baselines. Baselines are counter-factual consumption estimates of the energy an agent would have consumed if they were not participating in the DR program. Baselines are used to determine payments to agents. This creates an incentive for agents to inflate their baselines. We propose a novel self-reported baseline mechanism (SRBM) where each agent reports its baseline and marginal utility. These reports are strategic and need not be truthful. Based on the reported information, the aggregator selects or calls on agents to meet the load reduction target. Called agents are paid for observed reductions from their self- reported baselines. Agents who are not called face penalties for consumption shortfalls below their baselines. The mechanism is specified by the probability with which agents are called, reward prices for called agents, and penalty prices for agents who are not called. Under SRBM, we show that truthful reporting of baseline consumption and marginal utility is a dominant strategy. Thus, SRBM eliminates the incentive for agents to inflate baselines. SRBM is assured to meet the load reduction target. SRBM is also nearly efficient since it selects agents with the smallest marginal utilities, and each called agent contributes maximally to the load reduction target. Finally, we show that SRBM is almost optimal in the metric of average cost of DR provision faced by the aggregator.
The price set in electricity markets is given by the intersection of supply and demand during a given time period. The demand-side has traditionally been a price taker while the supply-side actively adjusts the output of the market clearing unit to fluctuations in consumption. Currently, there is a transition toward active demand participation that can adequately respond to market conditions. However, private knowledge of demand adjustments, such as the impact of modifying behavior or the availability to do so, creates asymmetry of information between the active supply side and the passive demand. This paper proposes a revelation mechanism that will prompt the demand-side to choose the best option for themselves among a menu of incentives. Rational behavior of consumers implies that demand will only shift when the benefit of doing so is higher than the costs of modifying consumption patterns. Given differences among demand participants and the objectives of the market operator, an analysis of the rationale of each market agent shows the feasible options for demand incentives. This study enables the design of appropriate market mechanisms aimed to discover customer categories and determine the adequate incentives for each case. We design an optimal contract between a demand response aggregator (DRA) and power grid customers for incentive-based demand response. We consider a setting in which the customers are asked to reduce their electricity consumption by the DRA and they are compensated for this demand curtailment. However, given that the DRA must supply every customer with as much power as she desires, a strategic customer can temporarily increase her base load in order to report a larger reduction as part of the demand response event. The DRA wishes to incentivize the customers both to make costly effort to reduce load and to not falsify the reported load reduction. We model this problem as a contract design problem and present a solution. The proposed contract consists of two parts: a part that depends on (the possibly inflated) load reduction as measured by the DRA and another that provides a share of the profit that accrues to the DRA through the demand response event to the customers. Since this profit accrues due to the total load reduction because of the actions taken by all the customers, the interaction among the customers also needs to be carefully included in the contract design. The contract design and its properties are presented and illustrated through examples.  In this paper we investigate efficient schemes for scheduling demand response (DR) in a deregulated environment. We begin with an analysis of partial schemes which are being implemented in many established markets. These schemes can be considered inefficient due to externalities that occur amongst DR beneficiaries including the transmission network company (Transco), distribution network companies (Discos), and retail electricity companies (Recos). This limitation of existing schemes motivates the development of a new concept-demand response exchange (DRX)-a separated market for trading DR fairly and flexibly across all beneficiaries. The DRX concept is realized by introducing a pool-based market clearing scheme. Extensive simulations are provided to illustrate the effectiveness of our DRX proposal.  In restructured power systems, there are many independent players who benefit from demand response (DR). These include the transmission system operator (TSO), distributors, retailers, and aggregators. This paper proposes a new concept-demand response eXchange (DRX)-in which DR is treated as a public good to be exchanged between DR buyers and sellers. Buyers need DR to improve the reliability of their own electricity-dependent businesses and systems. Sellers have the capacity to significantly modify electricity demand on request. Microeconomic theory is applied to model the DRX in the form of a pool-based market. In this market, a DRX operator (DRXO) collects DR bids and offers from the buyers and sellers, respectively. It then clears the market by maximizing the total market benefit subject to certain constraints including: demand-supply balance, and assurance contracts related to individual buyer contributions for DR. The DRX model is also tested on a small power system, and its efficiency is reported.