A Novel Demand Response Model with an Application for a Virtual Power Plant

Abstract

In modern power systems and electricity markets, demand response (DR) programs play an important role enabling the mitigation of critical load periods or price-peaking scenarios, thereby improving system reliability. Price fluctuations, in forward or real-time markets, can be an effective price-based DR mechanism for curtailing or shifting load. However, using dynamic pricing to achieve a desired load profile requires both an accurate demand forecast and knowledge of the price elasticity of demand, which is notoriously difficult to estimate. The limited accuracy of these parameter estimates is the main source of uncertainty limiting appropriate DR implementation. In this paper, we present a novel DR scheme that avoids the need to predict the price elasticity of demand or demand forecast, yet still delivers a significant DR. This is done based on the consumers' submissions of candidate load profiles ranked in the preference order. The load aggregator then performs the final selection of individual load profiles subject to the total system cost minimization. Additionally, the proposed DR model incorporates a fair billing mechanism that is enhanced with an ex post consumer performance tracking scheme implemented in a context of a virtual power plant aggregating load and generation units.Index Terms-Demand response (DR), demand side management, electricity market, smart grid, virtual power plant.

A Virtual Power Plant Architecture for the Demand-Side Management of Smart Prosumers

“…The specific application of DR schemes in the context of a VPP aggregating loads and RES generators in a distribution grid has been proposed in [30]. In this case, single customers are required to promote DR bids on candidate load profiles, and an independent operator is responsible for the final selection of individual profiles by pursuing the optimization of total system costs.…”

“…In this case, single customers are required to promote DR bids on candidate load profiles, and an independent operator is responsible for the final selection of individual profiles by pursuing the optimization of total system costs. Similarly to [30], in [31] a bidding strategy for the operation and management of a VPP is proposed, by considering DR strategies and RES uncertainty. In both of the proposed studies, operational plans and optimization strategies are computed at supervisory levels by considering the aggregated DERs only as dispersed generation or consumption units with limited decision capabilities.…”

Demand response for frequency control of multi-area power system

“…In addition, the system operators should sign contracts with the electric consumers for offering DR. These contracts will allow the system operator (or the aggregators) to manage the electricity consumption of the DR appliances through a technology named Virtual Power Plant (VPP) [2,17,18]. And the consumer will get some payment in return.…”

A review on the virtual power plant: Components and operation systems

“…The incomplete forecast of demand is the main uncertainty in a system equipped with DR programs. A new DR strategy is offered in [40] which is based on the consumers' submissions of candidate load profiles. Thus, forecasting the price elasticity of demand is not needed.…”