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.
This paper presents a model for operational decision making of a distribution company (disco) with distributed generation (DG) and interruptible loads (IL) in a competitive market. The disco objective, modeled through the upper-level problem, is to minimize the cost of market purchases and DG unit dispatch while taking into account the responses of the other discos. This upper-level problem is constrained by a lower-level market clearing problem whose objective corresponds to maximization of social welfare. Such a setting results in a multi-disco equilibrium problem formulated as an equilibrium problem with equilibrium constraints (EPEC) by combining the optimality conditions of all upper-level problems. Using a nonlinear approach, the EPEC problem is reformulated as a single nonlinear optimization model which is simultaneously solved for all discos. The proposed approach is applied to an ac model of a power system to account for voltage and reactive power constraints of the transmission and distribution networks. Numerical examples based on two test systems are presented to illustrate the application of the proposed method.
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