Abstract
Price based demand response is an important strategy to facilitate energy retailers and end-users to maintain a balance between demand and supply while providing the opportunity to end users to get monetary incentives. In this work, we consider real-time electricity pricing policy to further calculate the incentives in terms of reduced electricity price and cost. Initially, a mathematical model based on the backtracking technique is developed to calculate the load shifted and consumed in any time slot. Then, based on this, the electricity price is calculated for all types of users to estimate the incentives through load shifting profiles. To keep the load under the upper limit, the load is shifted in other time slots in such a way to facilitate end-users regarding social welfare. The user who is not interested in participating load shifting program will not get any benefit. Then the well behaved functional form optimization problem is solved by using a heuristic-based genetic algorithm (GA), wwhich converged within an insignificant amount of time with the best optimal results. Simulation results reflect that the users can obtain some real incentives by participating in the load scheduling process.
Highlights
Introduction and BackgroundThe smart grid (SG) is an emerging paradigm shift in power distribution systems that aims to improve itself using various information and communication technologies.It comprises various intelligent controlling and decision-making systems, which manage electricity generation, transmission and distribution through two-way communication mechanisms [1,2]
Unlike other pricing signals being widely used in the literature and real-time works such as real-time pricing (RTP), time of use (TOU), day-ahead pricing (DAP), critical peak pricing (CPP), the proposed price signal is dynamic with changing values at every instant of time
This price signal is considered to deeply analyze the realistic cost and incentive profiles of all the consumers instead of developing the load scheduling techniques of algorithms based on DAP, which is known in advance to the users and energy management controllers
Summary
Milyani 1 , Muhammad Awais 2 and Muhammad B. Computer Engineering Department, University of Alcalá, 28805 Alcalá de Henares, Spain
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