Load Scheduling and Power Trading in Systems With High Penetration of Renewable Energy Resources

Abstract

In this paper, we focus on the problems of load scheduling and power trading in systems with high penetration of renewable energy resources (RERs). We adopt approximate dynamic programming to schedule the operation of different types of appliances including must-run and controllable appliances. We assume that users can sell their excess power generation to other users or to the utility company. Since it is more profitable for users to trade energy with other users locally, users with excess generation compete with each other to sell their respective extra power to their neighbors. A game theoretic approach is adopted to model the interaction between users with excess generation. In our system model, each user aims to obtain a larger share of the market and to maximize its revenue by appropriately selecting its offered price and generation. In addition to yielding a higher revenue, consuming the excess generation locally reduces the reverse power flow, which impacts the stability of the system. Simulation results show that our proposed algorithm reduces the energy expenses of the users. The proposed algorithm also facilitates the utilization of RERs by encouraging users to consume excess generation locally rather than injecting it back into the power grid.Index Terms-Approximate dynamic programming, demand side management (DSM), load scheduling, power trading.

An Efficient Demand Side Management System with a New Optimized Home Energy Management Controller in Smart Grid

“…In HSA, each musician plays note repeatedly to improve its harmony and generates new random variable according to Equation (28).…”

“…However, authors have not addressed the user comfort and also computational time of the algorithm is high. Similarly, in [27,28], integer linear programming (ILP) and dynamic programming (DP) are used to schedule the appliances and reduce electricity cost and PAR. However, these algorithms are inefficient in terms of computational time.…”

Demand Side Management in Nearly Zero Energy Buildings Using Heuristic Optimizations

“…The load scheduling and power trading problems in the residential area of MG with a large share of RE are discussed in [12]. An approximate DP is used for appliance scheduling, and a game theoretic approach is used for power trading among different users.…”

“…Although the scheduling strategy reduces the energy expense, RESs integration can further decrease the electricity bill, carbon emissions and PAR. Residential load scheduling and power trading among different homes in the presence of RESs is discussed in [12]. Stochastic optimization is used for the residential scheduling, whereas a game theoretic approach is adopted for power trading among multiple homes.…”

“…In [11], the authors use integer linear programming (ILP) to reduce the daily electricity bill of residential consumers. An approximate dynamic programming (DP) is used in [12] to reduce the electricity burden and PAR on the main power grid. An energy sale mechanism among different MGs is proposed using the game theoretic approach.…”