The future of power systems known as smart grids is expected to involve an increasing level of intelligence and incorporation of new information and communication technologies in every aspect of the power grid. Demand response resources and gridable vehicle are two interesting programs which can be utilized in the smart grid environment. Demand response resources can be used as a demand side virtual power plant (resource) to enhance the security and reliability of utility and have the potential to offer substantial benefits in the form of improved economic efficiency in wholesale electricity markets. An economic model of incentive responsive loads is modelled based on price elasticity of demand and customers' benefit function. On the other hand, a gridable vehicle can be used as a small portable power plant to improve the reliability as well as security of the power system. This paper formulates a mixed-integer programming approach to solve the unit commitment problem with demand response resources and gridable vehicles. The objective function of the unit commitment problem has been modified to incorporate demand response resources and gridable vehicles. The proposed method is conducted on the conventional 10-unit test system to illustrate the impacts of smart grid environment on the unit commitment problem. Moreover the benefits of implementing demand response resources and gridable vehicle in electricity markets are demonstrated.Keywords: Demand response; mixed-integer programming; smart grid; unit commitment. ( ) PRInitial electricity price of an hour.Fuel cost coefficients of a unit. ( ) PRSpot electricity price of an hour. ( ) BCustomer ( ) PenPenalty of an hour. ( ) ESelf and cross elasticity of an hour. , r sCoefficients to reinforce the effect of Penalty and award in incentive-based programs, respectively. ( ) EmEmission function of a unit. ( ) RDRRamping down limit of a unit. ( ) EmLower limit on the emission of a unit. ( ) RURRamping ( ) NSENumber of segments for the piece-wise linearized emission curve. ( ) ΓDemand ratio parameter of an hour. GV PPower obtainable from one GV. ηThe potential of DR programs implementation.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
334 Leonard St
Brooklyn, NY 11211
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.