Original Research

Journal of Engineering Research

, 2:17

First online:

Open Access This content is freely available online to anyone, anywhere at any time.

A mixed integer linear programming based approach for unit commitment in smart grid environment

  • R. GhadirianariAffiliated withDepartment of Electrical Engineering, Tehran Science and Research Branch, Islamic Azad University Email author 
  • , M. RashidinejadAffiliated withDepartment of Electrical Engineering, Shahid Bahonar University of Kerman
  • , M. Fotuhi-FiruzabadAffiliated withCentre of Excellence in Power System Control and Management, Department of Electrical Engineering, Sharif University of Technology


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.


Demand response Mixed-integer programming Smart grid Unit commitment