1244 IEEE TRANSACTIONS ON SMART GRID, VOL. 3, NO. 3, SEPTEMBER 2012 Demand Side Management in Smart Grid Using Heuristic Optimization Thillainathan Logenthiran, Student Member, IEEE, Dipti Srinivasan, Senior Member, IEEE, and Tan Zong Shun Abstract—Demand side management (DSM) is one of the im- portant functions in a smart grid that allows customers to make informed decisions regarding their energy consumption, and helps the energy providers reduce the peak load demand and reshape the load profile. This results in increased sustainability of the smart grid, as well as reduced overall operational cost and carbon emission levels. Most of the existing demand side management strategies used in traditional energy management systems employ system specific techniques and algorithms. In addition, the existing strategies handle only a limited number of controllable loads of limited types. This paper presents a demand side management strategy based on load shifting technique for demand side man- agement of future smart grids with a large number of devices of several types. The day-ahead load shifting technique proposed in this paper is mathematically formulated as a minimization problem. A heuristic-based Evolutionary Algorithm (EA) that easily adapts heuristics in the problem was developed for solving this minimization problem. Simulations were carried out on a smart grid which contains a variety of loads in three service areas, one with residential customers, another with commercial customers, and the third one with industrial customers. The sim- ulation results show that the proposed demand side management strategy achieves substantial savings, while reducing the peak load demand of the smart grid. Index Terms—Demand side management, distributed energy resource, evolutionary algorithm, generation scheduling, load shifting, smart grid. I. INTRODUCTION S MART GRID [1], [2] represents a vision of the future power systems integrating advanced sensing technologies, control methodologies and communication technologies at transmission and distribution levels in order to supply elec- tricity in a smart and user friendly way. According to the U.S. Department of Energy’s modern grid initiative report, the main characteristics [2] of a smart grid are consumer friend- liness, hack proof self-healing, resistance for attack, ability to accommodate all types of generation and storage options, electricity market based efficient operation, high power quality, and optimal assets. This modern grid is prompted by several economical, political, environmental, social, and technical factors. Demand side management [3], [4] is an important function in energy management of the future smart grid, which provides support towards smart grid functionalities in various areas such as electricity market control and management, infrastruc- ture construction, and management of decentralized energy Manuscript received July 22, 2011; revised November 08, 2011; accepted April 11, 2012. Date of publication June 08, 2012; date of current version Au- gust 20, 2012. This work was supported by National Research Foundation pro- gramme grant, NRF-2007EWT-CERP01-0954 (R-263-000-522-272). Paper no. TSG-00260-2011. The authors are with the Department of Electrical and Computer Engineering, National University of Singapore, Singapore 117576 (e-mail: logenthiran@nus. edu.sg; dipti@nus.edu.sg; u0705831@nus.edu.sg). Color versions of one or more of the figures in this paper are available online at http://ieeexplore.ieee.org. Digital Object Identifier 10.1109/TSG.2012.2195686 resources and electric vehicles. Controlling and influencing energy demand can reduce the overall peak load demand, reshape the demand profile, and increase the grid sustainability by reducing the overall cost and carbon emission levels. Ef- ficient demand side management can potentially avoid the construction of an under-utilized electrical infrastructure in terms of generation capacity, transmission lines and distribution networks. Smart pricing [5], [6] is a unique characteristic of smart grid made possible by usage of smart metering devices in the au- tomatic metering infrastructure. It could lead to cost-reflective pricing based on the entire supply chain of delivering electricity at a certain location, quantity and period. When smart pricing is used with demand side management, control of the customer’s energy usage will be influenced by real-time penalty and incen- tive schemes at all levels of the supply chain. However, the ra- tionale behind the implementation of demand side management within the context of the smart grid is to promote the overall system efficiency, security and sustainability by maximizing the capacity of the existing infrastructure while facilitating the in- tegration of low carbon technology into the system. Demand side management also plays a significant role in electricity markets [7], [8]. Demand side management system will inform cluster’s central controller about new load schedule and available load reduction capabilities for each time step of next day. Then, the central controller can place bids in the market such that some loads from the peak demand will be shifted. Profits made through this load demand side manage- ment will be reimbursed to customers of the cluster. There are several demand side management techniques and algorithms used in the literature [4]–[6], [9]–[13]. Most of them are system specific [4]–[6], [10], [13] strategies, and some of which are not applicable to practical systems that have a wide variety of independent devices. Most of the techniques were de- veloped using dynamic programming [13] and linear program- ming [5], [10]. These programming techniques cannot handle a large number of controllable devices from several types of de- vices which have several computation patterns and heuristics. The primary objective of the demand side management tech- niques presented in the literature is reduction of system peak load demand and operational cost. Although the utilities are ca- pable of offering different incentives to respective customers for direct control [12]–[15] over selected loads by grouping the cus- tomers’ loads, most of the methodologies used in the literature do not consider the criteria and objectives independently. Thus, it is difficult to employ these methods for demand side manage- ment of future smart grids which aim to provide the customers with greater control over their energy consumption. In a smart grid, the demand side management strategies need to handle a large number of controllable loads of several types. Further- more, loads can have characteristics which spread over a few hours. Therefore, the strategies should be able to deal with all possible control durations of a variety of controllable loads. 1949-3053/$31.00 © 2012 IEEE