www.astesj.com 262 A Novel Demand Side Management by Minimizing Cost Deviation Vikas Anand Vatul 1 , Arputha Aravinth 1 , Narayanan K *,1 , Gulshan Sharma 2 , Tomonobu Senjyu 3 1 EEE Department, SASTRA Deemed University, Thanjavur, Tamil Nadu, India 2 Department of Electrical Power Engineering, Durban University of Technology, South Africa 3 Power and Energy System Control Laboratory, University of the Ryukyus, Japan A R T I C L E I N F O A B S T R A C T Article history: Received: 20 July, 2020 Accepted: 01 September, 2020 Online: 17 September, 2020 In the recent times power shortage has been a major setback to deal for the effective operation of power systems. Bridging the gap between generation and demand is known as Demand Side Management (DSM). For an effective DSM strategy to be implemented, it is crucial that both utility and customers be involved. By DSM, the energy generated is used more effectively. This reduces the burden of the utility to invest on additional generation. In this work, a DSM strategy has been performed on two systems: (i) on RTS 24 bus system with wind energy sources distributed at some nodes of the system (ii) on an institutional load with installed solar power plant. A generic DSM strategy to effectively utilize the generated energy and to minimize the utility bills for the customer has been proposed. An instantaneous billing scheme has been proposed. By implementing the instantaneous billing scheme, customers can be persuaded to change their consumption behavior, matching the demand with available generation. The results obtained are promising, with a resulting flat load profile and reduced utility bills for the customer. Keywords: Power Systems Energy System Demand Side Management Aggregated Energy Pricing Model Smart Grid Renewable Energy 1. Introduction Demand Side Management (DSM) has been in practice from the 20th century. Initially, DSM was implemented by replacing older equipment with a newer one for improved efficiency. DSM effectively reduces the gap between supply and demand with the help of various services. DSM is performed by suggesting adjustment in the electricity consumption of the customer to produce desired changes in the power distribution system. Some DSM strategies used to alter customers’ load profiles involve load shedding, valley filling, peak clipping, flexible load shape, strategic load growth, strategic conservation and load shifting [1]. The final load profile for each system depends on the operational requirement of the system. Performing DSM has the same objective to minimise customers’ utility bills and to reduce Peak to Average Ratio (PAR) by taking up different pricing models in many researches. By performing DSM, electrical infrastructure can be utilised effectively, and new investments on the same can be deferred. Price billing schemes are an important aspect of performing DSM. In recent times, instantaneous load billing scheme has been used to perform DSM. By implementing this billing scheme, the price at each hour can be changed depending on the aggregated load at that hour. A quadratic cost function has been used with the motive of reducing the total cost and minimize PAR with a simple billing mechanism for the subsequent period is proposed in [2]. This does not consider peak classification during the day, making it unfair to the customer by billing them similar at all times of the day based only on energy consumption. Some pricing models have been introduced and mapping between retail users and wholesale electric prices is portrayed in [3]. The motive was to improve utilization of cumulative generated energy and reduce energy cost by wholesale mapping of energy requirement [3]. A polynomial cost function with time-dependent coefficients has been used in [4]. The focus was to find the aggregated energy consumption and the selfish customers would modify their energy consumption in order to reduce their energy prices. The time slots have been classified in [4] as on peak, mid-peak and off-peak. Coefficients are time-dependent and are assigned based on the peak ASTESJ ISSN: 2415-6698 * Corresponding Author Narayanan. K, EEE Department, SASTRA Deemed University, Thanjavur, Tamil Nadu, India. Mob: +91-9790258910 Email: narayanan.mnit@gmail.com Advances in Science, Technology and Engineering Systems Journal Vol. 5, No. 5, 262-268 (2020) www.astesj.com Special Issue on Multidisciplinary Innovation in Engineering Science & Technology https://dx.doi.org/10.25046/aj050532