# Implementation of a Demand-Side Management Solution for South Korea's Demand Response Program
###### Abstract  
In this paper, we show the development of a demand-side management solution (DSMS) for demand response (DR) aggregator and actual demand response operation cases in South Korea. To show an experience, Korea's demand response market outline, functions of DSMS, real contracted capacity, and payment between consumer and load aggregator and DR operation cases are revealed. The DSMS computes the customer baseline load (CBL), relative root mean squared error (RRMSE), and payments of the customers in real time. The case of 10 MW contracted customers shows 108.03% delivery rate and a benefit of 854,900,394 KRW for two years. The results illustrate that an integrated demand-side management solution contributes by participating in a DR market and gives a benefit and satisfaction to the consumer. demand response; demand-side management solution; electricity market; energy management 2020 2020 2020 2020 2020 2020 2020 2020 2020 2020 2  
with the supply-side resources. DSM programs can be classified into load management (LM) types and energy efficiency (EE) types [4; 5; 6; 7; 8]. In order to deal with peak load conditions, electric utilities have to invest in system capacity, which is underutilized during most times. Not surprisingly, utilities have been seeking methods to improve capacity utilization. Demand response (DR) is one mechanism utilities use to curtail or shift peak customer load [9; 10; 11]. Regarding the remuneration, a price-based and an incentive-based DR program are used. In a price-based DR program, consumers reduce their power consumption by responding to the electricity tariff set by the electricity market. In an incentive-based DR program, consumers are contracted by individuals or groups to reduce their power consumption for a certain period that the economic transactions requested in the electricity market. For a price-based DR program, researchers investigated a multi-agent modeling and optimization algorithms under DR programs for real-time prices [12]; a coordination strategy between a micro network and a price-based demand response program for adjusting loads [13]; a bidirectional communication smart meter design between the household smart meters and the distribution management system [14]; a dynamic price scheme for electricity in a smart network, by analyzing the behavior and the possible demand response of the consumer [15]; and a modified real-time price model that encourages customer choice in electricity rates and is based on the amount of risk customers are willing to take and a real-time grid condition index developed by the California Independent Service Operator [16]. For an incentive-based DR program, research has shown that a fuzzy-based dynamic incentive scheme for residential customers can effectively incorporate the influences of socioeconomic conditions, expected curtailment, probability of curtailment, and notice period [17]. The dynamic adjustment of the offered prices is analyzed to reduce the demand and maximize its performance within T days [18]. The uncertainty of the demand in the network planning is modeled and includes the integral control of the load disconnection in search of the minimum cost [19]. The participation of smart homes with the help of a controller is capable of managing the electrical installation and restructuring the demand profile by changing the operation of the flexible loads [20]. The incentives motivate clients to participate in automatic DR programs with the purpose of compensating imbalances between offer and demand [21], and a DR program is shown from the economic point of view based on optimal incentives [22]. Demand resources have played an important role in Korea for more than 20 years. To reduce peak demand during summer and winter, DR programs and the operating system have been researched and implemented as a demonstration since 2010. In 2014, any customers who joined the DR market were able to sell their reduced demand in the electricity market as supply resources [23; 24].