# Enhancing Energy Efficiency in Retail within Smart Cities through Demand-Side Management Models
## 1 Introduction  
Energy has a significant impact on a country's economic development and people's livelihoods, particularly in terms of electricity demand. In pursuit of zero carbon emissions by 2050, companies are endeavoring to implement carbon reduction measures, and every step of their supply chain, from production to end use, must achieve the goal of utilizing 100% renewable energy before 2050. Energy management comprises three primary directions: creating energy, storing energy, and conserving energy. The government actively promotes renewable energy sources such as wind and solar power, while companies, under the regulation of the Electricity Act, establish renewable energy and energy storage facilities, and sell excess energy back to the Taipower (Taiwan Power Company (Taipei City, Taiwan)). Additionally, the promotion of energy conservation to businesses and the public is also encouraged. Energy management, aside from increasing energy supply, considers the regulation of energy usage from the demand side as an important approach to address the energy challenge. More studies have focused on energy management in household electricity usage [1]. While managing energy at the household level is crucial, greater benefits can be achieved by implementing energy management strategies at the industrial level. Past research has analyzed and confirmed that the proposed algorithms are effective in minimizing peak loads, demonstrating the feasibility of electricity demand analysis and prediction through power data analysis [2]. Industrial electricity consumption can generally be categorized into productive and non-productive sectors, which encompass various industries, including electronics manufacturing, chemicals, textiles, food, metals, papermaking, finance, insurance, real estate, wholesale, retail, catering, transportation, warehousing, communications, and social services. Given that the retail industry is a domestic industry and a significant economic driver, this study focuses on the retail sector. There have been some demand-side management studies in the past that have collected data through the Internet of Things (IoT) architecture [3] and have conducted energy management through analytical methods [4], but they have not specifically focused on the aggregator. This article examines the demand-side management (DSM) practices of major international countries, investigates the awareness and willingness of the domestic retail industry to participate in DSM through surveys, and ultimately evaluates the model's effectiveness through system simulations. DSM is an important method for sustainable energy management. However, regulations, ecology, and environments surrounding the power industry vary greatly around the world. Due to significant differences in the power industry in different regions, data collection can be challenging in some areas (such as Taiwan). Despite this, progress is being made within the existing framework to render electricity more sustainable based on the concept of'sustainable development.' This method can also be applied in regions with similar power industry environments. Large electricity consumers are typically enterprises, and various governments have corresponding energy policies in place. However, smaller retail stores generally lack awareness of energy saving. Yet, by connecting a considerable number of retail stores, each store making a small reduction in electricity consumption can result in substantial overall energy savings. Since the retail industry belongs to the service sector, achieving autonomous electricity conservation without incentives can be challenging. This study aims to explore innovative DSM applications in the retail industry by examining industry players' willingness to adopt such solutions. Therefore, this study aims to explore the feasibility of the DSM aggregator model in the retail industry.