Costs of Demand Response from Residential Customers’ Perspective

Abstract

Electricity demand in a certain locality varies during the day, depending on weather conditions, daily life routines, or a social event in a town. During high/peak demands, expensive power plants are put into operation, which affects electricity prices. Moreover, power lines are overloaded. If generation capacity is insufficient, a blackout may result. Demand response (DR) programs are widely proposed in energy research to tackle these problems. Although the benefits of DR programs are well known, customer response levels to these programs is low. This is due to the small fraction of benefits they receive against the loss of comfort, lost leisure time, and other inconveniences. The objective of this work is to study DR costs from the customer perspective by considering these factors. A customer survey-based direct approach is used to evaluate the willingness of customers to accept (WTA) a certain compensation when shifting the load is adopted. Two different methods are used to calculate DR costs: percentage compensation, which customers are WTA, and one based on a macroeconomic model, which considers the dependency factor of customers on loads and hourly wage. A linear mathematical model is presented based on both these techniques. This study reveals that DR costs are much less than interruption costs paid by the utility company, and hence is in the best interests of all stakeholders, i.e., customers, utility company, and transmission company.

Impact of Demand Response on Reliability Enhancement in Distribution Networks

“…While the electric energy industry is moving towards changing the power system structure, various problems and challenges, including transmission network congestion [9], electricity price spikes [10,11], operation, and management, have emerged. In the emerging competitive electricity markets, congestion management plays an essential role in economical, safe, and stable operation of the power system [12]. With the development of demand-side management, it was decided to activate load and customers so that electricity market problems would be resolved with minimum cost.…”

“…The investigated studies had some shortcomings that might affect the decisions of a DSO. In this regard, in [3,[9][10][11][12][13], although DR programs were used, the reliability of the distribution system was not investigated. In some articles (for example, [12][13][14][15][16][17][18]), the authors presented a framework for developing sell/purchase strategies for a distribution company in the energy and retail markets considering demand uncertainty, but none of them examined the effect of elasticity on consumption demand.…”

“…In this regard, in [3,[9][10][11][12][13], although DR programs were used, the reliability of the distribution system was not investigated. In some articles (for example, [12][13][14][15][16][17][18]), the authors presented a framework for developing sell/purchase strategies for a distribution company in the energy and retail markets considering demand uncertainty, but none of them examined the effect of elasticity on consumption demand. In some studies, no pricing scheme was used, such that the customers of the distribution network were ignored (for example, [32][33][34][35][36][37][38][39][40][41][42][43][44][45][46][47]).…”

Harnessing the Flexibility of District Heating System for Integrating Extensive Share of Renewable Energy Sources in Energy Systems

“…However, in case of other appliances, it is relatively difficult to establish the acceptable limits of user comfort [22]. For instance, the load shifting costs linked to the Finnish household appliances were estimated in [23] by applying customer survey based approach. Moreover, no additional equipment other than a smart thermostat is required to probe the power resource or sink capabilities of TCLs.…”

A Novel Algorithm with Multiple Consumer Demand Response Priorities in Residential Unbalanced LV Electricity Distribution Networks

“…Such algorithms were proposed before, in papers such as [9,16,17]. However, in these existing approaches the operation state of the network is assessed using load flow computations, which are time-costly, especially for networks with larger sizes [26][27][28], and they are limited to proposing two objective functions.…”