Framework for minimum user participation rate determination to achieve specific demand response management objectives in residential smart grids. (January 2016)

• Record Type: Journal Article
• Authors: Hassan, Naveed Ul; Khalid, Yawar Ismail; Yuen, Chau; Huang, Shisheng; Pasha, Muhammad Adeel; Wood, Kristin L.; Kerk, See Gim
• Is Part Of: International journal of electrical power & energy systems. Volume 74(2016:Jan.)
• Page Start: 91
• Page End: 103
• Publication Date: 2016-01
• Subjects: Smart grids -- Demand side management -- Smart energy systems; Electrical engineering -- Periodicals; Electric power systems -- Periodicals; Électrotechnique -- Périodiques; Réseaux électriques (Énergie) -- Périodiques; Electric power systems; Electrical engineering; Periodicals; 621.3
• DOI: 10.1016/j.ijepes.2015.07.005
• Languages: English
• ISSNs: 0142-0615

Abstract

Highlights: A framework to determine minimum user participation to achieve specific DRM objectives. Methodologies to tradeoff participation rate and inconvenience of participating users. Development of appropriate inconvenience indexes for flexible loads. A data-set of household power consumption matching a given aggregated load profile shape. A step towards designing incentives to attract enough users to achieve desired objectives. Abstract: In this paper, we develop a framework for grid operators to determine the minimum required user participation rate to achieve specific Demand Response Management (DRM) objectives in residential smart grids. Under this framework, we propose power limit and inconvenience limit methodologies. In the power limit methodology, the grid communicates a power limit to participating users to achieve a desired amount of peak load reduction. In the inconvenience limit methodology, the grid communicates an inconvenience limit to participating users and demand is reduced accordingly to achieve the desired peak load reduction. We define indexes to measure user inconvenience and recommend physical and thermal load models for flexible appliances to measure temperature deviations and scheduling delays. We then analyze the performance of our developed framework in a residential community comprising of 780 homes. We generate power consumption data for individual devices of different users to match an aggregated load curve shape from the RELOAD database on a typical summer day. We determine the required user participation, experienced inconvenience temperature variations and scheduling delays for various DRM objectives. By determining the minimum required user participation, this framework can help the grid operators in designing proper incentives for specific DRM goals.