Token-based scheduling for access guarantee in deregulated electricity markets' smart grids. Issue 1 (1st January 2017)

• Record Type: Journal Article
• Authors: Ngondya, Daniel John; Mwangoka, Joseph Wynn
• Editors: Ai, Qingsong
• Is Part Of: Cogent engineering. Volume 4:Issue 1(2017)
• Publication Date: 2017-01-01
• Subjects: smart grid -- appliance scheduling -- community-based scheduling -- deregulated electricity markets -- demand-side management -- residential automation; Engineering -- Periodicals; Technology -- Periodicals; Engineering; Technology; Periodicals; 620
• DOI: 10.1080/23311916.2017.1394417
• Languages: English
• ISSNs: 2331-1916

Abstract

Abstract: Maintaining electric grid reliability is increasingly becoming a challenge because of factors such as significant accommodation of intermittent renewable energy sources into the grid, emergence of new consumption patterns and raising demand worldwide. Sustainable grid reliability cannot be attained solely by increasing generation; Demand-Side Management strategies must be employed. Community-based demand management strategies offer benefits like implementation costs, improved consumption pattern prediction and flexibility in policy management. However, ensuring guaranteed access for every consumer in the community is a challenge-especially when available power capacity is constrained. In this work, we have proposed an algorithm that guarantees access to shared capacity for each consumer in the community in an equitable manner. Numerical analysis of the algorithm indicates access variance of 0.1–0.3, compared to variance of 0.9–2.3 in literature, indicating more equitable access by our proposed algorithm. Moreover, the algorithms help to flatten the demand curve by keeping peak-to-average ratio (PAR) values as small as 1.02. Utility companies have an opportunity to enhance grid reliability through reduced PAR values by setting maximum power capacity for each time slot and consumers can save up to 16.6% off their bills by adhering to the set capacity. Demonstrated benefits of proposed algorithms to both consumers and utilities is likely to enhance acceptance of demand management programs in the electricity sector.