Next Article in Journal
Graphene Quantum Dots Doped PVDF(TBT)/PVP(TBT) Fiber Film with Enhanced Photocatalytic Performance
Previous Article in Journal
Geopolymer-Bonded Laminated Veneer Lumber as Environmentally Friendly and Formaldehyde-Free Product: Effect of Various Additives on Geopolymer Binder Features
Open AccessArticle

Maximizing Demand Response Aggregator Compensation through Optimal RES Utilization: Aggregation in Johannesburg, South Africa

Department of Electrical and Electronics Engineering Science, University of Johannesburg, Johannesburg 2006, South Africa
*
Author to whom correspondence should be addressed.
Appl. Sci. 2020, 10(2), 594; https://doi.org/10.3390/app10020594
Received: 17 November 2019 / Revised: 21 December 2019 / Accepted: 27 December 2019 / Published: 14 January 2020
(This article belongs to the Section Energy)
This paper examines the role of demand response aggregators in minimizing the cost of electricity generation by distribution utilities in a day-ahead electricity market. In this paper, 2500 standard South African homes are considered as end users. Five clusters (and aggregators) are considered with 500 homes in each cluster. Two cases are analysed: (1) Utilization of renewable energy sources (RES) is implemented by the distribution supply operator (DSO), where it meets excess demand for end users during peak hours by purchasing electricity from the renewable sources of the energy market, and (2) Utilization of RES is implemented by end users alone, and it is assumed that every household has one plug-in electric vehicle (PEV). The aggregators then compete with each other for the most cost-effective energy usage profile; the aggregator with the least energy demand wins the bid. In both cases, energy pricing is estimated according to the day-ahead energy market. A typical day during winter in Johannesburg is considered for the simulation using a genetic algorithm (GA). Results obtained demonstrate the effectiveness of demand response aggregators in maximizing the benefits on both sides of the electricity supply chain. View Full-Text
Keywords: demand response; day-ahead market; renewable energy sources; genetic algorithm; aggregator demand response; day-ahead market; renewable energy sources; genetic algorithm; aggregator
Show Figures

Figure 1

MDPI and ACS Style

Essiet, I.O.; Sun, Y. Maximizing Demand Response Aggregator Compensation through Optimal RES Utilization: Aggregation in Johannesburg, South Africa. Appl. Sci. 2020, 10, 594.

Show more citation formats Show less citations formats
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Back to TopTop