Abstract
A detailed study of the potential impact of low-voltage (LV) residential demand-side management (DSM) on the cost and greenhouse gas (GHG) emissions is presented. The proposed optimization algorithm is used to shift noncritical residential loads, with the wet load category used as a case study, in order to minimize the total daily cost and emissions due to generation. This study shows that it is possible to reshape the total power demand and reduce the corresponding cost and emissions to some extent. It is also shown that, when the baseload generating mix is dominated by coal-fired generation, the daily profiles of GHG emissions and cost conflict, such that further optimization of the cost leads to an increase in emissions.
Highlights
C USTOMERS’ interest in the reduction of the cost of their daily power demand has increased of late
The results demonstrate similar trends for each season (Figs. 6, 7, 8 and 9): in the winter there is a rapid decrease in total daily cost of demand as the number of shifted cycles is increased to 3500, beyond which it is either stabilised or decreases with a slower rate; in summer the minimum combined cost is achieved at the maximum number of shifted cycles - this is because the power demand for electric heating and lighting is higher during winter at reconnection time of the shifted loads, allowing for more shifted cycles during summer
This paper has shown that management of low voltage (LV) loads can allow for significant reductions in cost but is only effective in reducing greenhouse gas emissions (GHG) emissions when coal is supplying the marginal generation during the day
Summary
C USTOMERS’ interest in the reduction of the cost of their daily power demand has increased of late. This cost describes the price of electricity, and the environmental cost, defined in this paper by the generation of greenhouse gas emissions (GHG). One method of altering the cost to the consumer is through load manipulation by means of demand side management (DSM), which will impact on multiple aspects of the supply of electrical energy. There have been several studies on DSM strategies and their impact on energy demand [1], they have focussed on issues such as generation planning [2]–[4], or the effect on the energy efficiency [5], [6], and there are comparatively few studies directly connected to pricing and environmental factors [7]–[9]. As the approaches applied for industrial DSM are not appropriate for the analysis of LV networks, new methodologies must be developed and implemented
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
