Examining the benefits of load shedding strategies using a rolling-horizon stochastic mixed complementarity equilibrium model
Mel T. Devine and
European Journal of Operational Research, 2018, vol. 267, issue 2, 643-658
As a result of government policies increasing the amount of electricity generated from fluctuating renewable sources in many countries, the requirement for flexibility in the corresponding electricity systems increases. On the demand side, load shedding is one demand response mechanism contributing to an increased flexibility. Traditionally, load shedding was based on rather static or rotational strategies, whereby the system operator chooses the consumers for load shedding. However, ongoing technological developments provide the basis for smarter and more efficient load shedding strategies. We therefore examine the costs and strategies associated with such mechanisms by modelling an electricity market with different types of generators and consumers. Some consumers provide flexibility through load shedding only while others additionally have the ability to generate their own electricity. Focussing on the impacts of how and to whom consumers with own generation ability can supply electricity, the presence of market power and generator uncertainty, we propose a rolling horizon stochastic mixed complementarity equilibrium model, where the individual optimisation problems of each player are solved simultaneously and in equilibrium. We find that a non-static strategy reduces consumer costs while allowing consumers to provide own generation to the whole market results in minimal benefits. The presence of market power was found to increase costs to consumers.
Keywords: OR in energy; Stochastic programming; Load shedding; Stochastic mixed complementarity; Rolling horizon (search for similar items in EconPapers)
References: View references in EconPapers View complete reference list from CitEc
Citations Track citations by RSS feed
Downloads: (external link)
Full text for ScienceDirect subscribers only
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
Persistent link: https://EconPapers.repec.org/RePEc:eee:ejores:v:267:y:2018:i:2:p:643-658
Access Statistics for this article
European Journal of Operational Research is currently edited by Roman Slowinski, Jesus Artalejo, Jean-Charles. Billaut, Robert Dyson and Lorenzo Peccati
More articles in European Journal of Operational Research from Elsevier
Series data maintained by Dana Niculescu ().