Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/174274 
Year of Publication: 
2016
Series/Report no.: 
ESRI Working Paper No. 541
Publisher: 
The Economic and Social Research Institute (ESRI), Dublin
Abstract: 
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. Focusing 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. We also consider the optimal foresight horizon that market players should consider. This novel study finds that the optimal foresight horizon is mainly driven by the daily load structure and, to a lower degree, by the uncertainty of the generators' availability.
Subjects: 
Load shedding
Demand-side flexibility
Rolling horizon
Stochastic mixed complementarity
Document Type: 
Working Paper

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