Analysing long-term interactions between demand response and different
electricity markets using a stochastic market equilibrium model. ESRI WP585, February 2018
Power systems based on renewable energy sources (RES) are characterised by
increasingly distributed, volatile and uncertain supply leading to growing requirements for
flexibility. In this paper, we explore the role of demand response (DR) as a source of flexibility
that is considered to become increasingly important in future. The majority of research in this
context has focussed on the operation of power systems in energy only markets, mostly using
deterministic optimisation models. In contrast, we explore the impact of DR on generator
investments and profits from different markets, on costs for different consumers from
different markets, and on CO2 emissions under consideration of the uncertainties associated
with the RES generation. We also analyse the effect of the presence of a feed-in premium
(FIP) for RES generation on these impacts. We therefore develop a novel stochastic mixed
complementarity model in this paper that considers both operational and investment
decisions, that considers interactions between an energy market, a capacity market and a
feed-in premium and that takes into account the stochasticity of electricity generation by RES.
We use a Benders decomposition algorithm to reduce the computational expenses of the
model and apply the model to a case study based on the future Irish power system. We find
that DR particularly increases renewable generator profits. While DR may reduce consumer
costs from the energy market, these savings may be (over)compensated by increasing costs
from the capacity market and the feed-in premium. This result highlights the importance of
considering such interactions between different markets
