A looming revolution: Implications of self-generation for the risk exposure of retailers. ESRI WP597, September 2018

Managing the risk associated with uncertain load has always been a challenge for retailers in electricity markets. Yet the load variability has been largely predictable in the past, especially when aggregating a large number of consumers. In contrast, the increasing penetration of unpredictable, small-scale electricity generation by consumers, i.e. self-generation, constitutes a new and yet greater volume risk. Using value-at-risk metrics and Monte Carlo simulations based on German historical loads and prices, the contribution of decentralized solar PV self-generation to retailers’ load and revenue risks is assessed. This analysis has implications for the consumers’ welfare and the overall efficiency of electricity markets

Determinants of power spreads in electricity futures markets: A multinational analysis. ESRI WP580, December 2017

The growth in variable renewable energy (vRES) and the need for flexibility in power systems go hand in hand. We study how vRES and other factors, namely the price of substitute fuels, power price volatility, structural breaks, and seasonality impact the hedgeable power spreads (profit margins) of the main dispatchable flexibility providers in the current power systems - gas and coal power plants. We particularly focus on power spreads that are hedgeable in futures markets in three European electricity markets (Germany, UK, Nordic) over the time period 2009-2016. We find that market participants who use power spreads need to pay attention to the fundamental supply and demand changes in the underlying markets (electricity, CO2, and coal/gas). Specifically, we show that the total vRES capacity installed during 2009-2016 is associated with a drop of 3-22% in hedgeable profit margins of coal and especially gas power generators. While this shows that the expansion of vRES has a significant negative effect on the hedgeable profitability of dispatchable, flexible power generators, it also suggests that the overall decline in power spreads is further driven by the price dynamics in the CO2 and fuel markets during the sample period. We also find significant persistence (and asymmetric effects) in the power spreads volatility using a univariate TGARCH model

The role of demand response in mitigating market power - A quantitative analysis using a stochastic market equilibrium model. ESRI WP635, August 2019

Market power is a dominant feature of many modern electricity markets with an oligopolistic structure, resulting in increased consumer cost. This work investigates how consumers, through demand response (DR), can mitigate against market power. Within DR, our analysis particularly focusses on the impacts of load shifting and self-generation. A stochastic mixed complementarity problem is presented to model an electricity market characterised by oligopoly with a competitive fringe. It incorporates both energy and capacity markets, multiple generating firms and different consumer types. The model is applied to a case study based on data for the Irish power system in 2025. The results demonstrate how DR can help consumers mitigate against the negative effects of market power and that load shifting and self-generation are competing technologies, whose effectivity against market power is similar for most consumers. We also find that DR does not necessarily reduce emissions in the presence of market power

Optimally allocating renewable generation in Ireland: a long-term outlook until 2050. ESRI Research Bulletin, 2018/03

The Irish energy white paper released in December 2015 states the objective of diversifying electricity generation from renewable energy sources (RES-E). While onshore wind is planned to continue to make a significant contribution, the question arises which roles other RES-E technologies, such as solar PV, wind offshore or bioenergy, will play in the future. Moreover, the Irish 2030 target for RES-E is about to be set. Since the electricity demand growth in future is uncertain and the national target is yet unknown, this creates a high uncertainty around the overall amount of RES-E required. In this uncertain context, this research seeks to provide support for 1. achieving the national RES-E target determined as percentage share of energy demand in a cost minimal way under consideration of different diversification approaches, and 2. long-term planning of the electricity system by providing insight into the future regional distribution of generation and demand under different scenarios

Capacity-constrained renewable power generation development in light of storage cost uncertainty. ESRI Working Paper No. 647 December 2019

The development of sustainable energy sources and their enabling infrastructures are often met by public opposition, resulting in lengthy planning processes. One proposed means of reducing public opposition is constraining the capacity of renewable energy projects onshore, leading to more small-scale, decentralised and possibly community-driven developments. This work computes the effects of same by performing a medium- and long-term generation expansion planning exercise considering two renewable development cases, in which renewable power expansion is spatially constrained to certain degrees, under high and low storage cost regimes. We employ an appropriately designed optimisation model, accounting for network effects, which are largely neglected in previous studies. We apply our study to the future Irish power system under a range of demand and policy scenarios. Irrespective of storage costs, the unconstrained portfolio is marginally cheaper than the constrained one. However, there are substantial differences in the final generation expansion portfolios. The network reinforcement requirements are also greater under the unconstrained approach. Lower storage costs only slightly mitigate the costs of capacity constraints but significantly alter the spatial distribution of generation investments. The differential in costs between the unconstrained and constrained cases increases non-linearly with renewable generation targets

Compensating communities to reduce resistance to energy infrastructure development. ESRI Research Bulletin, 2018/01

Ireland has ambitious plans to reduce the level of greenhouse gases emitted from electricity generation by increasing the amount of power that is generated from renewable technologies. Doing so will require a significant expansion of wind farms, and an accompanying expansion of the electricity transmission network (the “grid”). Previous analyses that we have conducted have shown that Irish residents are generally favourably disposed towards further development of renewable generation technologies; however, in practice, planners and policy makers are frequently met with objections from local communities to specific siting proposals. Community resistance to electricity infrastructure development can result in unhappy residents, frustrated planners, and project delays. In this research we consider a range of procedures that could be adopted in order to involve local communities in these projects. Such procedures may potentially reduce resistance amongst local communities

Demand response within the energy-for-water-nexus - A review. ESRI WP637, October 2019

A promising tool to achieve more flexibility within power systems is demand re-sponse (DR). End-users in many strands of industry have been subject to research up to now regarding the opportunities for implementing DR programmes. One sector that has received little attention from the literature so far, is wastewater treatment. However, case studies indicate that the potential for wastewater treatment plants to provide DR services might be significant. This review presents and categorises recent modelling approaches for industrial demand response as well as for the wastewater treatment plant operation. Furthermore, the main sources of flexibility from wastewater treatment plants are presented: a potential for variable electricity use in aeration, the time-shifting operation of pumps, the exploitation of built-in redundan-cy in the system and flexibility in the sludge processing. Although case studies con-note the potential for DR from individual WWTPs, no study acknowledges the en-dogeneity of energy prices which arises from a large-scale utilisation of DR. There-fore, an integrated energy systems approach is required to quantify system and market effects effectively

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

Examining the benefits of demand reduction policies for electricity. ESRI Research Bulletin, 2018/03

Many governments have adopted policies that provide incentives to increase the amount of electricity generated from clean and renewable sources. However, the availability of such sources, e.g., solar or wind energy, is unpredictable and varies throughout the day and seasons. To account for this variability electricity systems need to become more flexible, i.e., there must be measures in place to ensure that demand and supply are balanced when renewable sources are not available

Are Renewables Profitable in 2030? A Comparison between Wind and Solar across Europe

The European Union has set ambitious targets for emission reduction and the penetration of renewable energy, including the electricity generation sector as one of the major emitters of CO2. After a period of subsidy-driven investments, the costs of renewables decreased strongly making investments more attractive. Since European countries differ strongly in terms of natural resources, we analyse the profitability of wind onshore and offshore and solar PV across Europe to determine where it is optimal to invest in the future and to understand which factors drive the profitability of the investments. We use a power systems model to simulate the whole European electricity market in 2030. Using the renewable revenues determined by the model, we calculate the internal rate of return to analyse how profitable each technology is in each country. We find that investments in the considered technologies are not homogeneously profitable across Europe. This suggests that cooperation between European countries can be expected to achieve the overall targets at lower costs than nationally-driven approaches. We also find that in many countries, wind onshore and solar PV are profitable by 2030 in absence of any financial support. Wind offshore does not seem to be profitable without financial support