UK Electricity Market Research Articles

The Impact of Policy Measures on Future Power Generation Portfolio and Infrastructure: A Combined Electricity and CCTS Investment and Dispatch Model (ELCO)

This paper presents a general electricity-CO2 (ELCO) modeling framework that is able to simulate interactions of the energy-only market with different forms for national policy measures. We set up a two sector model where players can invest into various types of generation technologies including renewables, nuclear and Carbon Capture, Transport, and Storage (CCTS). For a detailed representation of CCTS we also include industry players (iron and steel as well as cement), and CO2 transport and CO2 storage including the option for CO2 enhanced oil recovery (CO2-EOR). The players maximize their expected profits based on variable, fixed and investment costs as well as the price of electricity, CO2 abatement cost and other incentives, subject to technical and environmental constraints. Demand is inelastic and represented via a selection of type hours. The model framework allows for regional disaggregation and features simplified electricity and CO2 pipeline networks. The model is balanced via a market clearing for the electricity as well as CO2 market. The equilibrium solution is subject to constraints on CO2 emissions and renewable generation share. We apply the model to a case study of the UK Electricity Market Reform to illustrate the mechanisms and potential results attained from the model.

The progressive inefficiency of replacing renewable obligation certificates with contracts-for-differences in the UK electricity market

This paper looks at the emerging risk/return profile for new renewable assets as a conventional wholesale electricity market progressively decarbonises. Using a detailed fundamental model of price formation risks, under increasing replacement of fossil fuel facilities with onshore and offshore wind, we show that the risk return profile becomes less attractive over time, and may therefore need sustained and possibly increasing policy support. Furthermore, we show that green certificate trading may become progressively more attractive as a supplementary support to wholesale prices, compared to fixed feed-in-tariffs. This is because the increasingly negative correlation between renewable output and wholesale prices reduces its revenue risk compared to fixed feed-in tariffs, if other factors remain constant, and thereby improves conventional financial performance risk metrics. In particular, this suggests that the recent energy policy change in Britain to move away from green certificates and into contracts-for-differences may have been ill-founded.

イギリスにおける電力自由化後の実態と課題

イギリスにおける電力自由化後の実態と課題

Have Technology Specific Measures for the UK Electricity Market Reform Gone Far Enough?

Have Technology Specific Measures for the UK Electricity Market Reform Gone Far Enough?

Modeling and analysis of renewable energy obligations and technology bandings in the UK electricity market

In the UK electricity market, generators are obliged to produce part of their electricity with renewable energy resources in accordance with the Renewable Obligation Order. Since 2009 technology banding has been added, meaning that different technologies are rewarded with a different number of certificates. We analyze these two different renewable obligation policies in a mathematical representation of an electricity market with random availabilities of renewable generation outputs and random electricity demand. We also present another, alternative, banding policy. We provide revenue adequate pricing schemes for the three obligation policies. We carry out a simulation study via sampling. A key finding is that the UK banding policy cannot guarantee that the original obligation target is met, hence potentially resulting in more pollution. Our alternative provides a way to make sure that the target is met while supporting less established technologies, but it comes with a significantly higher consumer price. Furthermore, as an undesirable side effect, we observe that a cost reduction in a technology with a high banding (namely offshore wind) leads to more CO2 emissions under the UK banding policy and to higher consumer prices under the alternative banding policy.

Variability of Behaviour in Electricity Load Profile Clustering; Who Does Things at the Same Time Each Day?

UK electricity market changes provide opportunities to alter households’ electricity usage patterns for the benefit of the overall electricity network. Work on clustering similar households has concentrated on daily load profiles and the variability in regular household behaviours has not been considered. Those households with most variability in regular activities may be the most receptive to incentives to change timing. Whether using the variability of regular behaviour allows the creation of more consistent groupings of households is investigated and compared with daily load profile clustering. 204 UK households are analysed to find repeating patterns (motifs). Variability in the time of the motif is used as the basis for clustering households. Different clustering algorithms are assessed by the consistency of the results. Findings show that variability of behaviour, using motifs, provides more consistent groupings of households across different clustering algorithms and allows for more efficient targeting of behaviour change interventions.

Modeling and Analysis of Renewable Energy Obligations and Technology Bandings in the UK Electricity Market

In the UK electricity market generators are obliged to produce a certain amount of their electricity with renewable energy resources in accordance with the Renewable Obligation Order. This obligation comes with an (indirect) subsidy rewarding firms with tradable green certificates for their renewable energy production. Until 2009 every unit production of renewable energy was rewarded with the same amount of certificates. Since 2009 a banding has been added to the Renewable Order, meaning that different technologies are rewarded with a different number of certificates. The obligation then shifted from one on production to one on certificates. This paper discusses and analyzes these two different renewable obligation policies in a mathematical framework. The policies are modeled into a two-stage electricity market investment model in which firms invest at the first stage and produce at the second stage. Since banding may result in an outcome where the original obligation target is not satisfied, hence potentially resulting in more pollution, we present an alternative banding policy. We provide revenue adequate pricing schemes for the three obligation policies in order to guarantee that the regulator can cover the payments to firms owning certificates with the mark-ups paid by consumers. Then we move to a stochastic framework where the two main sources of uncertainty are the availability of renewable generation output and the stochastic nature of electricity demand. The stochastic framework is used to carry out a simulation study via sampling on a small network representing the UK market. We analyze the effects of the three obligation policies; a key finding is that, indeed, the UK banding policy cannot guarantee that the original obligation target is met. Our alternative provides a way to make sure that the target is met while supporting less established technologies, but it comes with a significantly higher consumer price. Furthermore, we observe a concerning side effect of banding policies, as a cost reduction in a technology with a high banding (namely offshore wind) leads to more CO2 emissions under the UK banding policy and to higher consumer prices under the alternative banding policy.

Report: Uk Electricity Market Reform (Emr) — What's in Place, What Still Has to Be Done for the Biggest Changes in the Electricity Market?

Report: Uk Electricity Market Reform (Emr) — What's in Place, What Still Has to Be Done for the Biggest Changes in the Electricity Market?

An Agent-Based Simulation of Smart Metering Technology Adoption

Based on the classic behavioural theory the “Theory of Planned Behaviour,” the authors have developed an agent-based model to simulate the diffusion of smart metering technology in the electricity market. The authors simulate the emergent adoption of smart metering technology under different management strategies and economic regulations. Their research results show that in terms of boosting the take-off of smart meters in the UK electricity market, choosing the initial users on a random and geographically dispersed basis and encouraging meter competition between energy suppliers can be two effective strategies. The authors also observe an “S-curve” diffusion of smart metering technology and a “lock-in” effect in the model. The research results provide users with insights as to effective policies and strategies for the roll-out of smart meters in the UK electricity market.

Demand Side Response: Challenges & Opportunities for providing equilibrium in the UK electricity market

UK Electricity thermal generation is creaking at the seams. A large amount of coal and oil fuelled generation has and is retiring due to age and environmental legislation including the European Union Large Combustion Plant Directive. Furthermore, challenging economics for gas fuelled generation has resulted in few new power plants being built and in fact many being mothballed, including units only two years old, until the business case for their operation becomes more favourable. The resulting decline in capacity and generator availability has lead to very tight capacity margins – the difference between electricity supply and demand levels, which can make National Grid's role – the UK's Transmission System Operator (TSO) – in matching generation and demand quite challenging. Indeed, spare electricity power production in the electricity system is predicted to fall to only 2% by 2015, increasing the risks of blackouts across the UK, should an unforeseen operational issue arise or the UK experience a cold winter. Demand Side Response (DSR) could provide an important contribution to managing security of supply and cutting energy consumption. It offers a cheaper and greener alternative to building new generating capacity and could make a meaningful contribution towards security of supply. This study provides a brief overview of the recent developments on the growing DSR market in the UK. Fast acting, clean flexible load is a unique asset which currently is virtually untapped in the UK. With the emerging regulatory support in the UK and across Europe, this is a valuable commodity which can potentially meet the pressures of peak electricity demand while giving businesses security over their power supply needs. The role of the Demand Response Aggregator (DRA) using an Automated Demand Response (ADR) platform to draw on flexible loads across many sites in a coordinated and automated fashion has been discussed. Furthermore, the relationship between the DRA and ADR Technology Solution Provider in establishing a new business to provide aggregated demand response (load adjustment; down and up) as a service to distribution network operators, TSOs, and wholesale Traders have been explored.

The Analysis of Real Data Using a Stochastic Dynamical System Able to Model Spiky Prices

In this paper we use filtering and maximum likelihood methods to solve a calibration problem for a stochastic dynamical system used to model spiky asset prices. The data used in the calibration problem are the observations at discrete times of the asset price. The model considered has been introduced by V.A. Kholodnyi in [1,2] and describes spiky as-set prices as the product of two independent stochastic processes: the spike process and the process that represents the asset prices in absence of spikes. A Markov chain is used to regulate the transitions between presence and absence of spikes. As suggested in [3] in a different context the calibration problem for this model is translated in a maximum likelihood problem with the likelihood function defined through the solution of a filtering problem. The estimated values of the model parameters are the coordinates of a constrained maximizer of the likelihood function. Furthermore, given the calibrated model, we develop a sort of tracking procedure able to forecast forward asset prices. Numerical examples using synthetic and real data of the solution of the calibration problem and of the performance of the tracking procedure are presented. The real data studied are electric power price data taken from the UK electricity market in the years 2004-2009. After calibrating the model using the spot prices, the forward prices forecasted with the tracking procedure and the observed forward prices are compared. This comparison can be seen as a way to validate the model, the formulation and the solution of the calibration problem and the forecasting procedure. The result of the comparison is satisfactory. In the website: http://www.econ.univpm.it/recchioni/finance/w10 some auxiliary material including animations that helps the understanding of this paper is shown. A more general reference to the work of the authors and of their coauthors in mathematical finance is the website: http://www.econ.univpm.it/ recchioni/finance.

UK Electricity Market Reform—revolution or much ado about nothing?

The UK Government has published a White paper on Electricity Market Reform, which precedes legislation with a declared aim of delivering secure, clean and decarbonised electricity supply. It introduces interventionist methods aiming to promote a nuclear power construction programme, a streamlined renewables programmes and a system to ensure that generation capacity is built to cope with variability in electricity output. However, the policies announced to date are likely to fail in delivering the promised nuclear programme and the system of ‘feed-in tariffs’ announced for renewables is stunted and made less efficient by a desire to integrate it with the prevailing electricity market arrangements. The effect of the changes in the White Paper is likely to be incremental rather than revolutionary.

Theoretical and practical foundations of large-scale agent-based micro-storage in the smart grid

In this paper, we present a novel decentralised management technique that allows electricity micro-storage devices, deployed within individual homes as part of a smart electricity grid, to converge to profitable and efficient behaviours. Specifically, we propose the use of software agents, residing on the users' smart meters, to automate and optimise the charging cycle of micro-storage devices in the home to minimise its costs, and we present a study of both the theoretical underpinnings and the implications of a practical solution, of using software agents for such micro-storage management. First, by formalising the strategic choice each agent makes in deciding when to charge its battery, we develop a game-theoretic framework within which we can analyse the competitive equilibria of an electricity grid populated by such agents and hence predict the best consumption profile for that population given their battery properties and individual load profiles. Our framework also allows us to compute theoretical bounds on the amount of storage that will be adopted by the population. Second, to analyse the practical implications of micro-storage deployments in the grid, we present a novel algorithm that each agent can use to optimise its battery storage profile in order to minimise its owner's costs. This algorithm uses a learning strategy that allows it to adapt as the price of electricity changes in real-time, and we show that the adoption of these strategies results in the system converging to the theoretical equilibria. Finally, we empirically evaluate the adoption of our micro-storage management technique within a complex setting, based on the UK electricity market, where agents may have widely varying load profiles, battery types, and learning rates. In this case, our approach yields savings of up to 14% in energy cost for an average consumer using a storage device with a capacity of less than 4.5 kWh and up to a 7% reduction in carbon emissions resulting from electricity generation (with only domestic consumers adopting micro-storage and, commercial and industrial consumers not changing their demand). Moreover, corroborating our theoretical bound, an equilibrium is shown to exist where no more than 48% of households would wish to own storage devices and where social welfare would also be improved (yielding overall annual savings of nearly £1.5B).

The case for a new capacity mechanism in the UK electricity market—Lessons from Australia and New Zealand

The UK Government plans a capacity mechanism to ensure sufficient reserves as the share of intermittent generation increases. This article reviews the use of last resort capacity mechanisms in two other energy-only markets, Australia and New Zealand.The Australian National Electricity Market has infrequent price spikes up to A$12,500 (£7800)/MWh. Option contracts have supported significant investment in peak capacity. The system operator also has an ability to contract reserve up to 9 months before projected shortfalls. Reserve has been contracted on two occasions but never dispatched.The New Zealand electricity market includes a reserve energy scheme which allows the system operator to contract and dispatch reserve capacity. One plant has been contracted under the scheme. The plant is currently offered into the market at NZ$5000 (£2300)/MWh.In both markets there have been concerns that reserve schemes could reduce the frequency of high prices and damage price signals for peak investment. Following a Ministerial review in 2009 the New Zealand scheme is being closed down and the plant is for sale. The Australian scheme is to be closed down in 2013. This experience raises concerns about the possible impact of a new capacity mechanism in Great Britain.

Conditions for aggregation of CHP plants in the UK electricity market and exploration of plant size

Combined heat and power (CHP) plants with thermal stores may be suitable for sustainable energy production and the accommodation of fluctuating renewable energy sources. At the moment, in the UK, only a few CHP plants have thermal stores. Previous research has shown that thermal stores can improve the economics of CHP plants in the UK under the current market conditions. However, currently, it is only beneficial for CHP plants to sell their electricity to a third party, a Licensed Electricity Supplier, rather than to sell it directly to the power exchange market at prices which are much higher. If CHP plants aggregate, direct access to the power exchange market can become economically viable hence there is the possibility that thermal stores could further improve the economics of CHP plants under an aggregated electricity dispatch. This work firstly explains the conditions under which such plants could aggregate and act as a large power plant in the UK market, and secondly explores the most economic-size of gas engine and thermal store, in the case of aggregation, using energyPRO software and Excel spreadsheets. The work suggests that direct access to the power exchange market can improve the economics of the CHP plants. The highest Net Present Value (NPV), without heat dissipation, for a CHP plant exporting its electricity to the grid for a community heating load of 20 GW h, is more than £5 m, and is obtained for a 6 MW engine with a 28.2 MW h (900 m 3) thermal store. The research suggests that such high electricity prices could make even larger plants more profitable than that; however, this can happen only if some of the produced heat is dissipated.

Report: Wec Seminar on UK Electricity Market Reform 20th January 2011

Report: Wec Seminar on UK Electricity Market Reform 20^th January 2011

Grid-connected renewables, storage and the UK electricity market

This article is mainly a counterpoint to an article by Swift-Hook in the journal of Renewable Energy titled “Grid-connected intermittent renewables are the last to be stored”. It also describes the four main distinct UK markets where electrical energy and services are traded, in order to provide a context for the discussion of renewable energy and energy storage in the UK electricity system. In Swift-Hook’s article it was argued that “grid-connected intermittent renewables like wind energy will never be stored unless nothing else is available” and that “storage is counter-productive for fuel saving”. We, however, find evidence that “grid-connected intermittent renewables” have been, and will continue to be stored when it suits the “UK market” to do so. Furthermore, Swift-Hook’s article neglects the potential wider benefits that storage offers to UK energy policy’s goals, in terms of reduced emissions (when used in conjunction with renewables) and enhanced security of supply.

Creating Personalised Energy Plans: From Groups to Individuals Using Fuzzy C Means Clustering

Changes in the UK electricity market mean that domestic users will be required to modify their usage behaviour in accordance with energy efficiency targets. Clustering allows usage data, collected at the household level, to be clustered into groups and assigned a stereotypical profile which may be used to provide individually tailored energy plans. Fuzzy C Means extends previous work based around crisp K means clustering by allowing a household to be a member of multiple customer profile groups to different degrees, thus providing the opportunity to make personalised offers to the household dependent on their degree of membership of each group. In addition, feedback can be provided on how household’s changing behaviour is moving them towards more ”green” or cost effective stereotypical usage

Do consumers switch to the best supplier?

This paper demonstrates that the ability of consumers to choose the best alternative supplier is limited even in a relatively simple and transparent market. Across two independent datasets from the UK electricity market we find, on aggregate, that those consumers switching exclusively for price reasons appropriated less than a half of the gains available. While such outcomes can be explained by high search costs, the observation that at least 17% of consumers actually reduced their surplus as a result of switching cannot. We rule out an explanation of incorrect demand prediction, and test for others including mis-selling.

Price transmission in the UK electricity market: Was NETA beneficial?

This paper explores the relationship between domestic retail electricity prices in Great Britain and their determinants in the context of the New Electricity Trading Arrangements (NETA) introduced in 2001. We employ a consistent comparison of wholesale power price series before and after NETA, alongside a difference-in-differences analysis based on using Scotland as a control. Despite NETA's stated intention of reducing wholesale and thereby retail prices, we conclude that its net effect, alongside other developments, instead merely rearranged where money was made in the system.