UK Electricity Market Research Articles

The influences of non-optimal investments on the scale-up of smart local energy systems in the UK electricity market

Rapid and deep decarbonisation of electricity systems is critical in many pathways to meet net-zero emissions by 2050. Smart local energy systems (SLES) have been touted as key for both a rapid scale-up of renewable electricity and flexibility for stability in decarbonised electricity systems. A novel agent-based model – incorporating local investor and governance agents, improved temporal resolution, and demand-side flexibility – was used to investigate strategic decision making in the scale-up of SLES. From the perspective of this model, key modelling insights include: SLES investors, initially supported by local governments, can successfully boost the uptake of renewable energy up to 80% of total generation; SLES scale-up significantly erodes the market share and profitability of incumbent utilities, however national level agents are still key for capital-intensive low carbon plants; Demand-side response facilitates balancing electricity supply and demand, but it can result in non-optimal policy agents postponing required incentives for heterogeneous investor agents to build new low carbon plants; National carbon prices (in conjunction with local SLES and technology support mechanisms) are needed to maintain overall system stability. Therefore, understanding the critical role of non-optimal investor decision making is key to fully understand the drivers and implications of a rapid scale-up of SLES.

Daily peak electrical load forecasting with a multi-resolution approach

In the context of smart grids and load balancing, daily peak load forecasting has become a critical activity for stakeholders in the energy industry. An understanding of peak magnitude and timing is paramount for the implementation of smart grid strategies such as peak shaving. The modelling approach proposed in this paper leverages high-resolution and low-resolution information to forecast daily peak demand size and timing. The resulting multi-resolution modelling framework can be adapted to different model classes. The key contributions of this paper are (a) a general and formal introduction to the multi-resolution modelling approach, (b) a discussion of modelling approaches at different resolutions implemented via generalised additive models and neural networks, and (c) experimental results on real data from the UK electricity market. The results confirm that the predictive performance of the proposed modelling approach is competitive with that of low- and high-resolution alternatives.

A methodology for techno-economic evaluation of asymmetric energy storage systems: A nuclear energy case study

This paper discusses a novel methodology for the analysis of energy storage system. This methodology combines engineering and economic modelling to assess the relative economic performance of plant designs within a simulated UK electricity market. It presents a case study that explores whether a nuclear power plant can be combined with a liquid air energy storage plant to allow the resultant hybrid plant to provide a load-following electricity supply. The approach adopted is distinct from much of the work on conventional load following nuclear power plant operations, as in our case the underlying nuclear energy production does not vary. The methodology expands the previous literature by performing market-led system optimisation to best design the output profile of the hybrid plant to improve economic performance in the UK electricity grid. Whilst this combined modelling approach has been demonstrated in the context of a specific plant design, this methodology might be applied to any asymmetric energy storage system to assess its economic viability. This work is both contrasting and complementary to the levelized cost of storage approach. Rather than providing the price at which energy must be sold to make a storage system economically viable, this approach considers how volatile the electricity spot market would have to become to make such a system profitable. The ability to explore different market conditions is a major omission from the existing literature on energy storage systems.

Measuring the impact of electricity market reform in a Chinese Context

This paper draws on international experience to examine how the ongoing power sector reform (PSR) in China since 2015 should be measured and assessed. We proceed by reviewing some relevant international reform experience and then applying this to the Chinese context. Thus we focus on some of the extensive previous literature which has documented reforms in cross-country and in single country studies. We pay particular attention to the European Union (EU) single electricity market, which is the largest integrated electricity market in the world. We also look at a social cost benefit analyses of UK electricity market reforms and how these might applied in a given Chinese province. We go on to examine the actual price impact evidence from two leading provinces – Guangdong and Zhejiang – on the overall price effect and on exactly how those price effects have been achieved. We then offer some insights from the extensive regulatory reporting by leading regulators on market performance that is relevant to PSR in China based on excellent annual reporting from the UK, Australia and the US.

The entry and exit game in the electricity markets: A mean-field game approach

<p style='text-indent:20px;'>We develop a model for the industry dynamics in the electricity market, based on mean-field games of optimal stopping. In our model, there are two types of agents: the renewable producers and the conventional producers. The renewable producers choose the optimal moment to build new renewable plants, and the conventional producers choose the optimal moment to exit the market. The agents interact through the market price, determined by matching the aggregate supply of the two types of producers with an exogenous demand function. Using a relaxed formulation of optimal stopping mean-field games, we prove the existence of a Nash equilibrium and the uniqueness of the equilibrium price process. An empirical example, inspired by the UK electricity market is presented. The example shows that while renewable subsidies clearly lead to higher renewable penetration, this may entail a cost to the consumer in terms of higher peakload prices. In order to avoid rising prices, the renewable subsidies must be combined with mechanisms ensuring that sufficient conventional capacity remains in place to meet the energy demand during peak periods.</p>

A techno-economic assessment of battery business models in the UK electricity market

The UK's transition to a zero-carbon economy is inevitably leading to an electricity grid with a high penetration of intermittent renewable energy generation, resulting in the need to install grid-scale energy storage systems at an accelerating rate. This study has taken the perspective of a business owner to assess the profitability of deploying battery technologies in the UK electricity market by analysing arbitrage in electricity markets, capacity market auctions, and ancillary services (frequency response and reserve). Additional work was conducted for integrating battery arbitrage cycling with solar and wind generation, comparing the utilisation of a linear programming model against a simplistic threshold cycling model. An overall economic assessment of value streams found that the lowest payback periods for premium ancillary services were 3.3 years (advanced lead-acid battery providing fast reserve) and 6.6 years (lithium-ion battery providing frequency response). Moreover, this research has demonstrated promising returns on investment for stacking short-term operating reserve with arbitrage in the balancing market. In the near future, battery systems will likely attain accelerated deployment due to reforms in ancillary service structures, cost reductions in battery technologies, greater price volatility in the balancing market, and effective policy incentives introduced by the UK government.

Integrated techno-economic assessment of Liquid Air Energy Storage (LAES) under off-design conditions: Links between provision of market services and thermodynamic performance

This paper deals with Liquid Air Energy Storage (LAES) – one of the most promising thermo-mechanical technologies with the potential to provide bulk energy storage functionalities. More specifically, an integrated technical and economic assessment of the performance of LAES when providing multiple energy and frequency control ancillary services is carried out. To this end, an off-design thermodynamic model of LAES was developed and validated against experimental data from the literature to allow understanding the links between the specific requirements of the market services to provide and the performance of each component of the LAES plant, and from here the performance of whole LAES process. The model was then applied to assess how a stand-alone LAES plant performs when providing three specific assets in the UK electricity market: arbitrage, short term operating reserve (STOR), and fast reserve (FR). The results obtained clearly demonstrate that (a) a strong link between type of service and LAES off-design conditions exists and cannot be neglected; (b) roundtrip efficiency and liquid air consumption can vary by up to 30% during off-design operation, causing some 10 k£/MW of missed revenue; (c) the effect of off-design conditions is unevenly distributed across LAES components, with low-pressure turbines affected the most; (d) a suitable regulation strategy can alleviate but not prevent off-design performance variations, improving roundtrip efficiency by up to 4 percentage points. The modelling developed is thus essential for a realistic assessment of the value and constraints for LAES to participate in electricity markets and support low-carbon power system operation and development.

Operating Elements of UK Electricity Contract Market and Its Enlightenment to China

The United Kingdom is the birthplace of the world industrial revolution. Its marketization of the power industry has been going on for more than 20 years. It is a developed country with a relatively mature power market system. The UK electricity market reform has experienced the Power P00L model, the New Electricity Trading Arrangements model, and the British Electricity Trading and Transmission Arrangements model. Since the NETA model, the UK has formed a power production-transaction-regulatory system centered on bilateral transactions. China is undergoing market-oriented reform of the power system. In order to break the monopoly, the main contents include changes in the development concept of the traditional power industry, the establishment of a new mechanism for direct trading between power generation enterprises and users, the establishment of an independent and reasonable transmission and distribution mechanism, and the opening of private capital into the electricity market, and so on. This paper introduces the reform process of the UK electricity contract market, summarizes the substantive elements and mechanism elements, lists the operation elements of the current UK electricity contract market, and analyses the structure of the UK electricity market and the bilateral electricity trading mechanism deeply. On this basis, some suggestions are put forward to further improve the construction of China’s electricity market.

UK Electricity Market Reform and the Energy Transition:Emerging Lessons

The 2013 Electricity Market Reform (EMR) was a response to the twin problems of securing efficient finance for a new generation of low carbon investments, and delivering reliability along with a growing share of renewables in its energy-only market. Four EMR instruments combined to revolutionize the sector; stimulating unprecedented technological and structural change. Competitive auctions for both firm capacity and renewable energy have seen prices far lower than predicted and the entry of unexpected new technologies. A carbon price floor displaced coal, whose share fell from 46% in 1995 to 7% in 2017, halving CO2. Renewables grew from under 4% in 2008 to 22% by 2017, projected at 30+% by 2020 despite a political ban on onshore wind. Neither the technological nor regulatory transitions are complete, and the results to date highlight other challenges, notably to transmission pricing and locational signals. EMR is a step forwards, not backwards; but it is not the end of the stor

The Financial Benefits of Various Catastrophic Failure Prevention Strategies in a Wind Farm: Two market studies (UK-Spain)

Operation of wind farms is driven by the overall aim of minimising costs while maximising energy sales. However, in certain circumstances investments are required to guarantee safe operation and survival of an asset. In this paper, we discuss the merits of various catastrophic failure prevention strategies in a Spanish wind farm. The wind farm operator was required to replace blades in two phases: temporary and final repair. We analyse the power performance of the turbine in the different states and investigate four scenarios with different timing of temporary and final repair during one year. The financial consequences of the scenarios are compared with a baseline by using a discounted cash flow analysis that considers the wholesale electricity market selling prices and interest rates. A comparison with the UK electricity market is conducted to highlight differences in the rate of return in the two countries.

Branding Instead of Product Innovation: A Study on the Brand Personalities of the UK's Electricity Market

This study extends understanding of and demonstrates the importance of corporate branding in the energy sector. We analyse the relationship between branding and consumer switching behaviour among the UK’s Big Six electricity providers. Since privatisation companies have competed against each other, but to the consumer they often appear to have very similar product offerings; firms also face criticism from consumer groups regarding confusing and difficult to compare pricing schemes. This study examines the use of corporate branding to enhance differentiation and specifically examines the influence of brand consistency and brand personality on the retention of customers. Consumers, who find it difficult to compare tariffs, may be influenced by more demonstrable factors like branding. We demonstrate the importance of longitudinal brand consistency, as well as the personality dimension Excitement, which when communicated strongly has the greatest influence on customer retention levels. This work contributes to branding theory, demonstrating that brand personality does differentiate otherwise homogeneous (and low-contact) services. Managerial implications are presented for brands seeking to improve consumer retention.

Cloud energy storage for grid scale applications in the UK

In this paper, the UK's electricity market and battery technologies were researched to determine the economics of aggregating domestic batteries for grid-scale services. A feasibility study was conducted under three scenarios in order to estimate the value of Advanced Lead-Acid (ALA) and Lithium-Ion (LI) batteries for domestic households in the UK. A profit optimization model was built using historical market data, and technical parameters of the batteries. An aggregated system of 5000 batteries was simulated and used to compare and stack value streams of seven different grid-scale services in the UK, including energy arbitrage, reserve and frequency regulation services.The results showed that using a battery system for domestic services is currently not economically viable, however grid-scale provision of dynamic frequency response and fast reserve services yield sufficient annual revenue to compensate for these losses. The annual profit margin per household obtained was £ 532/692 for ALA and LI batteries respectively, allowing a shared margin of £ 230–300 after accounting for household costs.The promotion of an aggregated storage system is hindered by current regulatory barriers in the UK, such as a double payment structure for storage operators, lack of subsidy and lack of separate definition for storage devices.

Pricing decisions and market power in the UK electricity market: A VECM approach

This paper examines the influence of market power in the formation of retail and wholesale electricity prices in the UK over 1998–2012 on the basis of Vector Error Correction model (VECM). Market power is measured as the influence of the market share of the Big Six in a dynamic demand and supply VECM. The findings indicate that market power of the Big Six in the wholesale industry has a significant and large positive influence on the wholesale mark-up in the short-run. The long-run estimates support the arguments about ‘revenue rebalancing’ resulting from vertical integration. That is, low market power (and hence low revenues) in the wholesale industry leads to higher prices (hence higher revenues) in the retail industry. These findings are in contrast to the CMA's finding that no market power is exercised in the wholesale industry. Retail electricity prices are affected directly by both the wholesale and retail market concentration ratios in the long-run rather than indirectly through the wholesale mark-up. Overall, the findings in this paper provide support for the view that the UK electricity market exhibits significant anti-competitive conduct in both the retail and wholesale segments.

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-CO $$_{2}$$ modeling framework that is able to simulate interactions of the energy-only market with different forms of national policy measures. We set up a two sector model where players can invest into various types of generation technologies including renewables, nuclear power 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 CO $$_{2}$$ transport and CO $$_{2}$$ storage including the option for CO $$_{2}$$ enhanced oil recovery (CO $$_{2}$$ -EOR). The players maximize their expected profits based on variable, fixed and investment costs as well as endogenous prices of electricity, CO $$_{2}$$ abatement cost and other incentives, subject to technical and environmental constraints. Demand is inelastic and represented via type hours. The model framework allows for regional disaggregation and features simplified electricity and CO $$_{2}$$ pipeline networks. It is balanced via a market clearing for the electricity as well as CO $$_{2}$$ market. The equilibrium solution is subject to constraints on CO $$_{2}$$ 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.

Comparison of ARIMA and ANN Models Used in Electricity Price Forecasting for Power Market

In power market, electricity price forecasting provides significant information which can help the electricity market participants to prepare corresponding bidding strategies to maximize their profits. This paper introduces the models of autoregressive integrated moving average (ARIMA) and artificial neural network (ANN) which are applied to the price forecasts for up to 3 steps 8 weeks ahead in the UK electricity market. The half hourly data of historical prices are obtained from UK Reference Price Data from March 22nd to July 14th 2010 and the predictions are derived from a sliding training window with a length of 8 weeks. The ARIMA with various AR and MA orders and the ANN with different numbers of delays and neurons have been established and compared in terms of the root mean square errors (RMSEs) of price forecasts. The experimental results illustrate that the ARIMA (4,1,2) model gives greater improvement over persistence than the ANN (20 neurons, 4 delays) model.

Finding the Creatures of Habit; Clustering Households Based on Their Flexibility in Using Electricity

Changes in the UK electricity market, particularly with the roll out of smart meters, will provide greatly increased opportunities for initiatives intended to change households’ electricity usage patterns for the benefit of the overall system. Users show differences in their regular behaviours and clustering households into similar groupings based on this variability provides for efficient targeting of initiatives. Those people who are stuck into a regular pattern of activity may be the least receptive to an initiative to change behaviour. A sample of 180 households from the UK are clustered into four groups as an initial test of the concept and useful, actionable groupings are found.

A perspective on the rise and fall of the energy regulator in Britain

The process of Electricity Market Reform instigated in 2010 is leading to fundamental reforms to the UK electricity market. Despite its previous strong presence in the policy process, the British energy market regulator, OFGEM, appears to have only a minimal role in the implementation of these reforms. This article reviews the history of OFGEM, including expectations for the agency when it was established and how it evolved over time. From this perspective, several factors that might have contributed to OFGEM's apparent marginalisation are identified. These include perceptions of a poor track record, a tendency of governments to bypass the regulator for decisions deemed important, and the subordination of economic issues to climate-change priorities.

Comparison of two energy storage options for optimum balancing of wind farm power outputs

This study presents a simple methodology for analysing and optimising combined wind generation and storage schemes, using both technical and economic performance criteria. The study provides a detailed analysis of the performance of two storage options for such a scheme: pumped storage hydro (PSH) and battery energy storage systems (BESSs). The analysis is carried out using recorded data from an actual UK wind farm (WF), information on the UK electricity market, and currently available PSH and BESS storage technologies to estimate and compare performance of the considered wind generation–storage schemes over the entire lifetime. The results show that an optimised generation–storage scheme can significantly reduce the variability of power outputs and increase the profitability of the WF. It is further shown that optimised PSH-based schemes have better economic performance than BESS schemes, as the latter are limited by the short discharge times. The approach developed in this study could be used during the initial design and planning stages, in order to select and optimise the type and size of energy storage for a combined wind generation–storage scheme.

Novel Power Smoothing and Generation Scheduling Strategies for a Hybrid Wind and Marine Current Turbine System

Grid integration of wind energy is a major challenge as grid codes require electricity generation units to schedule their generation ahead of the trading period and to limit the power fluctuations. This paper proposes novel strategies for mitigating the effects of wind intermittency by developing hybrid off-shore wind and marine current turbines. Unlike the random nature of wind, marine currents have slow cyclic variations and are highly predictable. The proposed methods involve optimal sizing strategy for the hybrid system and rely on the resource predictions. Prediction Intervals for wind speed forecasts using Bootstrapped Artificial Neural Networks have been developed and validated. Marine current speeds have been mathematically modeled using the Harmonic Analysis Method. Subsequently, novel power fluctuation mitigation and generation scheduling strategies using minimum energy storage have been designed based on the UK electricity market regulations and the predicted wind and current speeds. The results demonstrate the effectiveness of the proposed methods which ensure successful mitigation of power fluctuations, reliable dispatch scheduling of renewable generation, and significant cost saving potential.

A Short-Term Electricity Price Forecasting Scheme for Power Market

Electricity price forecasting has become an important aspect of promoting competition and safeguarding the interests of participants in electricity market. As market participants, both producers and consumers intent to contribute more efforts on developing appropriate price forecasting scheme to maximize their profits. This paper introduces a time series method developed by Box-Jenkins that applies autoregressive integrated moving average (ARIMA) model to address a best-fitted time-domain model based on a time series of historical price data. Using the model’s parameters determined from the stationarized time series of prices, the price forecasts in UK electricity market for 1 step ahead are estimated in the next day and the next week. The most suitable models are selected for them separately after comparing their prediction outcomes. The data of historical prices are obtained from UK three-month Reference Price Data from April 1st to July7th 2010.