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As the penetration of renewable energy sources into a power system increases, the significance of precise short-term forecasts for wind power generation becomes paramount. However, the erratic and non-periodic nature of wind poses challenges in accurately predicting the output. This paper presents a comprehensive investigation into forecasting wind power generation for the following day, using three machine learning models: long short-term memory (LSTM), convolutional neural network-bidirectional LSTM (CNN-biLSTM), and light gradient boosting machine (LGBM). In addition, this paper proposes a method to improve the prediction performance of LGBM by separating data according to the distribution of features, and training and testing each separated dataset with a distinct model. This study includes a comparative analysis of the performance of the proposed models in predicting wind turbine output, offering valuable insights into their respective efficiencies. The results of this investigation were analyzed for two geographically distinct wind farms (Korea and the UK). The findings of this study are expected to facilitate the selection of efficient prediction models within the forecast accuracy auxiliary service market and assist grid operators in ensuring reliable power supply for the grid. [ABSTRACT FROM AUTHOR]

Given the fundamental role of renewable energy assets in achieving global temperature control targets, new energy management methods are required to efficiently match intermittent renewable generation and demand. Based on analysing various designed cases, this paper explores a number of heuristics for a smart battery scheduling algorithm that efficiently matches available power supply and demand. The core of improvement of the proposed smart battery scheduling algorithm is exploiting future knowledge, which can be realized by current state-of-the-art forecasting techniques, to effectively store and trade energy. The performance of the developed heuristic battery scheduling algorithm using forecast data of demands, generation, and energy prices is compared to a heuristic baseline algorithm, where decisions are made solely on the current state of the battery, demand, and generation. The battery scheduling algorithms are tested using real data from two large-scale smart energy trials in the UK, in addition to various types and levels of simulated uncertainty in forecasts. The results show that when using a battery to store generated energy, on average, the newly proposed algorithm outperforms the baseline algorithm, obtaining up to 20–60% more profit for the prosumer from their energy assets, in cases where the battery is optimally sized and high-quality forecasts are available. Crucially, the proposed algorithm generates greater profit than the baseline method even with large uncertainty on the forecast, showing the robustness of the proposed solution. On average, only 2–12% of profit is lost on generation and demand uncertainty compared to perfect forecasts. Furthermore, the performance of the proposed algorithm increases as the uncertainty decreases, showing great promise for the algorithm as the quality of forecasting keeps improving. [ABSTRACT FROM AUTHOR]

This paper provides a high-accuracy assessment of domestic demand-side management (DSM) approach in the context of distributed renewable energy sources (RES). To determine the potential of domestic DSM for households, a microgrid model of a typical UK residential estate was developed to simulate the impact of RES. The microgrid model comprises 15 UK households with appropriate allocation of washing machines, tumble dryers and dishwashers in accordance with the statistical data. In order to obtain a high-accuracy result, the power consumption of the microgrid model utilises real historical high-resolution data of household energy consumption and RES generation. Thereafter, 40% of distributed wind and solar energy is implemented in the model to produce two individual scenarios. The operation of the white appliances in the model is controlled using a domestic DSM based on a load shifting algorithm. The primary criterion of the DSM considered in this paper is the reduction in energy feedback to the grid in order to decrease the utilisation of the grid and to reduce the transmission losses. The results obtained from the model simulation are compared to the baseline model and discussed with respect to the possible benefits of implementation of domestic DSM under the impact of RES. It has been shown that the self-consumption ratio of the microgrid operating under the DSM is increased by 3% for both scenarios. The model analysis provides highly realistic results which can be used for efficiency assessment of various load shifting methods. [ABSTRACT FROM AUTHOR]

This paper discusses the role of Tidal Power in the UK in fulfilling the UK's requirements for reducing greenhouse gas emissions. Generating electricity from tidal range of the Severn Estuary has the potential to generate some 5% of UK electricity from a renewable indigenous resource. The paper focuses primarily on the proposed Severn Barrage considering potential benefits, conditions for sustainable development, energy policy context and compliance with environment legislation. UK tidal resource is reviewed: stream resource (that is KE contained in fast-flowing tidal currents), and tidal range resource (that refers to gravitation potential energy). The top tidal range and tidal stream sites in the UK with the resource (in TWh/year) are indicated. A feasibility study for Tidal Range development in the Mersey Estuary is also summarised and other schemes including the Loughor Estuary (Wales), Duddon Estuary (located on the Cumbrian coast) and the Thames Estuary proposals are reported. Also given is a strategic overview of the Severn Estuary resource, electric output and characteristics, carbon emissions (carbon payback and carbon reduction potential) and physical implications of a barrage. [ABSTRACT FROM AUTHOR]

This paper investigates the future role of cross-border electricity flow between Great Britain (GB) and its neighbors until 2030, considering high deployment of renewable energy sources (e.g., wind, solar, and biomass), enhanced interconnection capacity, and a partly electrified heating sector. It was assumed that two cross-border interconnectors links will connect GB's power system to its neighbors: (1) a one-way interconnector (IC1) that imports electricity to GB, and (2) a two-way one (IC2) between France and GB. The IC2 was allowed to transfer electricity from a cheaper power system to a more expensive one. The results show that at a fixed CO2 price, a change in power imported via IC1 will affect the power dispatch of the CO2 emitting power plants and biomass-fired power plants, and electricity trade via IC1 and IC2. At IC1 importing of £60/MWh, by raising the CO2 price from 60 to £70/ton, the share of CCGT power plants will reduce by 75%, and the power imported via IC1 link will face 19-times growth. With a constant IC1 import price, raising the CO2 tax will reduce the total quantity of electricity being exported to France via IC2. Moreover, increasing the CO2 tax will increase the emissions cost of gas and coal-fired generators, and the power required to meet the demand will be imported via IC1. With the IC1 electricity price set to £20/MWh and the CO2 tax set to £50/ton, there may be 595 periods out of 17,520 in which GB will be used as an electricity trade corridor. GB's total CO2 emissions should drop as the CO2 tax increases. [ABSTRACT FROM AUTHOR]

We introduce the BDA dynamics and explore the associated applications in renewable energy sector with a focus on data-driven innovation. Our study draws on the exponential growth of renewable energy initiatives over the last decades and on the paucity of literature to illustrate the use of BDA in the energy industry. We conduct a qualitative field study in the UK with stakeholder interviews and analyse our results using thematic analysis. Our findings indicate that no matter if the importance of the energy sector for 'people's well-being, industrial competitiveness, and societal advancement, old fashioned approaches to analytics for organisational processes are currently applied widely within the energy sector. These are triggered by resistance to change and insufficient organisational knowledge about BDA, hindering innovation opportunities. Furthermore, for energy organisations to integrate BDA approaches, they need to deal with challenges such as training employees on BDA and the associated costs. Overall, our study provides insights from practitioners about adopting BDA innovations in the renewable energy sector to inform decision-makers and provide recommendations for future research. [ABSTRACT FROM AUTHOR]

In the context of challenging targets for renewable energy generation, this paper draws out social implications of moves towards low carbon energy systems. As renewable energy develops as a heterogeneous category, many potential forms of social relation between ‘publics’ and technologies are emerging. Utilising perspectives from science and technology studies, we outline five modes in which renewable energy has been implemented in the UK and how these involve different configurations of technology and social organisation. We argue that a multiplicity of roles for ‘the public’ are implicated across this increasingly complex landscape, cutting across established categories and raising questions of meaning, differentiation, interrelation and access. Policy assumptions and conceptions are questioned, highlighting that dominant characterisations of public roles have been part of a concentration on particular socio-technical pathways to the exclusion of others. [ABSTRACT FROM AUTHOR]

Renewable energy sources (RES) are gradually becoming one of the key elements in the process of achieving energy efficiency worldwide. This trend can be observed in many developed Western economies—for example, in the United States, as well as in the United Kingdom. Hence, the role of innovative policies for promoting energy efficiency is becoming crucial in transition to the post-carbon economy. The shift to the carbon-free future make all actors to face forgoing commitments Nevertheless, customers and residential households are the first and the most important players in the pursuit of the energy-efficient future. Without them, carbon-free economy based on RES would never take the shape as envisaged. Our paper focuses on the innovative strategies and policies studying the effect and the scope of RES penetration into the households. We employ and empirical analysis of the effects from using RES in households using an example of the residential households in the northwest region of the United Kingdom (UK) with and without solar photovoltaic (PV) panels and electric vehicles (EV). We analyse the four scenarios that are aimed at analysing the system dynamics and providing differentiation between systems in terms of the varying values of the gross demand, tariffs, metered import, and the total revenue. Our results demonstrate that the solar PV leads to the transfer of costs and wealth regardless of the ownership of PV and EVs. Solar energy generation reduces the share of UK solar PV households per kWh costs of the distribution system which causes the augmenting of the per unit charges as well as to the changes in payments for the electricity that impoverishes less wealthy customer groups. It also becomes clear that with the increase of EV penetration, the existing energy efficiency schemes would have to be revised. [ABSTRACT FROM AUTHOR]

To achieve the UK net‐zero emissions target by 2050, transformations to decarbonise the energy system will be essential. A transition from generating electricity by burning fossil fuel to renewable energy sources (RESs) is one of the most effective ways, in addition to customer transformation, in which people are willing to participate to reduce energy consumption. The railway sector accounts for 0.5% of carbon emissions in the United Kingdom. In order to meet the net‐zero goal, more railway routes must be electrified, as only 38% of railway routes are electrified at present. Furthermore, clean energy is necessary. Therefore, schemes for integrating RESs into the AC high‐speed railway power supply system are proposed and simulated in a case study. Power losses in the power system are comprehensively studied and compared. Owing to the fluctuation of traction load, the power quality issue is inevitable. Thus, the voltage unbalance factor is adopted to measure the severity of the imbalance. The results from the case study demonstrate that the proposed scheme in which the RES is connected to a three‐phase railway power network generates the smallest power losses among all proposed schemes. Moreover, it also requires lower investment expenditure and provides the most significant cost saving in the long run. The results also reveal that the VUFs of all schemes based on a 400 kV transmission system are below the United Kingdom's stringent limit of 1.5%. Furthermore, the CO2 emissions are reduced significantly with RES integration by half for the case study with the 120 MW RES. Although the other proposed schemes had higher losses and lifetime costs, the differences are not significant. Each scheme has its advantages and disadvantages. Several factors need to be considered to choose the suitable scheme, such as the size of land available etc. [ABSTRACT FROM AUTHOR]

Energy policy is too often not designed for energy consumers in a low-cost and consumer-friendly manner. This paper proposes a novel Stackelberg game and Blockchain-based framework that enables consumer-centric decarbonization by automating iterative negotiations between policy makers and consumers or generators to reduce carbon emissions. This iterative negotiation is modeled as a Stackelberg game-theoretic problem, and securely facilitated by Blockchain technologies. The policy maker formulates carbon prices and monetary compensation rates to dynamically incentivize the carbon reduction, whereas consumers and generators schedule their power profiles to minimize bills and maximize profits of generation, respectively. The negotiating agreement is yielded by reaching a Stackelberg equilibrium. The exchanged information and controlling functions are realized by using smart contracts of Blockchain technologies. Case studies of GB power systems show that the proposed framework can incentivize 9% more bill savings for consumers and 45.13% more energy generation from renewable energy sources. As a consumer-centric decarbonization framework, it can at least reduce carbon emissions by 40%. [Display omitted] • A novel consumer-centric and negotiation-based framework to decarbonize power systems. • A Blockchain based platform to integrate the exchanged information and controlling functions of the power system scheduling into data structures, nodes, and smart contracts of Blockchain networks. • How Blockchain based platform can prevent cyber attacks is discussed. • Case studies demonstrate the effectiveness of the proposed framework in the context of Great Britain power systems. [ABSTRACT FROM AUTHOR]

Taking the UK as a case study, this paper describes current energy use and a range of sustainable energy options for the future, including solar power and other renewables. I focus on the area involved in collecting, converting and delivering sustainable energy, looking in particular detail at the potential role of solar power. Britain consumes energy at a rate of about 5000 watts per person, and its population density is about 250 people per square kilometre. If we multiply the per capita energy consumption by the population density, then we obtain the average primary energy consumption per unit area, which for the UK is 1.25 watts per square metre. This areal power density is uncomfortably similar to the average power density that could be supplied by many renewables: the gravitational potential energy of rainfall in the Scottish highlands has a raw power per unit area of roughly 0.24 watts per square metre; energy crops in Europe deliver about 0.5 watts per square metre; wind farms deliver roughly 2.5 watts per square metre; solar photovoltaic farms in Bavaria, Germany, and Vermont, USA, deliver 4 watts per square metre; in sunnier locations, solar photovoltaic farms can deliver 10 watts per square metre; concentrating solar power stations in deserts might deliver 20 watts per square metre. In a decarbonized world that is renewable-powered, the land area required to maintain today's British energy consumption would have to be similar to the area of Britain. Several other high-density, high-consuming countries are in the same boat as Britain, and many other countries are rushing to join us. Decarbonizing such countries will only be possible through some combination of the following options: the embracing of country-sized renewable power-generation facilities; large-scale energy imports from country-sized renewable facilities in other countries; population reduction; radical efficiency improvements and lifestyle changes; and the growth of non-renewable low-carbon sources, namely 'clean' coal, 'clean' gas and nuclear power. If solar is to play a large role in the future energy system, then we need new methods for energy storage; very-large-scale solar either would need to be combined with electricity stores or it would need to serve a large flexible demand for energy that effectively stores useful energy in the form of chemicals, heat, or cold. [ABSTRACT FROM AUTHOR]

Miscanthus has been identified as one of the most promising perennial grasses for renewable energy generation in Europe and the United States [ Mitigation and Adaptation Strategies for Global Change 9 (2004) 433]. However, the decision to use Miscanthus depends to a considerable degree on its economic and environmental performance [ Soil Use and Management 24 (2008) 235; Renewable and Sustainable Energy Reviews 13 (2009) 1230]. This article assessed the spatial distribution of the economic and greenhouse gas ( GHG) costs of producing and supplying Miscanthus in the UK. The average farm-gate production cost of Miscanthus in the UK is estimated to be 40 £ per oven-dried tonne (£ odt−1), and the average GHG emissions from the production of Miscanthus are 1.72 kg carbon equivalent per oven-dried tonnes per year (kg CE odt−1 yr−1). The production cost of Miscanthus varies from 35 to 55 £ odt−1 with the lowest production costs in England, Wales and Northern Ireland, and the highest costs in Scotland. Sensitivity analysis shows that yield of Miscanthus is the most influential factor in its production cost, with precipitation the most crucial input in determining yield. GHG emissions from the production of Miscanthus range from 1.24 to 2.11 kg CE odt−1 yr−1. To maximize the GHG benefit, Miscanthus should be established preferentially on croplands, though other considerations obviously arise concerning suitability and value of the land for food production. [ABSTRACT FROM AUTHOR]

The development and rapid consumer adoption of energy efficiency products and renewable energy systems are key elements of the UK and the EU carbon reduction strategies to meet the challenge of climate change. Many such technologies are available for domestic use, but despite government incentives to meet carbon reduction targets consumer adoption has been slow. This Open University research with 111 in-depth interviews plus an on-line survey with nearly 400 responses, investigates consumer adoption, non-adoption and use of these technologies. Results show that it is important to research consumer use experiences, problems and requirements when designing and developing "green" technologies. With results tailored to each technology, this study shows that user-centred improvements are required to improve functionality, ergonomics, inter-connectedness with other systems and symbolic value, and to reduce cost and payback. User-centred research supports new product/system design and development to promote more rapid adoption and carbon-saving use of energy efficient and renewable technologies in homes. [ABSTRACT FROM AUTHOR]