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The urgent need to achieve net-zero carbon emissions by 2050 has led to a growing focus on innovative approaches to producing, storing, and consuming energy. Integrated energy systems (IES) have emerged as a promising solution, capitalising on synergies between energy networks and enhancing efficiency. Such a holistic approach enables the integration of renewable energy sources and flexibility provision from one energy network to another, reducing emissions while facilitating strategies for operational optimisation of energy systems. However, emphasis has been mostly made on steady-state methodologies, with a dynamic verification of the optimal solutions not given sufficient attention. To contribute towards bridging this research gap, a methodology to verify the outcomes of an optimisation algorithm is presented in this paper. The methodology has been applied to assess the operation of a civic building in the UK dedicated to health services. This has been done making use of real energy demand data. Optimisation is aimed at improving power dispatch of the energy system by minimising operational costs and carbon emissions. To quantify potential discrepancies in power flows and operational costs obtained from the optimisation, a dynamic model of the IES that better captures real-world system operation is employed. By incorporating slow transients of thermal systems, control loops, and non-linearity of components in the dynamic model, often overlooked in traditional optimisation modules, the methodology provides a more accurate assessment of energy consumption and operational costs. The effectiveness of the methodology is assessed through model-in-the- loop co-simulations between MATLAB/Simulink and Apros alongside a series of scenarios. Results indicate significant discrepancies in power flows and operational costs between the optimisation and the dynamic model. These findings illustrate potential limitations of conventional operational optimisation modules in addressing real-world complexities, emphasising the significance of dynamic verification methods for informed energy management and decision-planning. [ABSTRACT FROM AUTHOR]

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]

Solar energy is one type of clean energy resource, and currently the IMO, EU and UK are targeting net zero carbon emissions by 2050. This paper delves into the integration of photovoltaic (PV) systems into hybrid vessels in order to meet their strategies and targets. The technical challenges that come with designing such systems as well as their economic and environmental impacts are examined. By optimizing the usage of harnessed solar energy, we discover the operational strategy that provides maximal benefits through day-to-day savings as well as over the 25 year lifespan of solar panels. It demonstrates impressive economic viability, with cost savings of up to GBP 4.55 per day and a payoff period as short as 9 years. It also displays a modest emission reduction of up to 8.002 kg of CO2, which serves as proof for a pathway to greener practices in the maritime industry. This report highlights the operational flexibility that a hybrid vessel possesses once paired with a PV system through the ability to withstand regulatory and market changes. Also, when looking ahead, further adoption of PV technology creates opportunities for innovation in adopting renewable energy solutions in maritime transportation. [ABSTRACT FROM AUTHOR]

The UK net‐zero target requires the integration of significant renewable energy resources into the electrical grid. This, together with the projected growth in electricity demand imposes practical challenges on the power transfer capability of existing transmission feeders. For environmental and planning reasons, construction of new overhead lines is problematic, and where possible upgrading of existing substations and lines is preferred. This paper investigates the feasibility of transforming an existing three‐phase (3Φ) double‐circuit 400 kV line into a six‐phase (6Φ) feeder for a simulated future GB scenario. Results indicate a 6Φ feeder, operating at a 'phase‐adjacent phase' voltage of 400 kV can effectively solve the constraints of boundaries in transmission networks. When considering the various operating contingencies, associated with an important UK network boundary and its expected near‐future winter‐peak power transfer requirements, the thermal overload issues are mitigated by transforming a feeder from 3Φ to 6Φ. The paper demonstrates upgrading to 6Φ technology is a potential solution to certain future boundary constraints and in these cases avoids the need to build new underground or overhead AC/DC lines. [ABSTRACT FROM AUTHOR]

Hydrogen is gaining prominence as a sustainable energy source in the UK, aligning with the country's commitment to advancing sustainable development across diverse sectors. However, a rigorous examination of the interplay between the hydrogen economy and the Sustainable Development Goals (SDGs) is imperative. This study addresses this imperative by comprehensively assessing the risks associated with hydrogen production, storage, transportation, and utilization. The overarching aim is to establish a robust framework that ensures the secure deployment and operation of hydrogen-based technologies within the UK's sustainable development trajectory. Considering the unique characteristics of the UK's energy landscape, infrastructure, and policy framework, this paper presents practical and viable recommendations to facilitate the safe and effective integration of hydrogen energy into the UK's SDGs. To facilitate sophisticated decision making, it proposes using an advanced Decision-Making Trial and Evaluation Laboratory (DEMATEL) tool, incorporating regret theory and a 2-tuple spherical linguistic environment. This tool enables a nuanced decision-making process, yielding actionable insights. The analysis reveals that Incident Reporting and Learning, Robust Regulatory Framework, Safety Standards, and Codes are pivotal safety factors. At the same time, Clean Energy Access, Climate Action, and Industry, Innovation, and Infrastructure are identified as the most influential SDGs. This information provides valuable guidance for policymakers, industry stakeholders, and regulators. It empowers them to make well-informed strategic decisions and prioritize actions that bolster safety and sustainable development as the UK transitions towards a hydrogen-based energy system. Moreover, the findings underscore the varying degrees of prominence among different SDGs. Notably, SDG 13 (Climate Action) exhibits relatively lower overall distinction at 0.0066 and a Relation value of 0.0512, albeit with a substantial impact. In contrast, SDG 7 (Clean Energy Access) and SDG 9 (Industry, Innovation, and Infrastructure) demonstrate moderate prominence levels (0.0559 and 0.0498, respectively), each with its unique influence, emphasizing their critical roles in the UK's pursuit of a sustainable hydrogen-based energy future. [ABSTRACT FROM AUTHOR]

The reduced inertia levels in low-carbon power grids necessitate explicit constraints to limit frequency’s nadir and rate of change during scheduling. This can result in significant curtailment of renewable energy due to the minimum generation of thermal plants that are needed to provide frequency response (FR) and inertia. Additional consideration of fast FR, a dynamically reduced largest loss and under frequency load shedding (UFLS) allows frequency security to be achieved more cost effectively. This paper derives a novel constraint from the swing equation to contain the frequency nadir using all of these services. The expected cost of UFLS is found probabilistically to facilitate its comparison to the other frequency services. We demonstrate that this constraint can be accurately and conservatively approximated for moderate UFLS levels with a second order cone (SOC), resulting in highly tractable convex problems. Case studies performed on a Great Britain 2030 system demonstrate that UFLS as an option to contain single plant outages can reduce annual operational costs by up to $\pounds $ 559 m, 52% of frequency security costs. The sensitivity of this value to wind penetration, abundance of alternative frequency services, UFLS amount and cost is explored. [ABSTRACT FROM AUTHOR]

Offshore wind is in a rapid transitional phase, pushed worldwide by efforts of those to reduce climate change. Wind power is becoming a commercialised, unsubsidised competitive form of low carbon generation of renewable energy. Marketplaces reflect this growing trend with the first introduction of subsidy free bids in a tender for the Dutch and German governments. The analysis of surrounding literature of subsidy free bids and governmental policies revealed that integration of subsidy free bids have been carried out to various extents. Bids like those seen in the German and Dutch governments have been done in accompaniment with supportive policies and measures. For the UK, a possible subsidy free bid could be developed under the Scottish Sectoral Marine Plan. Owing to that, this paper investigates the feasibility of a subsidy free bid for the Scottish government. Utilising the Department for Business, Energy and Industrial Strategy (BEIS) levelised cost of electricity (LCOE) metric were inserted into a detailed excel spreadsheet. This paper calculates multiple financial scenarios under the LCOE metric to provide an insight into the possible scenarios of which different models of subsidy free bids can be implemented. The main parameters associated with the BEIS metric and calculator design were investigated. These included financial cost predictions, discount rate, generational capacity and net capacity factors. The final conclusion of the generated output data, showed it was indeed possible to adopt a subsidy free bid under the current UK contract for difference (CfD) scheme under strict and favourable conditions. [ABSTRACT FROM AUTHOR]

This paper makes a novel contribution by turning an 'asset' lens onto social and technical innovation in the context of the small-scale generation of renewable energy. The authors draw on learning from an international project that aimed to develop innovative technologies for the micro generation of energy using wastes and residues. Variations on innovation that cut across the social and technical are introduced. It is noted that although emanating from different traditions, a common theme is emphasis on a distributed knowledge base in which the roles of innovator, producer and consumer overlap or merge. This implies that the (social) innovation process is also one of co-creation. The authors borrow from international development studies the Sustainable Livelihood Analysis (SLA) framework, which is usually used for working with poor households to foreground strengths and resources rather than needs and deficits. To illustrate the utility of SLA for social innovation at local and community level, findings are presented from UK fieldwork on socio economic barriers and opportunities aff ecting the feasibility of new community energy generation and enterprise options. The importance and the fragility of human assets are highlighted. [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]

As renewable energy expands rapidly in installed capacity and in built-over area, constructors and researchers are shifting their sights from the lands to the seas. Offshore wind power (OWP), or offshore wind farm, is a typical source of the renewable energy constructed on the offshore islands or in the oceans. Since the installed capacity of OWP has become booming since 2000, its relevant researches also grow substantially. The objective of this paper is to quantify the research works of OWP and to analyze their focuses, main producers and high impact literature using bibliometric method, where the OWP-related core literature in recent 40 years are sorted out and a visualized analysis closely concerned terms, contributors on national/regional basis, and highly cited articles. The results show that researchers have been largely followed on the grid-connection operations, the frameworks and the ambient environment change of offshore wind power. Moreover, the UK has taken the leading position on the study of OWP at present. [ABSTRACT FROM AUTHOR]

The way of control and operation of an electrical power system has been changing rapidly with the integration of renewable energy sources (RES). One of the emerging issues that require addressing is the capability of RES to participate in the restoration process upon a total or partial system failure. However, with the continuous shutdown of large-centralised generators, which traditionally provided the black start support together with the variability of RES, the restoration process becomes much more complex. Primarily, the RES should have enough capacity to energise the load at the time of the restoration. Nonetheless, due to significant advantages, there is an increasing trend to use RES to meet the local energy demand by large industrial customers. The flexibility of shifting loads together with the surplus of RE generation could support the system operator during the system energisation process after a blackout. This paper mainly focuses on identifying the capabilities and factors that should be accounted for to participate in the system restoration process by large industrial consumers. The case study conducted on a large-scale steel factory in the UK reveals the possibility of supporting the restoration process under the bottom-up approach. [ABSTRACT FROM AUTHOR]

Political flexibility brings about trade-offs for policy-makers aiming to support the deployment of renewable energy sources (RES). On the one hand, it allows incorporating new information on ex ante uncertain benefits and costs of RES policy. On the other hand, it may deter RES investments. This paper scrutinizes how these trade-offs play out economically and politically when RES policy-makers choose the degree of flexibility as well as the instruments to implement flexibility. The analysis builds on a theoretical framework distinguishing between flexibility by design and by adjustment. It is complemented by a discussion of three case studies: RES support schemes in Germany and the United Kingdom, and the EU Emissions Trading Scheme. Theoretical as well as empirical results suggest that the politically chosen degree of flexibility by policy design may be sub-optimally low. In contrast, flexibility by policy adjustment is often excessively high. [ABSTRACT FROM AUTHOR]

• A net-zero DN model composed of solely non-dispatchable DGs and BESSs has been considered to tackle severe windstorms. • The proposed framework is particularly effective in DNs with high shares of converter-based DGs. • The proposed three-stage resilience assessment can provide up to 25 percent load shedding reduction. • A detailed spatiotemporal representation of the DN was implemented to accurately estimate the status of the grid. Increasing incidences of extreme weather events pose significant challenges to the electrical grids in terms of the ability to withstand those high-impact eventualities. This paper proposes a resilience assessment framework for net-zero active distribution networks (ADNs) to tackle the impacts of extreme windstorms where only renewable energy resources (RESs) and battery energy storage systems (BESSs) are considered. To accurately capture the influence of windstorms on the grid, a detailed spatiotemporal representation of grid system assets and their exposure to the wind has been implemented. The suggested day-ahead resilience assessment is based on a three-stage approach. The first stage computes the probabilities of failure of each line and determines the most vulnerable ones. The second stage obtains the optimal grid configuration based on the outcomes of the first stage given the available non-dispatchable RESs and commits the available resources in each island to minimize the loss of load during the windstorm. If such a value is still larger than zero after the second stage, a novel voltage regulation scheme is applied in the third stage, taking advantage of the RESs and BESSs in each island. The proposed resilience assessment has been evaluated using the IEEE 33-bus test system with the meteorological data retrieved from an actual windstorm event occurred in the UK on the 20th of February. The outcomes of this paper underscore that a significant reduction in load shedding during such extreme events can be achieved, thus having a notable enhancement to the overall resilience of the system. Finally, the performance of this approach is compared with other resilience-oriented methods for windstorms, where the benefits of using the scheme reported in this paper are highlighted and quantified. [ABSTRACT FROM AUTHOR]

In the context of Great Britain, onshore wind provides the most cost-effective method of renewable electricity generation. However, projects often face opposition to development based on social issues, and there are concerns that existing geospatial modelling approaches fail to fully integrate these effects into their assessment. Building upon previous statistical analysis, this paper presents a geospatial multi-criteria decision analysis that integrates the technological, legislative and social constraints to determine suitable sites for onshore wind turbine development in Great Britain. The findings suggest that the capacity estimates for wind are less than 5% of what was previously estimated, yet opportunities remain for further exploitation of this resource. [ABSTRACT FROM AUTHOR]

This paper articulates the potential implications of Brexit on energy policy and security in the United Kingdom (UK). Given the uncertainties associated with the decision to leave the European Union (EU), the need to consider its potential effects on the UK's energy sector becomes even more pertinent. Through the lens of a few widely reviewed trade regimes in the light of Brexit, it can be observed that while UK energy policies are unlikely to change drastically, Brexit nevertheless threatens the UK's capacity to safeguard its energy supply. The uncertainties following Brexit could arguably starve the UK's upstream petroleum, electricity, and renewable energy sectors of their required investments. Both short and long-term impacts could result in UK residents paying more per unit of energy consumed in a "hard Brexit" scenario, where the UK exits the Internal Energy Market (IEM) and must trade with the EU underWorld Trade Organisation rules. While a hard Brexit could aid the growth of the nascent shale gas industry, a negotiated withdrawal that includes some form of access to the IEM (a "soft Brexit") would be more beneficial for the future of energy security in the UK. [ABSTRACT FROM AUTHOR]

There is a need for increased renewable energy to meet net-zero targets and decarbonise the economy. Harnessing the predictable power of the tides with tidal stream turbines can contribute to this. Tidal energy is a nascent technology with higher costs at present. However, cost reductions have been observed with an increased deployment in other renewable energy technologies that have received financial support, and it is postulated that similar will happen with tidal energy. The first tidal stream projects have been awarded market support in the UK through the Contracts for Difference (CfD) scheme, with almost 100 MW expected to be commissioned by 2028. This work uses learning rates to investigate how much investment in ongoing market support might be needed to achieve cost reductions through subsidised deployment alongside research and innovation. Using a range of informed 'what if?' scenarios, it shows sensitivity to key inputs. The results show that the support needed is most sensitive to the learning rate, reducing it from 15% to 12.5% or 10% doubles or more than quadruples the investment required, respectively. The support is also highly dependent on the starting cost from which learning occurs, taken as the CfD Strike Price in 2025. Varying this between 156 and 220 GBP/MWh results in total investment of GBP 6.7 and 22.3 bn, respectively. Most importantly, a balance is needed between subsidising deployment to drive down costs through learning and funding innovation to maintain a high learning rate. [ABSTRACT FROM AUTHOR]

ABSTRACT Green electricity tariffs are one means by which green consumers can contribute to a more sustainable future. This paper profiles potential adopters of green electricity tariffs. Potential adoption is measured in terms of respondents' willingness to pay a premium for green energy in a national survey of the UK population. Hypotheses based principally on the cognitive-behavioural literature on green consumerism and green energy markets are developed. These are tested using a broad range of variables, which are grouped into three categories (demographic, attitudinal and behavioural). Consistent with past research, the empirical analyses find that attitudinal variables best characterize potential adopters. Further, potential adopters are found to have higher income, be better informed with respect to energy matters, show concern for the environment and believe that individual actions can make a difference to environmental decay. The implications of these findings for marketing and environmental policy are explored. Copyright © 2010 John Wiley & Sons, Ltd and ERP Environment. [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]

Wind power is an increasingly used form of renewable energy. The uncertainty in wind generation is very large due to the inherent variability in wind speed, and this needs to be understood by operators of power systems and wind farms. To assist with the management of this risk, this paper investigates methods for predicting the probability density function of generated wind power from one to ten days ahead at five U.K. wind farm locations. These density forecasts provide a description of the expected future value and the associated uncertainty. We construct density forecasts from weather ensemble predictions, which are a relatively new type of weather forecast generated from atmospheric models. We also consider density forecasting from statistical time series models. The best results for wind power density prediction and point forecasting were produced by an approach that involves calibration and smoothing of the ensemble-based wind power density. [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]

Presently, there is growing discourse surrounding climate change, global warming, and the possibility of urban smog. Daily, we encounter air pollutants unwittingly, often oblivious to the substantial adverse impacts they may impart on our health. This manuscript furnishes a thorough examination of the shifts in the concentrations of distinct air pollutants, namely, sulphur oxides (SOx), nitrogen oxides (NOx), and particulate matter PM2.5 and PM10, within the contexts of the United Kingdom (a country progressively transitioning to alternative energy sources) and Poland (a country in the EU with the second lowest climate policy evaluation in the climate change performance index or CCPI) from 1970 to 2020. This comparative study between the two countries clearly showed the importance of the transition to clean energy sources. The UK's efforts towards cleaner energy sources have led to reduced emissions of sulphur oxides (SOx) and particulate matter. In contrast, Poland's heavy dependence on energy primarily from coal over the years has resulted in elevated pollution levels, notably in the concentration of pollutants such as particulate matter. This study also revealed that changes in emissions predominantly stem from technological advancements and economic activities. Additionally, political regulations and the gradual phase-out of specific fuels or energy-rich substances and their substitution with alternative energy sources have also imparted considerable influence. [ABSTRACT FROM AUTHOR]

There are global efforts to deploy Electric Vehicles (EVs) because of the role they promise to play in energy transition. These efforts underscore the e-mobility paradigm, representing an interplay between renewable energy resources, smart technologies, and networked transportation. However, there are concerns that these initiatives could burden the electricity grid due to increased demand. Hence, the need for accurate short-term load forecasting is pivotal for the efficient planning, operation, and control of the grid and associated power systems. This study presents robust models for forecasting half-hourly and hourly loads in the UK's power system. The work leverages machine learning techniques such as Support Vector Regression (SVR), Artificial Neural Networks (ANN), and Gaussian Process Regression (GPR) to develop robust prediction models using the net imports dataset from 2010 to 2020. The models were evaluated based on metrics like Root Mean Square Error (RMSE), Mean Absolute Prediction Error (MAPE), Mean Absolute Deviation (MAD), and the Correlation of Determination (R2). For half-hourly forecasts, SVR performed best with an R-value of 99.85%, followed closely by GPR and ANN. But, for hourly forecasts, ANN led with an R-value of 99.71%. The findings affirm the reliability and precision of machine learning methods in short-term load forecasting, particularly highlighting the superior accuracy of the SVR model for half-hourly forecasts and the ANN model for hourly forecasts. [ABSTRACT FROM AUTHOR]

In the process of decarbonization, the configuration of renewable energy and energy storage plays a crucial role. In current research, there is often a singular focus on the isolated optimization of either renewable energy configurations or energy storage configurations, resulting in limitations within the optimized outcomes. Therefore, we propose a collaborative configuration approach for renewable energy and energy storage under fixed investment, considering the impact of uncertainty on optimization results. By employing the W/S (wind-to-solar ratio) and E/P (energy-to-power ratio) and constructing a model with an hourly granularity, we can obtain the configurations of renewable energy and energy storage at crucial time points. Using the UK as a case study, we calculate the configurations for renewable energy and energy storage from 2020 to 2050, offering effective recommendations for the decarbonization efforts in the UK. [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]

Due to the increasing use of renewable, non-controllable energy generation systems energy storage systems (ESS) are seen as a necessary part of future power delivery systems. ESS have gained research interest and practical implementation over the past decade and this is expected to continue into the future. This is due to the economic and operational benefits for both network operators and customers, battery energy storage system (BESS) is used as the main focus of this research paper. This paper presents an analytical study of the benefits of deploying distributed BESS in an electrical distribution network (DN). The work explores the optimum location of installing BESS and its impact on the DN performance and possible future investment. This study provides a comparison between bulk energy storage installed at three different locations; medium voltage (MV) side and low voltage (LV) side of the distribution transformer (DT) and distributed energy storage at customers' feeders. The performance of a typical UK DN is examined under different penetration levels of wind energy generation units and BESS. The results show that the minimum storage size is obtained when BESS is installed next to the DT. However, the power loss is reduced to its minimum when BESS and wind energy are both distributed at load busbars. The study demonstrates that BESS installation has improved the loss of life factor of the distribution transformer. [ABSTRACT FROM AUTHOR]

Tidal stream energy is a predictable renewable energy source; however, environmental consent of developments remains a key barrier to the expansion of this industry. Uncertainty around collision risk, i.e., the risk of animals colliding with a tidal device, remains a major barrier to consent. Collision risk models are used in environmental impact assessments. Common collision risk models, like the Encounter Rate and Band Models, have limitations in accommodating new device designs and flexibility. To address this, a simulation-based approach was developed. To provide confidence in its use, it is important that the simulation-based approach is compared against the Band model and the Encounter rate model, which have been regularly used in the UK. Here, we compared collision risk estimates from the three models under the same exact conditions and one alternative condition. The results of the main scenario (where all conditions were the same) showed that the three models produced comparable results with <6% difference across all models. However, for the alternative scenario, the simulation-based approach produced a result three times higher compared to other models, which could not account for a vertical approach angle. These findings provide confidence in the simulation-based approach whilst also outlining the importance of selecting an appropriate collision risk model, tailored to the specific assessment scenario. Improved understanding and application of such models hold the key to more accurate risk evaluations in environmental impact assessments, thus facilitating the sustainable development of the tidal energy industry. [ABSTRACT FROM AUTHOR]

This paper presents a comprehensive analysis of renewable and especially tidal energy through a political, economic, social, technology, legal and environmental (PESTLE) analysis approach and by reviewing the most up to date relevant literature. The study focuses on the United Kingdom given the favourable environmental resources for such technologies; the number of different design concepts that are currently under development as well as the research funding that has been invested over the last few years. Findings of the analysis identify the risks and multiple stakeholders involved at all stages of the tidal energy projects development from the conceptualization of the design, right through to decommissioning. Many of the stakeholders present benefits to the tidal developers through funding, incentives and knowledge sharing, but at the same time they also present potential risks to the future of projects. This is mostly down to different approaches of the most important aspect of tidal energy that needs to be considered, making it hard for technologists and developers to equally address all requirements. From this research it can be concluded that several of these risks can be mitigated early on providing that particular stakeholders are involved at the correct stage of a project. [ABSTRACT FROM AUTHOR]

Abstract: This paper demonstrates how Linear Programming (LP) can be applied to assist in the choice of renewable energy technologies for use in buildings to meet CO2 emissions reduction targets. Since there are many possibilities for combining different renewable technologies, the capital costs associated with the installation of one or more renewables can vary widely. In terms of capital investment the preferred solution will be the one at least cost, and LP provides an effective way to find this minimum through the so-called “objective function”. This project has used “lp_solve”, a free-source Mixed Integer Linear Programming solver that has been embedded in a Microsoft Excel application called Carbon emissions And Renewables for Building OPtimisation Toolkit (CARB-OPT) developed by RES Ltd in collaboration with London South Bank University (Renewable Environmental Services Ltd. (RES) is the environmental consultancy of Long and Partners Engineering Group. RES is currently involved in a Knowledge Transfer Partnerships (KTP) project in conjunction with the Faculty of Engineering, Science and the Building Environment (ESBE) at London South Bank University). This paper reports the application of this LP optimisation process for an office building case study with four alternative combinations of renewables. The process showed the technology mix that would lead to the smallest investment needed to comply with UK Building Regulations requirements and regional planning targets. In addition, the process offers a robust methodology to test the impact that the key assumptions may have upon the optimum solution. [Copyright &y& Elsevier]

Abstract: The Netherlands is both heavily dependent on the success of carbon capture and storage (CCS) and renewable electricity for its decarbonisation policy. The same holds for the EU and some of its Member States like the United Kingdom. This paper discusses several scenarios for the Netherlands within the context of a liberalised and a more and more connected energy market in Northwest-Europe. The research reported here shows that CCS on new coal fired power plants does not pose a threat to the increase in the electricity production by large quantities of wind energy in the electricity system, and vice versa. For renewable energy, several additional policies are in place mainly in the form of financial support as long as these renewable options are not yet profitable. For CCS, financial support is only granted now for a selection of the first demonstration projects now planned in the EU. It is not yet clear if large scale CCS and high shares of wind energy can be incorporated in a balanced way in the electricity system. This paper shows that from a technical and economic point of view, there is room for both, and under which conditions such a two fold growth will be feasible. [Copyright &y& Elsevier]

Apart from numerous technical challenges, the transition towards a carbon-neutral energy supply is greatly hindered by limited economic feasibility of renewable energy sources. This results in their slow and bounded penetration in both commercial and residential sectors that are responsible for over 40% of final energy consumption. This paper aims to demonstrate that combined application of sophisticated planning methodologies at building-level and presents incentive mechanisms for renewables that can result in prosumers, featuring hybrid renewable energy systems (HRES), with economic performance comparable to that of conventional energy systems. The presented research enhances existing planning methodologies by integrating appliance-level demand side management into the decision process and investigates its effect on the planning problem. Moreover, the proposed methodology features an innovative and holistic approach that simultaneously assess electrical and thermal domain in both an isolated and grid-connected context. The analyzed hybrid system consists of solar photovoltaic, wind turbine and battery with thermal supply featuring solar thermal collector and a ground-source heat pump. Overall optimization problem is modeled as a mixed-integer linear program, while ranking of all feasible alternatives is made by the multicriteria decision-making algorithm against several technological, economic, and environmental criteria. A real-life scenario of energy system retrofit for a building in the United Kingdom was employed to demonstrate overall cost savings of 12% in the present market and regulation context. [ABSTRACT FROM AUTHOR]

Abstract: In the past decade or so, the British government policy support for renewable energy (RE) has been at the core of the rapid growth of bioenergy in the UK rather than genuine market forces. Policy support has been through various instruments which are discussed in this paper, with particular attention given to co-firing and transport fuels. The UK energy sector remains dominated by large fossil fuels power plants and this does not facilitate the introduction of RE. One exception is co-firing which in 2005 generated 2.5TWh. Another area of considerable potential and interest is the use of biofuels (biodiesel and bioethanol) for transport, although current contribution remains still very small (0.18% of total fuel sales in 2005). In 2005, the UK used 1.4 million tonnes of biomass in co-firing, mostly imported, while considerable potential exists for further expansion should policy incentives continue. It is also generally accepted that the UK will have to rely largely on imports if it is to fulfil its 5% minimum biofuel blends agreed for 2010 and 10% in 2015. Both sectors present excellent opportunities for international bioenergy trade, despite the domestic production potential, as demonstrated in this paper. In addition, the forthcoming introduction of carbon and sustainability reporting should incentivise greater reporting along the supply chain, encouraging trade in the most sustainable biofuels. [Copyright &y& Elsevier]

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]

Hydrogen vehicles, encompassing fuel cell electric vehicles (FCEVs), are pivotal within the UK's energy landscape as it pursues the goal of net-zero emissions by 2050. By markedly diminishing dependence on fossil fuels, FCEVs, including hydrogen vehicles, wield substantial influence in shaping the circular economy (CE). Their impact extends to optimizing resource utilization, enabling zero-emission mobility, facilitating the integration of renewable energy sources, supplying adaptable energy storage solutions, and interconnecting diverse sectors. The widespread adoption of hydrogen vehicles accelerates the UK's transformative journey towards a sustainable CE. However, to fully harness the benefits of this transition, a robust investigation and implementation of safety measures concerning hydrogen vehicle (HV) use are indispensable. Therefore, this study takes a holistic approach, integrating quantitative risk assessment (QRA) and an adaptive decision-making trial and evaluation laboratory (DEMATEL) framework as pragmatic instruments. These methodologies ensure both the secure deployment and operational excellence of HVs. The findings underscore that the root causes of HV failures encompass extreme environments, material defects, fuel cell damage, delivery system impairment, and storage system deterioration. Furthermore, critical driving factors for effective safety intervention revolve around cultivating a safety culture, robust education/training, and sound maintenance scheduling. Addressing these factors is pivotal for creating an environment conducive to mitigating safety and risk concerns. Given the intricacies of conducting comprehensive hydrogen QRAs due to the absence of specific reliability data, this study dedicates attention to rectifying this gap. A sensitivity analysis encompassing a range of values is meticulously conducted to affirm the strength and reliability of our approach. This robust analysis yields precise, dependable outcomes. Consequently, decision-makers are equipped to discern pivotal underlying factors precipitating potential HV failures. With this discernment, they can tailor safety interventions that lay the groundwork for sustainable, resilient, and secure HV operations. Our study navigates the intersection of HVs, safety, and sustainability, amplifying their importance within the CE paradigm. Using the careful amalgamation of QRA and DEMATEL methodologies, we chart a course towards empowering decision-makers with the insights to steer the hydrogen vehicle domain to safer horizons while ushering in an era of transformative, eco-conscious mobility. [ABSTRACT FROM AUTHOR]

Climate change has highlighted the need to promote renewable energies. The offshore wind industry is growing exponentially because of some political strategies supported by various organizations, such as the European Union. The implementation of these strategies is commonly associated with significant investments, public acceptance, or achieving better installations and greater cumulative capacities. To ensure that offshore renewable energy projects could reach their ambitious targets, this study promotes the implementation of political strategies or planning decisions using data mining techniques and analytical tools. Strategic decisions based on real data analysis could help to achieve more suitable and optimal infrastructures. The scour phenomenon jeopardizes the operability of offshore wind farms, making it necessary to study its evolution over the years. In this work, extensive research on the scour phenomenon in offshore wind farms using real data (from the Lynn and Inner Dowsing offshore wind farms located in the UK) was performed, which revealed an evident lack of consideration of this phenomenon for data-driven decision-making processes. As a novelty, this research develops a detailed geospatial analysis of data, studying the possible autocorrelation of scour data measured from each turbine between 2011 and 2015. The conclusions obtained could be used to improve future planning tasks in offshore wind farms. [ABSTRACT FROM AUTHOR]

Decarbonisation is becoming a central aim of countries around the globe, ensuring the effects of climate change do not increase exponentially in the coming years. Renewable energy generation is at the core of this decarbonisation process, enabling economies to divorce themselves from a reliance on oil and coal. Hybrid energy systems can utilise multiple generation methods to supply electrical demand best. This paper investigates the use of localised hybrid energy systems around the UK, comparing the financial viability of solar, wind and hydrokinetic generation methods both as a hybrid system and individually in different scenarios. The significance of having localised hybrid energy systems is that they address two large problems within renewable energy generation, that of storage issues and also generating the electricity far away from where it is actually used, requiring extensive infrastructure. The microgrid optimisation software HOMER was used to simulate each of the generation methods alongside the national grid, including lithium ion batteries and converters to create a comprehensive hybrid system. Net Present Cost, which is the current value of all the costs of installing and operating the system over the project lifetime, was considered as the metric. The analysis finds that for each modelled location, wind turbines in combination with lithium ion batteries and a converter is the system with the lowest Net Present Cost, with the exception of Bristol, which also uses hydrokinetic turbines within the system. The findings indicate the extensive wind resources available within the UK, along with identifying that certain locations around the country also have very high potential for tidal power generation. [ABSTRACT FROM AUTHOR]

Electric heat pumps (HPs), hybrid heating technology and district heating networks (DHN) are the main low-carbon heating technologies that can deliver the ambitious carbon reduction target in the UK. The optimal design of the heating system on a national scale to maximize the economic benefits regarding both investment cost and operation cost while satisfying the carbon target remains an open question. This paper aims to compare the economic advantages as well as the associated impacts on the electricity system under the full deployments of ASHP (air source HP), hybrid HP-Bs (ASHP and gas boilers) and DHNs. To do so, a novel whole-system approach is applied with the explicit consideration of the coordinated operation between heat and electricity system. The optimized strategy for heat sector decarbonisation is also demonstrated, providing an outline of the optimal deployment for different heating technologies in terms of their penetrations and deployed areas. The UK case study suggests the significant economic advantage of the hybrid HP-B over the other two heating technologies, while DHN may play an important role in urban areas under the optimized heat decarbonisation strategy. The results also clearly demonstrate the changes on the electricity side driven by the different decarbonisation strategies in the heating system. [ABSTRACT FROM AUTHOR]

This paper presents the methodological approach and findings of a simulation study of advanced energy conservation, generation and management technologies applied to two case study dwellings in the UK, so as to achieve net zero energy (NZE) target that includes a reduction of net regulated energy (HVAC) to 0 kWh/m 2 per year and energy generation of at least 50 kWh/m 2 per year. The performance of the dwellings are also tested for a change in energy use and risk of summertime overheating in future climates in the short (2030s), medium (2050s) and long term (2080s). The findings indicate that to meet the NZE targets, regulated loads need to reduce by about half (over current Building Regulations) with community (rather than building-level) renewables playing a major role. It is also found that the NZE targets, given current regulations, are not particularly difficult to achieve in design with regard to energy efficiency but are highly expectant with regard to renewable energy. Further, summertime overheating is projected to be a risk for net zero energy dwellings by the 2050s. Despite this the regulated energy use of both dwellings is projected to reduce by 11 kWh/m 2 /yr, accompanied by a small increase in renewable generation (2 kWh/m 2 /yr). [ABSTRACT FROM AUTHOR]

The UK electricity grid is expected to supply a growing electricity demand and also to cope with electricity generation variability as the country pursues a low-carbon future. Molten Salt Reactors (MSRs) could offer a solution to meet this demand thanks to their estimated low capital costs, low operational risk, and promise of reliably dispatchable low-carbon electricity. In the published literature, there is little emphasis placed on estimating or modelling the future impact of MSRs on electricity grids. Previous modelling efforts were limited to quantifying the value of renewable energy sources, energy storage and carbon capture technologies. To date, no study has assessed or modelled MSRs as a competing power generation source for meeting decarbonization targets. Given this gap, the main objective of this paper is to explore the cost benefits for policy makers, consumers, and investors when MSRs are deployed between 2020 and 2050 for electricity generation in the UK. This paper presents results from electricity systems optimization (ESO) modelling of the costs associated with the deployment of 1350 MW e MSRs, from 2025 onwards to 2050, and compares this against a UK grid with no MSR deployment. Results illustrate a minimum economic benefit of £1.25 billion for every reactor installed over this time period. Additionally, an investment benefit occurs for a fleet of these reactors which have a combined net present value (NPV) of £22 billion in 2050 with a payback period of 23 years if electricity is sold competitively to consumers at a price of £60/MWh. [ABSTRACT FROM AUTHOR]

As the adoption of renewable energy sources, particularly photovoltaic (PV) solar, has increased, the need for effective inspection and data analytics techniques to detect early-stage defects, faults, and malfunctions has become critical for maintaining the reliability and efficiency of PV systems. In this study, we analysed thermal defects in 3.3 million PV modules located in the UK. Our findings show that 36.5% of all PV modules had thermal defects, with 900,000 displaying single or multiple hotspots and ~250,000 exhibiting heated substrings. We also observed an average temperature increase of 21.7 °C in defective PV modules. Additionally, two PV assets with 19.25 and 8.59% thermal defects were examined for PV degradation, and results revealed a higher degradation rate when more defects are present. These results demonstrate the importance of implementing cost-effective inspection procedures and data analytics platforms to extend the lifetime and improve the performance of PV systems. [ABSTRACT FROM AUTHOR]

Renewable energy sources are rapidly increasing in demand and importance as governments and countries around the globe begin to understand their vital role in reducing climate change. This project aimed to design and create an optimised micro-hydro turbine system for downpipes to harness the currently untapped potential energy from rainwater. Experimental methods were used to determine the magnitude of voltage output available at different rainfall intensities by simulating such flow rates on a hydraulic bench. The viability of this energy to power household appliances was then evaluated, and methods of increasing the voltage output were assessed, such as layering the turbines in a single downpipe or placing multiple downpipes around the building. The study determined that, during average rainfall in the UK, a single turbine could produce a maximum of 7.21 V of DC voltage, or 50.49 V during heavy rainfall—enough energy to power a mobile device charger or a vacuum cleaner, respectively. Therefore, this proves a high potential in rainwater energy harvesting as a renewable energy source. It was also concluded that a positive correlation occurred for both the number of turbines in a downpipe and the number of pipes around the building with the voltage output of the whole system. [ABSTRACT FROM AUTHOR]

• Severe PV ramping at high penetration could cause voltage instability in presence of Induction motor loads. • Replacement of Induction motor by Variable Speed Drive (VSD) loads enhances voltage stability of distribution network. • Enhanced stability with VSD is studied theoretically with Q-V analysis and with time simulations. • Minimum IM replacement by VSD is determined for realistic distribution network at various PV penetration levels. The Photovoltaic (PV) sources have become the most popular renewable energy resources as it is modular and are deployed quickly. However, the distributed PVs are highly volatile and can have high ramping characteristics where the ramping can go up to 90% of its capacity in about 20 s due to events such as the passing of fast-moving clouds. This kind of PV ramps with high magnitudes can lead to voltage instability in distribution networks that are usually dominated by Induction motor (IM) loads. This paper explains the mechanism of such an instability analytically using Q-V analysis with distribution feeder and IM load characteristics. Highlighting the gradual replacement of IM loads by Variable Speed Drive (VSD) loads due to energy efficiency policies, the paper demonstrates the enhanced voltage stability under VSD loads by both time simulation and analytical approach. Furthermore, the analysis is extended to a realistic distribution network namely, United Kingdom General Distribution System (UKGDS) and extensive case studies are conducted to analyze the voltage stability during PV ramping events at various load compositions of IMs and VSDs. Moreover, the minimum VSD penetration level required to avert the voltage instability at various PV penetration levels have also been determined. [ABSTRACT FROM AUTHOR]

In order to pursue the low-carbon development around the world, a large scale of renewable generation will be connected to the power systems. Take the Great Britain (GB) as an example, the GB power system has a large wind energy integration potential. The intermittency of wind generation will have great impact on the system frequency stability. Electric vehicles (EVs) have a crucial role in decarbonizing the transport sector. To increase the utilization of wind energy, EVs are suggested to provide frequency response service to the power system due to their quick power reaction characteristic. This paper proposes a general dynamic EV frequency control strategy considering the travelling behavior of the EV users. A droop control method is used to regulate the EV charging/discharging power according to the frequency signal. A Forced-Charge Boundary (FCB) and a Forced-Charge Area (FCA) are proposed to guarantee sufficient energy in the EV battery for user’s travel at the plug-out time. A dynamic Virtual Energy Storage System (VESS) is developed to evaluate the frequency response capacity of the EV clusters. In the case study, the model of the GB power system is used to investigate the frequency control effect of the control strategy. The simulation results show that the proposed strategy provides effective EV frequency response to the power system and thus is able to facilitate the integration of wind energy. [ABSTRACT FROM AUTHOR]

• Social acceptance research should be critical, systematic, and holistic. • Domestic hydrogen acceptance is shaped by the interplay of five distinct dimensions. • Hydrogen acceptance hinges on cognitive, sociopolitical, and sociocultural legitimacy. • Hydrogen acceptance is composed of a rich matrix of potential consumer responses. • Overcoming attitudinal and behavioral barriers is critical to the hydrogen transition. The 'deep' decarbonization of the residential sector is a priority for meeting national climate change targets, especially in countries such as the UK where natural gas has been the dominant fuel source for over half a century. Hydrogen blending and repurposing the national grid to supply low-carbon hydrogen gas may offer respective short- and long-term solutions to achieving emissions reduction across parts of the housing sector. Despite this imperative, the social acceptance of domestic hydrogen energy technologies remains underexplored by sustainability scholars, with limited insights regarding consumer perceptions and expectations of the transition. A knowledge deficit of this magnitude is likely to hinder effective policymaking and may result in sub-optimal rollout strategies that derail the trajectory of the net zero agenda. Addressing this knowledge gap, this study develops a conceptual framework for examining the consumer-facing side of the hydrogen transition. The paper affirms that the spatiotemporal patterns of renewable energy adoption are shaped by a range of interacting scales, dimensions, and factors. The UK's emerging hydrogen landscape and its actor-network is characterized as a heterogenous system, composed of dynamic relationships and interdependencies. Future studies should engage with domestic hydrogen acceptance as a co-evolving, multi-scalar phenomenon rooted in the interplay of five distinct dimensions: attitudinal, sociopolitical, community, market, and behavioral acceptance. If arrived to, behavioral acceptance helps realize the domestication of hydrogen heating and cooking, established on grounds on cognitive, sociopolitical, and sociocultural legitimacy. The research community should internalize the complexity and richness of consumer attitudes and responses, through a more critical and reflexive approach to the study of social acceptance. [ABSTRACT FROM AUTHOR]

The evolution towards Smart Grids (SGs) represents an important opportunity for modernization of the energy industry. It is characterized by a bidirectional flow of information and energy between consumers and suppliers. However, the rapid increase of energy demands in residential areas is becoming a challenging problem. In order to address this issue, Demand-Side Management (DSM) has proven to be an effective solution. In this paper, we propose LOSISH, a price-based Demand Response (DR) system for load scheduling in residential Smart Homes (SHs) that achieves a trade-off between electricity payments and consumer's discomfort. Our proposed system considers Renewable Energy Sources (RESs), Battery Energy Storage System (BESS) and Plug-in Electric Vehicle (PEV). We formulate our scheduling as a constrained optimization problem and we propose a new hybrid algorithm to solve it. The latter combines two well known heuristic algorithms: Particle Swarm Optimization (PSO) and Binary Particle Swarm Optimization (BPSO). Moreover, we propose a new clustering algorithm based on Machine Learning (ML) to extract consumer's preferences from a real dataset that contains the historical consumption patterns of his smart appliances. We test our approach on real data traces obtained from a SH and we set up an experiment to evaluate our algorithm on a Raspberry Pi and measure its energy consumption. To prove the effectiveness of our approach, we compare our results with another approach from the literature in terms of electricity bill, Peak-to-Average Ratio (PAR), energy consumption, and execution time. Numerical results show that LOSISH outperforms the other approach in terms of electricity bill (up to 52.92% cheaper), PAR (up to 44% decrease in peak demands), energy consumption (up to 69.44% less consumption), and execution time (up to 63.15% faster). • The load scheduling problem in residential smart homes is studied. • A constrained problem is formulated to make a trade-off between costs and comfort. • A hybrid heuristic algorithm and a Machine Learning clustering model are proposed. • Real data collected from a smart home in the UK was used to validate our approach. • Simulation and experimental results demonstrate the effectiveness of our approach. [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]

The dynamics of power consumption constitutes an essential building block for planning and operating sustainable energy systems. Whereas variations in the dynamics of renewable energy generation are reasonably well studied, a deeper understanding of the variations in consumption dynamics is still missing. Here, we analyse highly resolved residential electricity consumption data of Austrian, German and UK households and propose a generally applicable data-driven load model. Specifically, we disentangle the average demand profiles from the demand fluctuations based purely on time series data. We introduce a stochastic model to quantitatively capture the highly intermittent demand fluctuations. Thereby, we offer a better understanding of demand dynamics, in particular its fluctuations, and provide general tools for disentangling mean demand and fluctuations for any given system, going beyond the standard load profile (SLP). Our insights on the demand dynamics may support planning and operating future-compliant (micro) grids in maintaining supply-demand balance. In modern power grids, knowing the required electric power demand and its variations is necessary to balance demand and supply. The authors propose a data-driven approach to create high-resolution load profiles and characterize their fluctuations, based on recorded data of electricity consumption. [ABSTRACT FROM AUTHOR]