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Energy poverty is driven by four factors: poverty; high energy prices; energy-inefficiency; and specific household characteristics. Increasingly refined definitions of energy poverty (and/or vulnerability) identify types or locations of households most likely to be suffering it. But there is also a place for a different approach, considering poverty reduction directly, as poverty is a necessary component within all energy poverty definitions. This paper investigates how high the UK's top marginal tax rates would need to be, to provide funds to lift low-income UK households above the poverty threshold as defined by the low-income-high-cost (LIHC) and 10% energy poverty indicators. It finds that the increased top tax rates would still be in line with those of other European OECD countries. Using recent and new research on income elasticities of CO2 emissions, it then estimates the net direct effects on CO2 emissions of this redistribution. For both scenarios the most likely effect is a small reduction in net CO2 emissions. Further, indirect downward pressures on CO2 emissions due to reduced income among the highest earners are likely to lead to yet more favourable outcomes for net CO2 emission reduction. [ABSTRACT FROM AUTHOR]

Highlights • Energy consumption in higher education institutions (HEIs) modelled. • For the first time, panel data used, with cross-sectional and time-series variations. • Over time and across HEIs, energy use increases as income and size increase. • Economies of scale as HEIs grow, but energy use still rising with sector growth. • Research universities more energy intensive. Abstract Among the various sustainability goals of higher education institutions (HEIs), reducing energy use and carbon emissions are particularly important. However, not much is known about energy demand from the higher education sector – especially since there is a lack of robust models of energy demand in this sector. This paper, the first to utilize a panel dataset and advanced panel econometric techniques in order to model energy use in higher education, investigates variations in energy use between HEIs (cross-sectional analysis), and also changes in energy use over time (temporal analysis), using the UK as a case study. We argue that panel dataset and methods are more useful for understanding growth (and reduction) in energy use within the HE sector than the methods used within previous cross-sectional studies. Results show that, over time and also across the sector, energy consumption in the HEIs increases with increases in income and floor space, but at a slower rate. As HEIs grow overall (in terms of income, floor space, student and staff number) over time, they become more 'energy efficient' (using less energy per unit of area, population or income), indicating economies of scale in the temporal dimension. Results also show that after controlling for income and size, research intensive HEIs consume more energy. We also find a small but statistically significant effect of energy prices on energy consumption, as might be expected. Simulation using the model parameters for an example scenario suggests that energy consumption will continue to increase unless there is a significant change in the policies driving income growth and spatial expansion in the HE sector in the UK. [ABSTRACT FROM AUTHOR]

Abstract In the UK, housing has been identified as a major sector for contributing to the 80% reduction in carbon emissions over the 1990 baseline by 2050, required by the Climate Change Act 2008. However, pre-1919 housing stock is the least energy efficient and consequently poses challenges to meeting this target. Using a mixed methods approach, the current study demonstrates that, in actuality, there is a significant potential for reducing emissions among this sub-sector of housing, and that the major barriers to energy efficiency retrofits concern a lack of funding, the payback period for the investment, disruption to home life and finding a trustworthy and skilled installer. Moreover, this study finds that homeowners are motivated primarily by the desire to improve home comfort and aesthetics along with a reduction in energy bills rather than in reducing carbon emissions. The paper concludes with recommendations for improving the viability of retrofitting pre-1919 homes through enhanced financial resources, policy support and the promotion of social and economic benefits. [ABSTRACT FROM AUTHOR]

Dynamic tariffs play an important role in demand response, contributing to smoothing power consumption and reducing generation capacity requirement and carbon emission. However, in the existing works, tariffs are usually designed without comprehensive consideration, such as potential user responses to tariffs. Thus, assuming an electricity trading market contains a utility company and multiple residential users, a dynamic tariff design method is proposed in this paper, considering user responses to tariff changes. Leveraging the non-intrusive load monitoring technique, rated power and user preference features for each appliance are acquired by the utility company to quantify user comfort (discomfort) based on derived user appliance usage habits. Then, a bi-level Stackelberg game model is built on the supply side for designing optimal dynamic tariffs and imitating the influence of tariff changes on DR plans for users. The upper level represents the utility company, trying to maximize utility profit, social welfare and carbon emission reduction. While the lower level represents users, aiming to minimize electricity bills and user discomfort. By solving such an optimization problem with multiple objectives, a novel hybrid probabilistic multi-objective evolutionary algorithm balancing evolutionary efficiency and stability is applied where random forest is adopted to boost performance. The proposed model is benchmarked with two state-of-the-art pricing methods and validated on a publicly accessible REFIT dataset, where low-rate power measurements are collected from real houses in the UK. The experimental results show the proposed model generally outperforms benchmarks on dynamic tariff design in achieving peak-shaving and low carbon emission while preserving user satisfaction. Furthermore, a case study is implemented, which verifies the necessity of various objectives employed in the proposed method. • A bi-level Stackelberg game model for designing tariff based on user demand response. • Electricity-consuming feature extraction on non-intrusive load monitoring results. • A hybrid probabilistic multi-objective algorithm balancing efficiency and stability. • A random forest classifier for reducing computational complexity in late iterations. • Extensive case studies on evaluating objectives and visualizing optimization process. [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]

• Techno-economic analysis of low-carbon heat supply options for UK supermarkets. • RIHC, an ASHP, and a thermal storage tank with advanced control is recommended. • Best investments provide a 16-to-18-year payback without a carbon price. • The UK renewable heat incentive subsidy (for ASHP) generates 89% of the 'savings' • When a £100/tCO2e tax is considered, paybacks are reduced to a 9–11 years. Eliminating the use of natural gas for non-domestic heat supply is an imperative component of net-zero targets. Techno-economic analyses of competing options for low-carbon heat supply are essential for decision makers developing decarbonisation strategies. This paper investigates the impact various heat supply configurations can have in UK supermarkets by using heat recovery principles from refrigeration systems under different climatic conditions. The methodology builds upon a steady-state model that has been validated in previous studies. All refrigeration integrated heating and cooling (RIHC) systems employ CO 2 booster refrigeration to recover heat and provide space heating alongside various technologies such as thermal storage, air-source heat pumps (ASHPs) and direct electric heaters. Seven cases evaluating various technology combinations are analysed and compared against a conventional scenario in which the building is heated with a natural gas boiler. The specific combinations of technologies analysed here contrasts trade-offs and is a first in the literature. The capital costs of these projects are considered, giving insights into their business case. Results indicate that electric heaters are not cost-competitive in supermarkets. Meanwhile, RIHC and ASHP configurations are the most attractive option, and if a thermal storage tank system with advanced controls is included, the benefits increase even further. Best solutions have a 6.3% ROI, a payback time of 16 years while reducing energy demand by 62% and CO 2 emissions by 54%. Such investments will be difficult to justify unless policy steers decision makers through incentives or the business case changes by implementing internal carbon pricing. [ABSTRACT FROM AUTHOR]

• Assessed CO 2 shipping as a global decarbonisation strategy for future developments. • Identified technical and safety challenges encountered during in CO 2 shipping chain. • Evaluated the environmental impact of shipping emissions in the transport chain. • Summarised emission control technologies as a key enabler in the CO 2 shipping chain. Carbon Capture, Utilisation and Storage (CCUS) can reduce greenhouse gas emissions for a range of technologies which capture CO 2 from a variety of sources and transport it to permanent storage locations such as depleted oil fields or saline aquifers or supply it for use. CO 2 transport is the intermediate step in the CCUS chain and can use pipeline systems or sea carriers depending on the geographical location and the size of the emitter. In this paper, CO 2 shipping is critically reviewed in order to explore its techno-economic feasibility in comparison to other transportation options. This review provides an overview of CO 2 shipping for CCUS and scrutinises its potential role for global CO 2 transport. It also provides insights into the technological advances in marine carrier CO 2 transportation for CCUS, including preparation for shipping, and in addition investigates existing experience and discusses relevant transport properties and optimum conditions. Thus far, liquefied CO 2 transportation by ship has been mainly used in the food and brewery industries for capacities varying between 800 m3 and 1000 m3. However, CCUS requires much greater capacities and only limited work is available on the large-scale transportation needs for the marine environment. Despite most literature suggesting conditions near the triple-point, in-depth analysis shows optimal transport conditions to be case sensitive and related to project variables. Ship-based transport of CO 2 is a better option to decarbonise dislocated emitters over long distances and for relatively smaller quantities in comparison to offshore pipeline, as pipelines require a continuous flow of compressed gas and have a high cost-dependency on distance. Finally, this work explores the potential environmental footprint of marine chains, with particular reference to the energy implications and emissions from ships and their management. A careful scrutiny of potential future developments highlights the fact, that despite some existing challenges, implementation of CO 2 shipping is crucial to support CCUS both in the UK and worldwide. [ABSTRACT FROM AUTHOR]

Although the penetration of renewable energy in power systems has been substantially increased globally in the last decade, fossil fuels are still important in providing the essential flexibility required to reliably maintain the system balance. In 2019, more than one quarter of power generation in Europe and over 40% of the UK's electricity generation was from fossil fuels (mainly gas). For achieving the net-zero greenhouse gas emission target around the middle of this century, these fossil fuels have to be decarbonised in the coming decades. Bulk-scale energy storage has been recognised as a key technology to overcome the reduced dispatchability associated with the decrease of fossil fuels in generation. Taking the UK power system as a case study, this paper presents an assessment of geological resources for bulk-scale compressed air energy storage (CAES), and an optimal planning framework for CAES in combination with solar and wind to replace fossil fuels in the power generation system. The analysis reveals up to 725 GWh of ready-to-use capacity by utilising existing underground salt caverns in the UK. These potential CAES sites with added solar and wind generation equal to the generation from fossil fuels in 2018 can reduce carbon emissions by 84% with a cost increase by 29%, compared to the system in 2018. The results indicate the plausibly achievable cost-effectiveness of CAES as bulk-scale energy storage for power system decarbonisation in countries the geological resources are available. [ABSTRACT FROM AUTHOR]