Future directions for scientific advice in Europe

Across Europe, scientific evidence and advice is in great demand, to inform policies and decision making on issues such as climate change, new technologies and environmental regulation. But the diversity of political cultures and attitudes to expertise in different European countries can make the task of designing EU-wide advisory institutions and processes both sensitive and complex. In January 2015, President Juncker asked Commissioner Moedas to report on options for improving scientific advice within the European Commission. At a time when these issues are higher than usual on the political agenda, it is important that the case for scientific advice and evidence-informed policy is articulated and analysed afresh. To support these efforts, this collection brings together agenda-setting essays by policymakers, practitioners, scientists and scholars from across Europe. Authors include Anne Glover, Ulrike Felt, Robert Madelin, Andy Stirling, Vladimír Šucha and Jos van der Meer. Their contributions outline various challenges but also constructive ways forward for scientific advice in Europe

Artificial Intelligence and Machine Learning Approaches to Energy Demand-Side Response: A Systematic Review

Recent years have seen an increasing interest in Demand Response (DR) as a means to provide flexibility, and hence improve the reliability of energy systems in a cost-effective way. Yet, the high complexity of the tasks associated with DR, combined with their use of large-scale data and the frequent need for near real-time de-cisions, means that Artificial Intelligence (AI) and Machine Learning (ML) — a branch of AI — have recently emerged as key technologies for enabling demand-side response. AI methods can be used to tackle various challenges, ranging from selecting the optimal set of consumers to respond, learning their attributes and pref-erences, dynamic pricing, scheduling and control of devices, learning how to incentivise participants in the DR schemes and how to reward them in a fair and economically efficient way. This work provides an overview of AI methods utilised for DR applications, based on a systematic review of over 160 papers, 40 companies and commercial initiatives, and 21 large-scale projects. The papers are classified with regards to both the AI/ML algorithm(s) used and the application area in energy DR. Next, commercial initiatives are presented (including both start-ups and established companies) and large-scale innovation projects, where AI methods have been used for energy DR. The paper concludes with a discussion of advantages and potential limitations of reviewed AI techniques for different DR tasks, and outlines directions for future research in this fast-growing area

Mitigating exclusionary greening of South African cities through participation of indigent households in renewable energy: the case of Galeshwe settlement in Sol Plaatjie municipality, South Africa

A research report submitted to the Faculty of Engineering and Built Environment, University of the Witwatersrand, in partial fulfilment of the requirements for the degree of Masters of Architecture in the field of Sustainable and Energy Efficient Cities Johannesburg May 2018Based on the Sol Plaatje Municipality case study, this study focuses on how an innovative municipal business and funding approach could serve as a tool for transitioning from fossil fuels to renewable energy (solar) for the benefit of both indigent households and the municipality. Primary data from the municipality and indigent households in Galeshewe settlement indicates that in its current form, the 50kWh free basic electricity that indigent households receive monthly from the municipality is insufficient for their basic energy needs, while purchasing additional electricity is becoming increasingly unaffordable. This results in suppressed demand for the households and ongoing risk to the municipality due to escalating costs. In mitigation of the two fundamental challenges, findings from primary and secondary data have guided the study to the Renewable Energy for Low Income Earners (RELIE) model. The Equitable Share Grant and Integrated National Electrification Programme Grant (as currently allocated to municipalities by National Treasury and the Department of Energy for free basic electricity and electricity infrastructure provision for low income households) are highlighted as the initial funding channels under the proposed model based on a backcasting approach. Municipal energy plans and policies as well as integrated human settlements’ spatial plans also emerge as critical tools for transitioning to inclusionary RE. Other funding sources in the RELIE model include existing government funds such as the Green Fund and the Central Energy Fund from the Department of Environmental Affairs, as well as supplementary funds from relevant agencies such as climate funding entities and philanthropic socially responsive investments. The model also envisages end-user contribution through affordable payments for service. In conclusion, the study recommends that the RELIE model findings could be adapted for other municipalities in South Africa faced with the escalating indigent household energy crisis.MT 201

Emerging technologies for learning (volume 1)

Collection of 5 articles on emerging technologies and trend

A socio-technical evaluation of the impact of energy demand reduction measures in family homes

Energy consumption in the home depends on appliance ownership and use, space heating systems, control set-points and hot water use. It represents a significant proportion of national demand in the UK. The factors that drive the level of consumption are a complex and interrelated mix of the numbers of people in the home, the building and system characteristics as well as the preferences for the internal environment and service choices of occupants. Reducing the energy demand in the domestic sector is critical to achieving the national 2050 carbon targets, as upward of 60% reduction in demand is assumed by many energy system scenarios and technology pathways. The uptake of reduction measures has been demonstrated to be quite ad hoc and intervention studies have demonstrated considerable variation in the results. Additionally, a limitation of many studies is that they only consider one intervention, whereas a more holistic approach to the assessment of the potential of reduction measures in specific homes may yield a better understanding of the likely impact of measures on the whole house consumption and indeed would shed light on the appropriateness of the assumptions that underpin the decisions that need to be made regarding the future energy supply system and demand strategies. This work presents a systematic approach to modelling potential reductions for a set of seven family homes, feeding back this information to householders and then evaluating the likely reduction potential based on their responses. Carried out through a combination of monitoring and semi-structured interviews, the approach develops a methodology to model energy reduction in specific homes using monitoring data and steady-state heat balance principles to determine ventilation heat loss, improving the assumptions within the energy model regarding those variables affected by human behaviour. The findings suggest that the anticipated reductions in end use energy demand in the domestic sector are possible, but that there is no `one size fits all' solution. A combination of retrofitting and lifestyle change is needed in most homes and smart home technology may potentially be useful in assisting the home owner to achieve reductions where they are attempting to strike a balance between energy efficiency, service and comfort

Bioenergy and Minigrids for Sustainable Human Development

Human-caused climate change and deep disparities in human development imperil a prosperous and just future for our planet and the people who live on it. Transforming our society to mitigate global warming offers an opportunity to rebuild energy systems to the benefit of those who are harmed by global inequality today. I examine this opportunity through the lens of two sustainable energy technologies: bioenergy and miniature electricity grids (minigrids). Bioenergy requires land to produce biomass and is inextricably connected to the surrounding environment, agricultural livelihoods, and food system. I apply data science tools to study aspects of land use and food security that may intersect with increasing bioenergy production. I assess the potential to use over one billion hectares of grazing land more intensively with an empirical yield gap analysis technique called climate binning. To clarify how agricultural and socioeconomic characteristics relate to national food security, I study the relative importance of several drivers using simple linear regressions with cross validation and random sampling techniques. Minigrids can supply clean, reliable electricity to un- and under-served communities, but small and hard-to-predict customer loads hamper their financial viability. To improve predictions of daily electricity demand of prospective customers, I test a data-driven approach using customer demographic surveys and machine learning models. I also investigate opportunities to grow loads by stimulating income-generating uses of minigrid electricity in twelve Nigerian agricultural value chains. I conclude by emphasizing the fundamental complementarity of energy and agriculture as change levers for human development, especially in rural communities with low energy access and high poverty. I also provide recommendations to support the effective use of energy to solve pressing agricultural problems and drive multiplicative human development benefits

Agent-based models for residential energy consumption and intervention simulation

The increase in energy consumption in buildings has gained global concern due to its negative implications on the environment. A major part of this increase is attributed to human behavioural energy waste, which has triggered the development of energy simulation models. These models are used to analyse energy consumption in buildings, study the effect of human behaviour and test the effectiveness of energy interventions. However, existing models are limited in simulating realistic and detailed human dynamics, including occupant interaction with appliances, with each other or with energy interventions. This detailed interaction is important when simulating and studying behavioural energy waste. To overcome the limitations of existing models, this thesis proposes a complete layered Agent-Based Model (ABM) composed of three layers / models. The daily behaviour model simulates realistic and detailed behaviour of occupants by integrating a Probabilistic Model (PM) in the ABM. The peer pressure model simulates family-level peer pressure effect on the energy consumption of the house. This model is underpinned using well established human behaviour theories by Leon Festinger – informal social communication theory, social comparison theory and cognitive dissonance theory. The messaging intervention model implements and tests a novel messaging intervention that is proposed in the thesis along with the complete ABM. The intervention is a middle solution between the abstract data presented by existing energy feedback systems and the automated approach followed by existing energy management systems. Therefore, it detects and sends energy waste incidents to occupants who are allowed to take control of their devices. The proposed intervention is tested in the messaging intervention model, which takes advantage of the two other proposed models. The undertaken experiments showed that the model is able to overcome the limitations of exiting models by simulating realistic and detailed human behaviour dynamics. Besides, the experiments showed that the model can be used by policy makers to decide how to target family members to achieve optimal energy saving, thus addressing the world’s concern about increased energy consumption levels

Smart Energy Management for Smart Grids

This book is a contribution from the authors, to share solutions for a better and sustainable power grid. Renewable energy, smart grid security and smart energy management are the main topics discussed in this book