Evaluating the effects of social interactions on a distributed demand side management system for domestic appliances

In the presence of time-variable energy tariffs, users will try to schedule the usage of their electrical appliances with the goal of minimising their bill. If the variable price component depends on the peak aggregate demand during each given hour, users will be incentivised to redistribute their consumption during the day, thus lowering the overall peak consumption. The process can be automated by means of an Energy Management System that chooses the best schedule while satisfying the user's constraints on the maximum tolerable delays. In turn, users' thresholds on delay tolerance may slowly change over time. In fact, users may be willing to modify their threshold to match the threshold of their social group, especially if there is evidence that friends with a more flexible approach have paid a lower bill. We provide an algorithmic framework that models the effect of social interactions in a distributed demand side management system and show that such interactions can increase the flexibility of users' schedules and lower the peak power, resulting in a smoother usage of energy throughout the day. Additionally, we provide an alternative description of the model by using Markov Chains and study the corresponding convergence times. We conclude that the users reach a steady state after a limited number of interactions

Managing complexity in the smart grid through a new approach to demand response

CASCADE was a consortium project with Cranfield UniversityAdoption of weather-dependent renewable generation of electricity has introduced additional complexity to the challenge of maintaining a dynamic equilibrium between generation and electricity demand. At the same time the need for electricity to power heating and transport in place of fossil fuels will lead to congestion in distribution networks. Part of the solution will be to manage domestic electricity demand using signals between the smart grid and smart home, but this must be done in a way that does not provoke further instability. We use an agent-based model of household electricity consumption and supply to show how the complexity of domestic demand can be shaped allowing it to make a contribution to system stability. A possible role for this method in balancing conflicting interests between electricity consumers, suppliers, and distribution network operators is discussedEPSRC under the CASCADE project (EP/GO59969/1

Interactive Demand Shifting in the context of Domestic Micro-Generation

The combination of ubiquitous computing and emerging energy technologies is radically changing the home energy landscape. Domestic micro-generation, dominated by solar photovoltaic, is increasing at a rapid pace. This represents an opportunity for creating and altering energy behaviours. However, these transformations generate new challenges that we call the domestic energy gap: domestic electricity consumption and microgeneration are out of sync. Micro-generation is mainly uncontrollable production relying on weather while domestic energy consumption tends to happen mostly during the evening. This thesis focuses on understanding and supporting new domestic practices in the context of domestic solar electricity generation, looking at ‘Demand-Shifting’. Specifically, we look at how can digital tools leverage Demand-Shifting practices in the context of domestic micro-generation? Relying on a mixed-method approach, we provide a qualitative and quantitative answer with the collaboration of 38 participating households in several field studies including two spanning more than eight months. Through a deep investigation of laundry and electric mobility routines in the context of domestic micro-generation, we emphasised a natural engagement into Demand-Shifting which appeared as a complex and time-consuming task for participants which was not visible when we analysed their quantitative data. We revealed this complexity through Participatory Data Analyses, a method we designed to analyse the data in collaboration with the participating householders. This provided us with a comprehensive view of the relationship between domestic micro-generation and daily routines. Finally, we highlight the need for timely and contextual support through the deployment of interventions in-the-wild. Building on discussions of our findings in perspective of the literature, we propose a conceptual framework to support domestic interactive Demand-Shifting

Ties That Bind: the emergence of entrepreneurs in China

The paper describes the emergence of entrepreneurship in Shanxi province based on fieldwork in the last 6 years. Employing institutional and evolutionary economics shows that both the kind of firms that emerge and the individual behaviour of entrepreneurs reflect a systematic response to the situational constraint all would-be entrepreneurs face, namely a high level of uncertainty and weak institutions. In this situation to establish firms with a weak organisational identity allows to flexibly respond to new opportunities, while a strong reputation for accountability of the owners and managers is needed to get long term business relations started. As the Shanxi sample shows accountability can be achieved by a mix of reviving old economic institutions, hijacking social organisations, and building new business practices. To the extent that old institutions, social organisations and business practices do not spread equally across China, different forms of firms and different forms of entrepreneurship can be expected within China. In short, local cultures matter.evolutionary economics;organisational change;dealing with uncertainty and risk

Development of colletive intelligence for building energy efficiency

Energy consumption in the building sector is continuously increasing. In response to this situation, optimal collaborative action strategies aimed at improving building energy efficiency with human and building technical systems have become increasingly important. Collaborative actions which this research addresses focus on the interaction between humans and technical systems in a building environment. Most studies on building energy efficiency have dealt with the development of technical systems and lacked consideration of the complex socio-technological interface and collective efforts between technical systems and humans. This research aims to fill the gap by developing an innovative collective intelligence model to enable collective efforts by both building energy systems and people to achieve a greater energy saving. In this model, building energy systems and people are represented by intelligent agents, while genetic algorithms (GAs) are integrated into multi-agent modules to enable self-organization of energy efficient actions in order to achieve optimal energy consumption. The utility of the innovative collective intelligence model is further investigated through a multi-unit apartment building in the Australian context. As an example, the results of the prototype show that building energy performance can be significantly improved by using the proposed collective intelligence model compared to the baseline energy consumption of the building. This research links humans and collective intelligence with building energy systems to tackle energy efficiency problems in the built environment. Research outcomes will advance cross-disciplinary knowledge about the utilisation of artificial intelligence technologies for enhancing energy efficiency and sustainability in the built environment

Scenarios for the development of smart grids in the UK: literature review

Smart grids are expected to play a central role in any transition to a low-carbon energy future, and much research is currently underway on practically every area of smart grids. However, it is evident that even basic aspects such as theoretical and operational definitions, are yet to be agreed upon and be clearly defined. Some aspects (efficient management of supply, including intermittent supply, two-way communication between the producer and user of electricity, use of IT technology to respond to and manage demand, and ensuring safe and secure electricity distribution) are more commonly accepted than others (such as smart meters) in defining what comprises a smart grid. It is clear that smart grid developments enjoy political and financial support both at UK and EU levels, and from the majority of related industries. The reasons for this vary and include the hope that smart grids will facilitate the achievement of carbon reduction targets, create new employment opportunities, and reduce costs relevant to energy generation (fewer power stations) and distribution (fewer losses and better stability). However, smart grid development depends on additional factors, beyond the energy industry. These relate to issues of public acceptability of relevant technologies and associated risks (e.g. data safety, privacy, cyber security), pricing, competition, and regulation; implying the involvement of a wide range of players such as the industry, regulators and consumers. The above constitute a complex set of variables and actors, and interactions between them. In order to best explore ways of possible deployment of smart grids, the use of scenarios is most adequate, as they can incorporate several parameters and variables into a coherent storyline. Scenarios have been previously used in the context of smart grids, but have traditionally focused on factors such as economic growth or policy evolution. Important additional socio-technical aspects of smart grids emerge from the literature review in this report and therefore need to be incorporated in our scenarios. These can be grouped into four (interlinked) main categories: supply side aspects, demand side aspects, policy and regulation, and technical aspects.

The potential contribution of disruptive low-carbon innovations to 1.5 °C climate mitigation

This paper investigates the potential for consumer-facing innovations to contribute emission reductions for limiting warming to 1.5 °C. First, we show that global integrated assessment models which characterise transformation pathways consistent with 1.5 °C mitigation are limited in their ability to analyse the emergence of novelty in energy end-use. Second, we introduce concepts of disruptive innovation which can be usefully applied to the challenge of 1.5 °C mitigation. Disruptive low-carbon innovations offer novel value propositions to consumers and can transform markets for energy-related goods and services while reducing emissions. Third, we identify 99 potentially disruptive low-carbon innovations relating to mobility, food, buildings and cities, and energy supply and distribution. Examples at the fringes of current markets include car clubs, mobility-as-a-service, prefabricated high-efficiency retrofits, internet of things, and urban farming. Each of these offers an alternative to mainstream consumer practices. Fourth, we assess the potential emission reductions from subsets of these disruptive low-carbon innovations using two methods: a survey eliciting experts’ perceptions and a quantitative scaling-up of evidence from early-adopting niches to matched segments of the UK population. We conclude that disruptive low-carbon innovations which appeal to consumers can help efforts to limit warming to 1.5 °C

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

Enhancing the efficiency of electricity utilization through home energy management systems within the smart grid framework

The concept behind smart grids is the aggregation of “intelligence” into the grid, whether through communication systems technologies that allow broadcast/data reception in real-time, or through monitoring and systems control in an autonomous way. With respect to the technological advancements, in recent years there has been a significant increment in devices and new strategies for the implementation of smart buildings/homes, due to the growing awareness of society in relation to environmental concerns and higher energy costs, so that energy efficiency improvements can provide real gains within modern society. In this perspective, the end-users are seen as active players with the ability to manage their energy resources, for example, microproduction units, domestic loads, electric vehicles and their participation in demand response events. This thesis is focused on identifying application areas where such technologies could bring benefits for their applicability, such as the case of wireless networks, considering the positive and negative points of each protocol available in the market. Moreover, this thesis provides an evaluation of dynamic prices of electricity and peak power, using as an example a system with electric vehicles and energy storage, supported by mixed-integer linear programming, within residential energy management. This thesis will also develop a power measuring prototype designed to process and determine the main electrical measurements and quantify the electrical load connected to a low voltage alternating current system. Finally, two cases studies are proposed regarding the application of model predictive control and thermal regulation for domestic applications with cooling requirements, allowing to minimize energy consumption, considering the restrictions of demand, load and acclimatization in the system