Assessing heat pumps as flexible load

In a future power system featuring significant renewable generation, the ability to manipulate domestic demand through the flexible operation of heat-led technologies such as heat pumps and micro-combined heat and power could be a critical factor in providing a secure and stable supply of electrical energy. Using a simulation-based approach, this study examined the linkage between the thermal characteristics of buildings and the scope for flexibility in the operating times of air source heat pumps. This was assessed against the resulting impact on the end-user’s comfort and convenience. A detached dwelling and flat were modelled in detail along with their heating system in order to determine the temporal shift achievable in the heat pump operating times for present-day and future dwellings. The simulation results indicated that the scope for shifting heat pump operating times in the existing building stock was limited, with time shifts of only 1–2 h achieved before there was a serious impact on the comfort of the occupant. However, if insulation levels were dramatically improved and substantial levels of thermal buffering were added into the heating system, sizable time shifts of up to 6 h were achievable without a significant impact on either space or hot water temperatures

Performance assessment of tariff-based air source heat pump load shifting in a UK detached dwelling featuring phase change-enhanced buffering

Using a detailed building simulation model, the amount of thermal buffering, with and without phase change material (PCM), needed to time-shift an air source heat pump's operation to off-peak periods, as defined by the UK 'Economy 10' tariff, was investigated for a typical UK detached dwelling. The performance of the buffered system was compared to the case with no load shifting and with no thermal buffering. Additionally, the load shifting of a population of buffered heat pumps to off-peak periods was simulated and the resulting change in the peak demand on the electricity network was assessed. The results from this study indicate that 1000 L of hot water buffering or 500 L of PCM-enhanced hot water buffering was required to move the operation of the heat pump fully to off-peak periods, without adversely affecting the provision of space heating and hot water for the end user. The work also highlights that buffering and load shifting increased the heat pump's electrical demand by over 60% leading to increased cost to the end user and increased CO2 emissions (depending on the electricity tariff applied and time varying CO2 intensity of the electricity generation mix, respectively). The study also highlights that the load-shifting of populations of buffered heat pumps wholly to off-peak periods using crude instruments such as tariffs increased the peak loading on the electrical network by over 50% rather than reducing it and that careful consideration is needed as to how the load shifting of a group of heat pumps is orchestrated

Management and Control of Domestic Smart Grid Technology

Emerging new technologies like distributed generation, distributed storage, and demand-side load management will change the way we consume and produce energy. These techniques enable the possibility to reduce the greenhouse effect and improve grid stability by optimizing energy streams. By smartly applying future energy production, consumption, and storage techniques, a more energy-efficient electricity supply chain can be achieved. In this paper a three-step control methodology is proposed to manage the cooperation between these technologies, focused on domestic energy streams. In this approach, (global) objectives like peak shaving or forming a virtual power plant can be achieved without harming the comfort of residents. As shown in this work, using good predictions, in advance planning and real-time control of domestic appliances, a better matching of demand and supply can be achieved.\ud \u

Smart and flexible electric heat: an energy futures lab briefing paper

Heating in residential, commercial and industrial settings makes up almost half of final energy consumption in the UK, more than the energy consumed for electricity or transport. The electrification of heat is anticipated to play a major role for the UK’s efforts to reduce emissions to net-zero by 2050. Heating demand is highly variable between seasons and time of day. To take maximum advantage of low-carbon generation, and to respect the limitations of the distribution grid, electricity loads for heating will need to be flexible. This Briefing Paper explores the potential for smart flexible low-carbon electric heating in UK homes and the challenges for consumer engagement. This paper considers four key elements for enabling smart, flexible and cost- effective electric heating in UK homes: low-carbon heating systems; cost-reflective electricity pricing; thermally efficient buildings; and smart storage devices

A Three-Step Methodology to Improve Domestic Energy Efficiency

Increasing energy prices and the greenhouse effect lead to more awareness of energy efficiency of electricity supply. During the last years, a lot of technologies have been developed to improve this efficiency. Next to large scale technologies such as windturbine parks, domestic technologies are developed. These domestic technologies can be divided in 1) Distributed Generation (DG), 2) Energy Storage and 3) Demand Side Load Management. Control algorithms optimizing a combination of these techniques can raise the energy reduction potential of the individual techniques. In this paper an overview of current research is given and a general concept is deducted. Based on this concept, a three-step optimization methodology is proposed using 1) offline local prediction, 2) offline global planning and 3) online local scheduling. The paper ends with results of simulations and field tests showing that the methodology is promising.\u

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.