Towards sustainable production and consumption: A novel DEcision-Support Framework IntegRating Economic, Environmental and Social Sustainability (DESIRES)

AbstractThe idea of sustainable production and consumption is becoming a widely-accepted societal goal worldwide. However, its implementation is slow and the world continues to speed down an unsustainable path. One of the difficulties is the sheer complexity of production and consumption systems that would need to be re-engineered in a more sustainable way as well as the number of sustainability constraints that have to be considered and satisfied simultaneously. This paper argues that bringing about sustainable production and consumption requires a systems approach underpinned by life cycle thinking as well as an integration of economic, environmental and social aspects. In an attempt to aid this process, a novel decision-support framework DESIRES has been developed comprising a suite of tools, including scenario analysis, life cycle costing, life cycle assessment, social sustainability assessment, system optimisation and multi-attribute decision analysis. An application of the framework is illustrated by a case study related to energy

Time-of-use and time-of-export tariffs for home batteries: Effects on low voltage distribution networks

Time-of-use electricity tariffs are gradually being introduced around the world to expose consumers to the time-dependency of demand, however their effects on peak flows in distribution networks, particularly in areas with domestic energy storage, are little understood. This paper presents investigations into the impact of time-of-use and time-of-export tariffs in residential areas with various penetrations of battery storage, rooftop solar PV, and heat pumps. By simulating battery operation in response to high resolution household-level electrical and thermal demand data, it is found that home batteries operating to maximise cost savings in houses signed up to time-dependent tariffs cause little reduction in import and export peaks at the low voltage level, largely because domestic import and export peaks are spread out over time. When operating to maximise savings from the first three-tier time-of-use tariff introduced in the UK, batteries could even cause increases in peak demand at low voltage substations, if many batteries in the area commence charging at the start of the overnight off-peak price band. Home batteries operating according to time-dependent electricity tariffs significantly miss out on the potential peak shaving that could otherwise be achieved through dedicated peak shaving incentives schemes and smarter storage control strategies

The potential for peak shaving on low voltage distribution networks using electricity storage

Co-location of energy storage with demand provides several benefits over other locations, while still being able to provide balancing services to the grid. One of these additional benefits is deferral of distribution infrastructure reinforcement, allowing increased load growth. This paper considers the potential of electricity storage for peak shaving on distribution networks, focusing on residential areas. A demand model is used to synthesise high resolution domestic load profiles, and these are used within Monte Carlo analysis to determine how much peak shaving could be achieved with storage. An efficient method of finding the potential peak shaving using electricity storage is developed for this purpose. It is shown that moderate levels of storage capacity can deliver significant demand reductions, if suitably coordinated and incentivised. With 2 kWh of battery storage per household, the peak demand at low voltage substations could potentially be halved. The effects of PV capacity, household size and C rates are considered. With 3 kW PV per house, 4.5 kWh of batteries could keep peak flows at the same level as before the addition of PV. It is also shown that 3 kWh of battery storage per household could allow provision of all heating from heat pumps without increasing t he peak demand

A multi-period mixed-integer linear optimisation of future electricity supply considering life cycle costs and environmental impacts

AbstractA multi-period mixed-integer linear programming model has been developed to help explore future pathways for electricity supply where costs and carbon reduction are a priority. The model follows a life cycle approach and can optimise on costs and on a number of environmental objectives. To illustrate the application, the model has been optimised on two objectives: whole system costs and global warming potential (GWP) using the UK as an example. Four different scenarios have been considered up to 2060, each assuming different electricity demand and carbon reduction targets. When optimising on system costs, they range from £156.6bn for the least carbon-constrained scenario with moderate increase in electricity demand to £269.9bn for the scenario with high demand and requiring 100% decarbonisation of electricity supply by 2035. In optimisation on GWP, negative carbon emissions are achieved in all scenarios, ranging from −0.5 to −1.28 Gt CO2 eq. over the period, owing to biomass carbon capture and storage. Optimising on the GWP also reduces significantly other environmental impacts at costs comparable to optimised costs. This research shows that meeting carbon targets will require careful planning and consideration of objectives other than costs alone to ensure that optimal rather than suboptimal solutions are found for a more sustainable electricity supply

Insight Report: Domestic Time of Use Tariff: A comparison of the time of use tariff trial to the baseline domestic profiles

Peak electricity demand poses a particular challenge both to network operators and to energy suppliers. A reduction in peak demand would allow existing networks to accommodate load growth with lower investment, and also reduce the cost of electricity generation during peak periods. To explore the potential for peak reduction, the Customer-Led Network Revolution project has trialled a Time of Use (ToU) tariff scheme. By increasing electricity prices during the weekday peak period (4pm-8pm) for throughout the year and reducing prices in off-peak periods, the tariff incentivises a shift in consumption out of the peak period. A static ToU tariff was used – that is, the tariff remained constant and did not change dynamically depending on expected network loading. Based on smart meter data and survey responses, test cell (TC) 9a investigated the electricity use patterns of 574 domestic users on a ToU tariff between October 2012 and September 2013 and compared them to those of the control group (test cell 1a). The impact of demographic profile on customers’ responses to the ToU tariff was also considered. On average, when compared to consumers in the control cell TC1a, customers on the ToU tariff had lower consumption during the peak period on weekdays, and higher consumption at other times – indicating that the tariff achieved the intended behaviour change. There was a small net reduction (0.8%) in annual consumption, although this was not enough to be statistically significant. In particular, the trial showed; Lower electricity consumption during the peak periods (between 1.5% and 11.3% less than TC1a). This is in line with our qualitative research where customers claim changing time of use of certain appliances. Lower average peak power demands1 during the peak period (between 3.2% and 12.5% lower than TC1a when averaged throughout the year and across all customers). On average, customers showed a lower maximum half-hourly peak demand (between 2.1% – 10.3% lower than TC1a) during the peak period. However at the time of greatest system peak demand – specifically a single half-hour in the year there was no (statistically significant) difference in the mean peak demand observed between TC9a and TC1

High Level Summary of Learning: Heat Pump Customers

This summary presents the key messages from the final analysis of the domestic heat pump group (test cell 3) in the Customer-Led Network Revolution monitoring trials. It presents outputs from the largest study of household electricity use in the UK and provides integrated socio-technical analysis of domestic customer loads and electrical consumption on the basis of interdisciplinary multi-method research. This report draws on qualitative interviews and home energy tours conducted with 18 households recruited from the 331 domestic customers involved in the CLNR air-source-to-water heat pump (ASWHP) trial (Test Cell 3). Participants with ASWHP were contacted directly by one of the research team, using information provided by the energy retailer, which had previously identified households that were willing to participate. The semi-structured interviews focused on building rapport with the participant while discussing their energy use in general terms. These conversations included information about occupancy, major electrical loads, heating regimes, washing and cooking practices, thoughts and feelings about electricity use, seasonality and other temporal factors as well as experiences of and responses to new technologies. Interviews were focused on two clusters within the regional network: social housing tenants in South Tyneside and County Durham. Social housing landlords had installed loft and wall insulation, where feasible, and retrofitted an ASWHP at no cost to the tenants. Interview participants had lived with the ASWHP for between 6-12 months, including the winter months. Interviews were conducted between January and March 2013