Demand response within the energy-for-water-nexus - A review. ESRI WP637, October 2019

A promising tool to achieve more flexibility within power systems is demand re-sponse (DR). End-users in many strands of industry have been subject to research up to now regarding the opportunities for implementing DR programmes. One sector that has received little attention from the literature so far, is wastewater treatment. However, case studies indicate that the potential for wastewater treatment plants to provide DR services might be significant. This review presents and categorises recent modelling approaches for industrial demand response as well as for the wastewater treatment plant operation. Furthermore, the main sources of flexibility from wastewater treatment plants are presented: a potential for variable electricity use in aeration, the time-shifting operation of pumps, the exploitation of built-in redundan-cy in the system and flexibility in the sludge processing. Although case studies con-note the potential for DR from individual WWTPs, no study acknowledges the en-dogeneity of energy prices which arises from a large-scale utilisation of DR. There-fore, an integrated energy systems approach is required to quantify system and market effects effectively

Fast charging stations with stationary batteries: A techno-economic comparison of fast charging along highways and in cities

Fast charging infrastructure is widely acknowledged as necessary for the market success of electric vehicles. However, fast charging requires cost intensive infrastructure and grid connections. Accordingly, the risk of sunk cost is high, although fast charging infrastructure might be profitable in the medium to long term. In addition, the demand for fast charging varies greatly and the maximum power of charging stations may only be needed for a short time period per week. Although the profitability of stationary storages and the demand for fast charging have gained broad attention in literature, the specific question of how and under what circumstances stationary batteries can increase the profitability of fast charging stations has not yet been addressed for all potential applications. Here, we analyze the extent to which stationary storages can increase the profitability of fast charging stations by reduced grid connection costs on the one hand and additional revenues from intraday trading of electricity on the other hand. We compare different battery technologies and distinguish two use cases: fast charging in cities and along highways. Our results indicate that the profitability of a stationary storage installed together with a fast charging station depends on various parameters. While for a city fast charging station, intraday trading might lead to lower cost, this is not the case for highway stations since the heavy use motivated by intraday trading can significantly shorten battery life. Our results underline the importance of second life batteries since low-cost batteries have a significant impact on the system’s profitability

The shape of days to come : effects of climate change on building energy consumption

Climate change effects vary with region, season, and time of the day. Existing annual and diurnal temperature cycles will shift and be reshaped, leading to increased air temperatures earlier and later in the year. Buildings will be affected by these changes, especially the ones using passive design strategies, whose performance is highly weather dependent. Building energy simulation (BES) is key for building energy design and optimization. Since most buildings last 50+ years, BES must use future weather data accounting for climate change. Presently, photovoltaic (PV) energy self-consumption must be maximized through building demand flexibility and energy storage, because of grid and economic interests. However, clouds can shade PV systems, reducing production and increasing grid demand, particularly in the cooling season. This thesis addresses three complementary research topics that build on the use of high-resolution state-of-the-art historical and future climate data. First, two methods to produce future climate data for BES are compared. Secondly, upcoming changes in temperature, their interaction with solar radiation, and the consequent impacts on passive building strategies are analysed in the EU 43 most populated cities. Finally, cloud shading periods capable of triggering demand flexibility events are analysed and simulated. The results show that current methods used to produce future climate data for BES, produce reliable results when correctly applied. Upcoming climate change will impact diurnal temperature cycle by increasing or decreasing the daily temperature range depending on season and region. Further, natural ventilation and shading seasons will be affected, with a higher impact on energy consumption in Southern Europe. Finally, cloud shading periods vary with climate but, on average, clouds last 20 minutes and occur predominately in the afternoon. The simulation results show that grid energy demand can be reduced by 60 % while maintaining comfortable indoor conditions

Water consumption in industrial and energy processes

openAnalysis of water consumption and impacts in various industrial sectors and processes, including energy productio

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

An analysis of storage revenues from the time-shifting of electrical energy in Germany and Great Britain from 2010 to 2016

The purpose of this paper is to investigate the level of revenues available to storage operators through the bulk time-shifting of electrical energy in Germany and Great Britain over the 7 years from 2010 to 2016, and to analyse the impact of volatility and underlying mean price on the potential revenues that a storage operator could theoretically capture. The analysis is carried out using an algorithm adapted from previous work, coupled with new empirical hourly price data from the German and Great British day-ahead electrical markets, and using characteristics typical of a pumped-storage hydropower scheme (1000 MWh, 125 MW charge and discharge, and 75% round-trip efficiency). Our results suggest that volatility rather than average price is the dominant factor affecting storage revenues, with a 1% increase in volatility implying an increase in mean daily storage revenues of €300 in Germany and £550 in Great Britain for the simulated storage plant. In comparison, an increase in underlying mean prices of €1 per MWh leads to an increase in mean daily revenue of €100 in Germany, with a £1 per MWh increase in underlying mean prices leading to an increase in mean daily revenue of £380 in Great Britain. We also find that during the period 2010–2016, the times when the highest revenue is derived have moved from late morning to early evening, which we attribute to the increase in low short-run marginal cost solar PV electricity in both markets suppressing the day-ahead wholesale electrical prices. In addition, we find a large increase in storage operator revenues in Britain in the last quarter of 2016, due to a number of events that impacted the price of electricity, however these would have been difficult to predict with any degree of certainty. This paper therefore highlights the perennial problem of forecasting the time-shifting revenue for electrical energy, with its high degree of variation from one year to the next that would undoubtedly impact the financing of these capital-intensive projects that seek to capture these variable revenues

Low Carbon Futures: confronting electricity challenges on island systems

This paper considers the range of possible long-term futures for an electrically isolated island power system. Emphasis is given to generation investment decisions supportive of low-carbon renewable generation. Ranges of policy interventions are considered for the electrically isolated case study island of São Miguel in the Azores islands in the North Atlantic Ocean. The whole systems methodological approach of System Dynamics is used to bring together key sub-systems relating to, for example, generation adequacy, renewable generation investments and demand-side aspects. In this way, a comprehensive understanding is established with high levels of endogeneity. The model is used to investigate a range of policy scenarios associated with renewable energy growth, electric-vehicle uptake and electricity storage. It is found that policy is most effective when all aspects are addressed simultaneously and in a co-ordinated manner and that policy favouring renewable generation alone is not sufficient to achieve the highest possible penetration of renewables. Finally, the robustness of the observations is addressed via Monte-Carlo based sensitivity testing