Abstract:predominantly in decentralized settings located close to consumers. This creates a shift in the energy sector toward decentralized (or distributed) generation with smaller production units (Alanne & Saari, 2006). The primary challenge of using renewable energy technologies, such as wind and solar PV, is their highly intermittent and weather-dependent power output. Therefore, to match generation with load, additional measures for flexibility and balance are required. Such improvements can be provided by decentr… Show more
“…The papers analyzed therein are however focused with system planning and modelling rather than with driving/managing storage reservoirs in real time. Grosspietsch, Saenger and Girod (2019) analyze studies and practical implementations (i.e. pilot projects) focused on matching production and consumption, a goal which is present also in the present study: reducing Grid CO 2 intake using storage offers an outlet to low-value electricity that is being curtailed increasingly often.…”
Energy consumption of households is not evenly distributed. To satisfy peak demand, additional CO 2 intensive generators are turned on when demand peaks. To avoid peak demand from dwellings, the RED WoLF (Rethink Electricity Distribution Without Load Following) hybrid storage system is proposed, consisting of batteries, storage heaters and a water cylinder. This aims at avoiding the use of these peak generators and integrating a higher share of renewables on the Power Grid. This system is planned to be tested in 100 houses distributed in 6 pilot sites in Great Britain, Ireland and France, which are currently undergoing construction or refurbishment. This study presents the theoretical model of the controlling algorithm, which enables the uptake of Grid electricity only when CO 2 intensity is below a dynamically computed threshold. The algorithm is tested in computer simulations over the four seasons with varying size of batteries and photovoltaic arrays. Results show how RED WoLF algorithm satisfies households demands while, at the same time, successfully avoiding domestic peak demand, with a significant drop of CO 2 emissions. This is achieved by both increasing photovoltaic self-consumption and uptake of low carbon Grid energy. For example, with a 7 kWh battery and a 4 kW photovoltaic array, CO 2 emissions drop by 30% to almost 100%, depending on the season, relative to the same house without the RED WoLF system. The system has the potential to shift residential demand from peak power/peak times to low value electricity at a time of low demand.
“…The papers analyzed therein are however focused with system planning and modelling rather than with driving/managing storage reservoirs in real time. Grosspietsch, Saenger and Girod (2019) analyze studies and practical implementations (i.e. pilot projects) focused on matching production and consumption, a goal which is present also in the present study: reducing Grid CO 2 intake using storage offers an outlet to low-value electricity that is being curtailed increasingly often.…”
Energy consumption of households is not evenly distributed. To satisfy peak demand, additional CO 2 intensive generators are turned on when demand peaks. To avoid peak demand from dwellings, the RED WoLF (Rethink Electricity Distribution Without Load Following) hybrid storage system is proposed, consisting of batteries, storage heaters and a water cylinder. This aims at avoiding the use of these peak generators and integrating a higher share of renewables on the Power Grid. This system is planned to be tested in 100 houses distributed in 6 pilot sites in Great Britain, Ireland and France, which are currently undergoing construction or refurbishment. This study presents the theoretical model of the controlling algorithm, which enables the uptake of Grid electricity only when CO 2 intensity is below a dynamically computed threshold. The algorithm is tested in computer simulations over the four seasons with varying size of batteries and photovoltaic arrays. Results show how RED WoLF algorithm satisfies households demands while, at the same time, successfully avoiding domestic peak demand, with a significant drop of CO 2 emissions. This is achieved by both increasing photovoltaic self-consumption and uptake of low carbon Grid energy. For example, with a 7 kWh battery and a 4 kW photovoltaic array, CO 2 emissions drop by 30% to almost 100%, depending on the season, relative to the same house without the RED WoLF system. The system has the potential to shift residential demand from peak power/peak times to low value electricity at a time of low demand.
“…Although complementarity has been studied extensively with regards to energy system optimization and RE integration, there has been little to no analysis of policies that encourage complementarity (Haley, 2014). While there is an emerging literature on multi-actor grids and decentralization (Ghadi et al, 2019;Grosspietsch et al, 2019), there is limited knowledge about how to encourage multiple actors as prosumers and producers on a localized grid to provide complementary RE (Wolsink, 2012). Social science literature on decentralization recognises that social actors should be involved in decision making of shared, small scale RE systems.…”
Section: Address Complementarity Heterogeneity and Proximity Simultaneouslymentioning
Luis (2021) Implementing a just renewable energy transition: policy advice for transposing the new European rules for Renewable Energy Communities. Energy Policy, 156. a112435 1-10.
“…Within the two research areas of local energy management systems and MESs, previous studies [3,5,6] have reviewed definitions, trends, challenges, and categorization of literature providing valuable insight into the topic. For example, Grosspeithsch et al [6] categorized the literature into four categories: general overview, model and optimization, energy management and system analysis, and case study.…”
This paper investigates the cost-effectiveness of operation strategies which can be used to abate CO 2 emissions in a local multi-energy system. A case study is carried out using data from a real energy system that integrates district heating, district cooling, and electricity networks at Chalmers University of Technology. Operation strategies are developed using a mixed integer linear programming multi-objective optimization model with a short foresight rolling horizon and a year of data. The cost-effectiveness of different strategies is evaluated across different carbon prices. The results provide insights into developing abatement strategies for local multi-energy systems that could be used by utilities, building owners, and authorities. The optimized abatement strategies include: increased usage of biomass boilers, substitution of district heating and absorption chillers with heat pumps, and higher utilization of storage units. The results show that, by utilizing all the strategies, a 20.8% emission reduction can be achieved with a 2.2% cost increase for the campus area. The emission abatement cost of all strategies is 36.6–100.2 (€/tCO 2 ), which is aligned with estimated carbon prices if the Paris agreement target is to be achieved. It is higher, however, than average European Emission Trading System prices and Sweden’s carbon tax in 2019.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.