Electrification of residential areas is increasingly common. Major areas of development include rooftop solar panels, electric vehicles and heat pumps. However, existing grid components may have insufficient network capacity to accommodate the resulting electricity flows. Battery energy storage (BES) can be used to prevent transformer overloading resulting from electrification. Ideally, BES should be sized and placed such that it can prevent overloading with a minimum amount of storage capacity, but it is unclear how load characteristics affect BES capacity requirements. This study investigated how load simultaneity affects the minimum BES capacity required to prevent transformer overloading, comparing a central with a distributed BES layout. It was found that as simultaneity increases, distributed storage requires relatively less capacity than central storage. This is likely due to the reduced ability of central BES to share capacity between connections as simultaneity increases, and the ability of distributed BES to better reduce transportation losses.
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Electrification of residential areas is increasingly common. Major areas of development include promoting rooftop solar panels, electric vehicles and heat pumps. However, existing grid components may have insufficient capacity to support the resulting electricity flows. Battery energy storage (BES) can be used to prevent transformer overloading resulting from electrification. Ideally, BES should be sized and placed such that it can prevent overloading with a minimum amount of storage capacity, but it is unclear how load characteristics affect BES capacity requirements. This study investigated how load simultaneity affects the minimum BES capacity required to prevent transformer overloading, comparing a central with a decentral BES configuration. It was found that as simultaneity increases, decentral storage requires relatively less capacity than central storage. This is likely due to the reduced ability of central BES to share capacity between connections with higher simultaneity, and the ability of decentral BES to better reduce transportation losses.
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Battery energy storage (BES) can provide many grid services, such as power flow management to reduce distribution grid overloading. It is desirable to minimise BES storage capacities to reduce investment costs. However, it is not always clear how battery sizing is affected by battery siting and power flow simultaneity (PFS). This paper describes a method to compare the battery capacity required to provide grid services for different battery siting configurations and variable PFSs. The method was implemented by modelling a standard test grid with artificial power flow patterns and different battery siting configurations. The storage capacity of each configuration was minimised to determine how these variables affect the minimum storage capacity required to maintain power flows below a given threshold. In this case, a battery located at the transformer required 10–20% more capacity than a battery located centrally on the grid, or several batteries distributed throughout the grid, depending on PFS. The differences in capacity requirements were largely attributed to the ability of a BES configuration to mitigate network losses. The method presented in this paper can be used to compare BES capacity requirements for different battery siting configurations, power flow patterns, grid services, and grid characteristics.
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Residential electricity distribution grid capacity is based on the typical peak load of a house and the load simultaneity factor. Historically, these values have remained predictable, but this is expected to change due to increasing electric heating using heat pumps and rooftop solar panel electricity generation. It is currently unclear how this increase in electrification will impact household peak load and load simultaneity, and hence the required grid capacity of residential electricity distribution grids. To gain better insight, transformer and household load measurements were taken in an all-electric neighborhood over a period of three years. These measurements were analyzed to determine how heat pumps and solar panels will alter peak load and load simultaneity, and hence grid capacity requirements. The impacts of outdoor effective temperature and solar panel orientation were also analyzed. Moreover, the potential for smart grids to reduce grid capacity requirements was examined.
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Renewable energy is often suggested as a possible solution for reducing greenhouse gas emissions and decreasing dependency on fossil energy sources. The most readily available renewable energy sources in Europe, wind, solar and biomass are dispersed by nature, making them ideally suited for use within Decentralized Energy Systems. Decentralized energy grids can help integrate renewable production, short lived by-products e.g. heat, minimize transport of energy carriers and fuel sources and reduce the dependency on fossils, hence, possibly improving the overall efficiency and sustainability of the energy distribution system. Within these grids balance between local renewable production and local energy demand is an important subject. Currently, fluctuations between demand and production of energy are mainly balanced by input from conventional power stations, which operate on storable fossil energy sources e.g. coal, oil, natural gas and nuclear. Within the long term scope of transition towards a low carbon intensive energy system, sustainable systems must be found which can replace fossil energy sources as load balancer in our energy supply systems.
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The neighborhood of Houtlaan in Assen, the Netherlands, has ambitious targets for reducing the neighborhood’scarbon emissions and increasing their production of their own, sustainable energy. Specifically, they wish toincrease the percentage of houses with a heat pump, electric vehicle (EV) and solar panels (PV) to 60%, 70%and 80%, respectively, by the year 2030. However, it was unclear what the impacts of this transition would be onthe electricity grid, and what limitations or problems might be encountered along the way.Therefore, a study was carried out to model the future energy load and production patterns in Houtlaan. Thepurpose of the model was to identify and quantify the problems which could be encountered if no steps are takento prevent these problems. In addition, the model was used to simulate the effectiveness of various proposedsolutions to reduce or eliminate the problems which were identified.
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This paper proposes a Hybrid Microgrid (HμG) model including distributed generation (DG) and a hydrogen-based storage system, controlled through a tailored control strategy. The HμG is composed of three DG units, two of them supplied by solar and wind sources, and the latter one based on the exploitation of theProton Exchange Membrane (PEM) technology. Furthermore, the system includes an alkaline electrolyser, which is used as a responsive load to balance the excess of Variable Renewable Energy Sources (VRES) production, and to produce the hydrogen that will be stored into the hydrogen tank and that will be used to supply the fuel cell in case of lack of generation. The main objectives of this work are to present a validated dynamic model for every component of the HμG and to provide a strategy to reduce as much as possible the power absorption from the grid by exploiting the VRES production. The alkaline electrolyser and PEM fuel cell models are validated through real measurements. The State of Charge (SoC) of the hydrogen tank is adjusted through an adaptive scheme. Furthermore, the designed supervisor power control allows reducing the power exchange and improving the system stability. Finally, a case, considering a summer load profile measured in an electrical substation of Politecnico di Torino, is presented. The results demonstrates the advantages of a hydrogen-based micro-grid, where the hydrogen is used as medium to store the energy produced by photovoltaic and wind systems, with the aim to improve the self-sufficiency of the system
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To reduce greenhouse gas emissions, countries around the world are pursuing electrification policies. In residential areas, electrification will increase electricity supply and demand, which is expected to increase grid congestion at a faster rate than grids can be reinforced. Battery energy storage (BES) has the potential to reduce grid congestion and defer grid reinforcement, thus supporting the energy transition. But, BES could equally exacerbate grid congestion. This leads to the question: What are the trade-offs between different battery control strategies, considering battery performance and battery grid impacts? This paper addresses this question using the battery energy storage evaluation method (BESEM), which interlinks a BES model with an electricity grid model to simulate the interactions between these two systems. In this paper, the BESEM is applied to a case study, wherein the relative effects of different BES control strategies are compared. The results from this case study indicate that batteries can reduce grid congestion if they are passively controlled (i.e., constraining battery power) or actively controlled (i.e., overriding normal battery operations). Using batteries to reduce congestion was found to reduce the primary benefits provided by the batteries to the battery owners, but could increase secondary benefits. Further, passive battery controls were found to be nearly as effective as active battery controls at reducing grid congestion in certain situations. These findings indicate that the trade-offs between different battery control strategies are not always obvious, and should be evaluated using a method like the BESEM.
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