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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The ever-increasing electrification of society has been a cause of utility grid issues in many regions around the world. With the increased adoption of electric vehicles (EVs) in the Netherlands, many new charge points (CPs) are required. A common installation practice of CPs is to group multiple CPs together on a single grid connection, the so-called charging hub. To further ensure EVs are adequately charged, various control strategies can be employed, or a stationary battery can be connected to this network. A pilot project in Amsterdam was used as a case study to validate the Python model developed in this study using the measured data. This paper presents an optimisation of the battery energy storage capacity and the grid connection capacity for such a P&R-based charging hub with various load profiles and various battery system costs. A variety of battery control strategies were simulated using both the optimal system sizing and the case study sizing. A recommendation for a control strategy is proposed.
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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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This study used historical data from a Park & Ride facility in Amsterdam to build a validated computer (Python) model to optimize battery and grid connection sizing. The case study modelled is equipped with 8 EV chargers (16 connections), an on-site supplementary battery, and a limited capacity grid connection. This model was then used to optimize the battery energy storage capacity and grid connection capacity for minimal annualized investment, using a future proof monthly load profile. A variety of battery control strategies were simulated using both the optimal system sizing and the current system sizing. The results were compared and a recommended control strategy presented, considering a number of performance metrics.
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The intermittency of renewable energy technologies requires adequate storage technologies. Hydrogen systems consisting of electrolysers, storage tanks, and fuel cells can be implemented as well as batteries. The requirements of the hydrogen purification unit is missing from literature. We measured the same for a 4.5 kW PEM electrolyser to be 0.8 kW for 10 min.A simulation to hybridize the hydrogen system, including its purification unit, with lithium-ion batteries for energy storage is presented; the batteries also support the electrolyser. We simulated a scenario for operating a Dutch household off-electric-grid using solar and wind electricity to find the capacities and costs of the components of the system.Although the energy use of the purification unit is small, it influences the operation of the system, affecting the sizing of the components. The battery as a fast response efficient secondary storage system increases the ability of the electrolyser to start up.
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The application of DC grids is gaining more attention in office applications. Especially since powering an office desk would not require a high power connection to the main AC grid but could be made sustainable using solar power and battery storage. This would result in fewer converters and further advanced grid utilization. In this paper, a sustainable desk power application is described that can be used for powering typical office appliances such as computers, lighting, and telephones. The desk will be powered by a solar panel and has a battery for energy storage. The applied DC grid includes droop control for power management and can either operate stand-alone or connected to other DC-desks to create a meshed-grid system. A dynamic DC nano-grid is made using multiple self-developed half-bridge circuit boards controlled by microcontrollers. This grid is monitored and controlled using a lightweight network protocol, allowing for online integration. Droop control is used to create dynamic power management, allowing automated control for power consumption and production. Digital control is used to regulate the power flow, and drive other applications, including batteries and solar panels. The practical demonstrative setup is a small-sized desktop with applications built into it, such as a lamp, wireless charging pad, and laptop charge point for devices up to 45W. User control is added in the form of an interactive remote wireless touch panel and power consumption is monitored and stored in the cloud. The paper includes a description of technical implementation as well as power consumption measurements.
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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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A number of studies have investigated the possibility of extending Electric Vehicle (EV) Lithium-ion battery life by deliberately choosing to store the battery at a low to moderate state of charge. Recently, there has been considerable interest shown in the scheme of a deliberate discharge and subsequent recharge of a battery to yield an overall reduction in battery degradation whilst carrying out Vehicle-to-Grid (V2G) services (so-called `beneficial V2G'). This paper presents an investigation of the conditions permitting successful operation of this method by examining incremental time variation of the relevant parameters for two types of cells from results of the same physical size and chemistry, and similar capacity. These two types of cells are found in this present analysis to offer differing degrees of suitability for beneficial V2G.
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Renewable energy sources have an intermittent character that does not necessarily match energy demand. Such imbalances tend to increase system cost as they require mitigation measures and this is undesirable when available resources should be focused on increasing renewable energy supply. Matching supply and demand should therefore be inherent to early stages of system design, to avoid mismatch costs to the greatest extent possible and we need guidelines for that. This paper delivers such guidelines by exploring design of hybrid wind and solar energy and unusual large solar installation angles. The hybrid wind and solar energy supply and energy demand is studied with an analytical analysis of average monthly energy yields in The Netherlands, Spain and Britain, capacity factor statistics and a dynamic energy supply simulation. The analytical focus in this paper differs from that found in literature, where analyses entirely rely on simulations. Additionally, the seasonal energy yield profile of solar energy at large installation angles is studied with the web application PVGIS and an hourly simulation of the energy yield, based on the Perez model. In Europe, the energy yield of solar PV peaks during the summer months and the energy yield of wind turbines is highest during the winter months. As a consequence, three basic hybrid supply profiles, based on three different mix ratios of wind to solar PV, can be differentiated: a heating profile with high monthly energy yield during the winter months, a flat or baseload profile and a cooling profile with high monthly energy yield during the summer months. It is shown that the baseload profile in The Netherlands is achieved at a ratio of wind to solar energy yield and power of respectively Ew/Es = 1.7 and Pw/Ps = 0.6. The baseload ratio for Spain and Britain is comparable because of similar seasonal weather patterns, so that this baseload ratio is likely comparable for other European countries too. In addition to the seasonal benefits, the hybrid mix is also ideal for the short-term as wind and solar PV adds up to a total that has fewer energy supply flaws and peaks than with each energy source individually and it is shown that they are seldom (3%) both at rated power. This allows them to share one cable, allowing “cable pooling”, with curtailment to -for example-manage cable capacity. A dynamic simulation with the baseload mix supply and a flat demand reveals that a 100% and 75% yearly energy match cause a curtailment loss of respectively 6% and 1%. Curtailment losses of the baseload mix are thereby shown to be small. Tuning of the energy supply of solar panels separately is also possible. Compared to standard 40◦ slope in The Netherlands, facade panels have smaller yield during the summer months, but almost equal yield during the rest of the year, so that the total yield adds up to 72% of standard 40◦ slope panels. Additionally, an hourly energy yield simulation reveals that: façade (90◦) and 60◦ slope panels with an inverter rated at respectively 50% and 65% Wp, produce 95% of the maximum energy yield at that slope. The flatter seasonal yield profile of “large slope panels” together with decreased peak power fits Dutch demand and grid capacity more effectively.
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