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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This article explores the applicability of smart grid concepts to the Dutch gas network by reflecting on the experience of the electricity sector.
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The Smart Current Limiter is a switching DC to DC converter that provides a digitally pre-set input current control for inrush limiting and power management. Being able to digitally adjust the current level in combination with external feedback can be used for control systems like temperature control in high power DC appliances. Traditionally inrush current limiting is done using a passive resistance whose resistance changes depending on the current level. Bypassing this inrush limiting resister with a Mosfet improves efficiency and controllability, but footprint and losses remain large. A switched current mode controlled inrush limiter can limit inrush currents and even control the amount of current passing to the application. This enables power management and inrush current limitation in a single device. To reduce footprint and costs a balance between losses and cost-price on one side and electromagnetic interference on the other side is sought and an optimum switching frequency is chosen. To reduce cost and copper usage, switching happens on a high frequency of 300kHz. This increases the switching losses but greatly reduces the inductor size and cost compared to switching supplies running on lower frequencies. Additional filter circuits like snubbers are necessary to keep the control signals and therefore the output current stable.
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As the impact of our actions on the climate become more and more clear and environmental awareness is rising, the quest for increasing efficiency and lower environmental impact becomes very important. Efficiency is particularly important in the field of electricity consumption, which keeps on rising as electrification of our transportation, houses, offices and more continues worldwide. These loads and sustainable sources have one thing in common: Direct Current. To successfully respond to this growing usage of direct current (DC) systems it is important to provoke an evolution in the provision of DC infrastructure. The goal of this paper is to create a methodology to calculate and evaluate the power losses in both traditional AC grids and DC microgrids. This is done through simulation models made by Caspoc, a software for modeling and simulating physical systems in analog/power electronics, electric power generation/conversion/distribution and mechatronics. The results are compared on the quantifiable indicator: energy savings. The impact of cable losses and different converters is calculated through the simulation. This methodology and simulation strategy can be the basis for the optimal grid design in other infrastructures and cases. The model will be validated with intensive tests of household equipment in a later stage of the project, this paper focuses on the model and methodology itself. DOI: 10.1109/DUE.2014.6827760
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PV systems are used more and more. Not always is it possible to install them in the optimal direction for maximum energy output over the year. At the Johan Cruijff ArenA the PV panels are placed all around the roof in all possible directions. Panels oriented to the north will have a lower energy gain than those oriented to the south. The 42 panel groups are connected to 8 electricity meters. Of these 8 energy meters monthly kWh produced are available. The first assignment is to calculate the energy gains of the 42 panel groups, and connect these in the correct way with the 8 energy meter readings, so simulated data is in accordance with measured data.Of the year 2017 there are also main electricity meter readings available for every quarter of an hour. A problem with these readings is that only absolute values are given. When electricity is taken of the grid this is a positive reading, but when there is a surplus of solar energy and electricity is delivered to the grid, this is also a positive reading. To see the effect on the electricity demand of future energy measures, and to use the Seev4-City detailed CO2 savings calculation with the electricity mix of the grid, it is necessary to know the real electricity demand of the building.The second assignment is to use the calculations of the first assignment to separate the 15 minute electricity meter readings in that for real building demand and for PV production.This document first gives information for teachers (learning goals, possible activities, time needed, further reading), followed by the assignment for students.
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Installing photovoltaic panels (PV) on household rooftops can significantly contribute to mitigating anthropogenic climate change. The mitigation potential will be much higher when households would use PVs in a sustainable way, that is, if they match their electricity demand to their PVs electricity production, as to avoid using electricity from the grid. Whilst some have argued that owning PVs motivate households to use their PV in a sustainable way, others have argued that owning a PV does not result in load shifting, or that PV owners may even use more energy when their PV production is low. This paper addresses this critical issue, by examining to what extent PV owners are likely to shift their electricity demand to reduce the use of electricity from the grid. Extending previous studies, we analyse actual high frequency electricity use from the grid using smart meter data of households with and without PVs. Specifically, we employ generalized additive models to examine whether hourly net electricity use (i.e., the difference between electricity consumed from the grid and supplied back to the grid) of households with PVs is not only lower during times when PV production is high, but also when PV production low, compared to households without PVs. Results indicate that during times when PV production is high, net electricity use of households with PV is negative, suggesting they sent back excess electricity to the power grid. However, we found no difference in net electricity use during times when PV production is low. This suggests that installing PV does not promote sustainable PV use, and that the mitigation potential of PV installment can be enhanced by encouraging sustainable PV use
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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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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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