In this report, the details of an investigation into the e ect of the low induction wind turbines on the Levelised Cost of Electricity (LCoE) in a 1GW o shore wind farm is outlined. The 10 MW INNWIND.EU conventional wind turbine and its low induction variant, the 10 MW AVATAR wind turbine, are considered in a variety of 10x10 layout configurations. The Annual Energy Production (AEP) and cost of electrical infrastructure were determined using two in-house ECN software tools, namely FarmFlow and EEFarm II. Combining this information with a generalised cost model, the LCoE from these layouts were determined. The optimum LCoE for the AVATAR wind farm was determined to be 92.15 e/MWh while for the INNWIND.EU wind farm it was 93.85 e/MWh. Although the low induction wind farm o ered a marginally lower LCoE, it should not be considered as definitive due to simple nature of the cost model used. The results do indicate that the AVATAR wind farms require less space to achieve this similar cost performace, with a higher optimal wind farm power density (WFPD) of 3.7 MW/km2 compared to 3 MW/km2 for the INNWIND.EU based wind farm.
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The authors used the INFRASTRATEGO simulation game to examine strategic behavior in a liberalizing electricity market and the effectiveness of different regulatory regimes in dealing with this strategic behavior. The game simulates the Dutch electricity market in the years 2002 to 2006. The game was played eight times with about 400 players, both professionals and students. Two regulatory regimes defined by (a) the policy-making model and (b) the regulation by negotiation model were evaluated. The authors found several patterns of strategic behavior such as regulatory capture, sometimes with rather disturbing effects with regard to the settlement of rates and long-term capacity planning.
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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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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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How can physics education be designed and enacted in such a way that it is in agreement with the Nature of Science (NOS) and fosters conceptual understanding in electricity? The results of the studies may have implications for practice. Teachers and teacher educators need to develop a balanced perspective on conceptual understanding in relation to inquiry and take into account the tensions that were identified. For the topic of electricity, teachers may learn from the local instruction theory and pedagogy developed in this dissertation. Both teacher education institutes and professionalization efforts need to prepare teachers for this type of instruction. This will be fostered if teachers and teacher educators develop an understanding of NOS. A noticeable classroom impact of teacher learning may be expected if teachers work cooperatively on the same issue, related to a concern about student learning, if expertise is available on the content and pedagogy, and if classroom coaching and feedback are part of the project. The criteria to evaluate textbooks may be helpful for authors of learning materials if they intend to foster model-oriented activities and inquiry, but also for practitioners for the selection of these materials and in teacher education to prepare for a systematic evaluation of learning materials for physics.
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Poster presentation: decentralized gas storage.
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This research presents a case study exploring the potential for demand side flexibility at a cluster of university buildings. The study investigates the potential of a collection of various electrical devices, excluding heating and cooling systems. With increasing penetration of renewable electricity sources and the phasing out of dispatchable fossil sources, matching grid generation with grid demand will become difficult using traditional grid management methods alone. Additionally, grid congestion is a pressing problem. Demand side management in buildings may contribute to a solution to these problems. Currently demand response is, however, not yet exploited at scale. In part, this is because it is unclear how this flexibility can be translated into successful business models, or whether this is possible under the current market regime. This research gives insight into the potential value of energy demand flexibility in reducing energy costs and increasing the match between electricity demand and purchased renewable electricity. An inventory is made of on-site electrical devices that offer load flexibility and the magnitude and duration of load shifting is estimated for each group of devices. A demand response simulation model is then developed that represents the complete collection of flexible devices. This model, addresses demand response as a ‘distribute candy’ problem and finds the optimal time-of-use for shiftable electricity demand whilst respecting the flexibility constraints of the electrical devices. The value of demand flexibility at the building cluster is then assessed using this simulation model, measured electricity consumption, and data regarding the availability of purchased renewables and day-ahead spot prices. This research concludes that coordinated demand response of large variety of devices at the building cluster level can improve energy matching by 0.6-1.5% and reduce spot market energy cost by 0.4-3.2%.
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Power to methane provides a solution to a couple of two problems: unbalanced production and demand of wind plus solar power electricity and the low methane content of biogas by storing electricity via hydrogen into methane gas using carbon dioxide from biogas and methanogenic bacteria. The four-year project is performed by a consortium of three research institutes and five companies. In WP1 the-state-of- the-art of scientific knowledge on P2M technology is reviewed and evaluated.
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