University of Twente Student Theses


Modelling the LIFE project using DEMKit

Dai, Yinping (2020) Modelling the LIFE project using DEMKit.

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Abstract:With the depletion of fossil fuel and the acceleration of climate change, sustainability is more valued by the public and governments. Sustainable technologies, such as renewable energy technologies and smart appliances, are acknowledged as promising solutions to reduce carbon footprint. The University of Twente initiated a project named the LIFE with the intention to research residential energy and water system by incorporating various sustainable technologies. In this thesis, we explore the possibility of the LIFE microgrid to operate in a near-autarkic condition by DEMKit. The LIFE as envisioned consists of a 3 kW wind turbine, an EV parking lot with 25 kWp PV panels, a hybrid storage system (a short-term and seasonal buffer), and three tiny houses (including underfloor infrared heating systems). The models of the first three components are created and integrated into the DEMKit. Also, a long-term planning approach for buffers is developed to support seasonal storage. Besides, the Profile Steering control algorithm (PS) is applied to improve the Degree of Autarky (DoA) of the microgrid. The continuous power mode without loss and discrete power mode with the seasonal buffer conversion efficiencies, 45% for discharging and 65% for charging, are used in the simulation. The potential interactions between users and sustainable technologies and the consequential user behavior change are studied through literature research. A decrease of 10% is estimated for each house. The annual energy consumption of a normal household and a campus EV are estimated to be 4-4.5 MWh (including heating) and 2-2.5 MWh, respectively. The wind turbine and PV panels generate around 29.3 MWh of electricity a year. Based on this knowledge, we create a normal-behavior scenario and energy-saving scenario based on 10% household consumption decrease). We studied the impact of potential households’ behavior change on the sizing of the storage system, using continuous mode. It is found that PS is capable of improving DoA over 10 percent points alone and around 12 percent points with a hybrid buffer system. With it implemented, the normal-behavior scenario can achieve a 99.8% DoA with a 90 kWh short-term battery and 9000 kWh seasonal storage system. Whereas, a ceiling of 95% DoA exists for the energy-saving scenario under the present storage configuration, predominantly subjected to intentionally introduced prediction error. Nonetheless, a smaller seasonal buffer, 3000 kWh, is enough to reach its maximum DoA. When exploring the maximum amount of tiny houses that the LIFE can supply with the aforementioned PV and wind turbine, the 95% ceiling appears again (using continuous mode). With a 210 kWh short-term battery and 12000 kWh seasonal storage, six tiny houses plus a campus EV, whose total loads is 27.26 MWh, can achieve 94.7% of DoA. Moreover, the discrete power mode is exerted on the normal behavior scenario of three tiny houses. A 60 kWh short-term battery and 6000 kWh seasonal buffer results in 78.5% for DoA. The relatively low degree of autarky is mainly due to the enormous conversion losses, around 14.18 MWh, which turns the scenario into an extreme case. For a more compelling storage model, integrating loss into the continuous power mode of DEMKit and tackling prediction errors (95% ceiling problem) is desired. It is expected that with these improvements, the normal-behavior scenario may accomplish the target of near autarky with a larger long-term buffer.
Item Type:Essay (Master)
Faculty:EEMCS: Electrical Engineering, Mathematics and Computer Science
Subject:50 technical science in general, 53 electrotechnology, 54 computer science
Programme:Sustainable Energy Technology MSc (60443)
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