| 1. |
- Aupke, Phil, et al.
(författare)
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PV Power Production and Consumption Estimation with Uncertainty bounds in Smart Energy Grids
- 2023
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Ingår i: 2023 IEEE International Conference on Environment and Electrical Engineering and 2023 IEEE Industrial and Commercial Power Systems Europe (EEEIC / I&CPS Europe). - : IEEE. - 9798350347432 - 9798350347449
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Konferensbidrag (refereegranskat)abstract
- For efficient energy exchanges in smart energy grids under the presence of renewables, predictions of energy production and consumption are required. For robust energy scheduling, prediction of uncertainty bounds of Photovoltaic (PV) power production and consumption is essential. In this paper, we apply several Machine Learning (ML) models that can predict the power generation of PV and consumption of households in a smart energy grid, while also assessing the uncertainty of their predictions by providing quantile values as uncertainty bounds. We evaluate our algorithms on a dataset from Swedish households having PV installations and battery storage. Our findings reveal that a Mean Absolute Error (MAE) of 16.12W for power production and 16.34W for consumption for a residential installation can be achieved with uncertainty bounds having quantile loss values below 5W. Furthermore, we show that the accuracy of the ML models can be affected by the characteristics of the household being studied. Different households may have different data distributions, which can cause prediction models to perform poorly when applied to untrained households. However, our study found that models built directly for individual homes, even when trained with smaller datasets, offer the best outcomes. This suggests that the development of personalized ML models may be a promising avenue for improving the accuracy of predictions in the future.
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| 2. |
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| 3. |
- Norwood, Zack, 1979, et al.
(författare)
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Step-by-step deep retrofit and building integrated façade/roof on a 'million program' house
- 2016
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Ingår i: Passipedia.org, Conference proceedings of the 20th annual passive house conference.
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Konferensbidrag (refereegranskat)abstract
- Kollektivhuset Stacken is a building from the “miljonprogrammet” – the housing program implemented in Sverige from 1964 to 1975 to ensure everyone could have an affordable home. Step-by-step, it achieves passive house standard, BIPV covers its electricity demand, and the indoor comfort is improved.
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| 4. |
- Shafique, Hamza, et al.
(författare)
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Behind the Meter Strategies Energy management system with a Swedish case study
- 2021
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Ingår i: IEEE Electrification Magazine. - : Institute of Electrical and Electronics Engineers (IEEE). - 2325-5897. ; 9:3, s. 112-119
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Tidskriftsartikel (refereegranskat)abstract
- The Introduction of Smart Meters (SMs) is one of the fundamental changes for the intelligent power grid. SMs provide input data from the electricity customers, which might also be a local electricity producer, also called prosumers. This article proposes novel strategies using an energy management system (EMS) to enhance economic value for the prosumers and for the network operators in terms of reliability performance and flexibility of the electricity power grid. These strategies, referred to as behind the meter strategies, could be influenced, e.g., using a battery energy storage system (BESS), plug-in electric vehicles (PEVs), and various alternatives of local electricity generation like solar photovoltaic (PV) or wind power. Using remote sensing and the reading functionality of SMs, the BESS can be intelligently managed by an EMS that uses the BESS resource for multiple ancillary services, thereby generating additional value from the present resource.
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| 5. |
- Shafique, Hamza, et al.
(författare)
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Energy Management System (EMS) of Battery Energy Storage System (BESS) – Providing Ancillary Services
- 2021
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Ingår i: 2021 IEEE Madrid PowerTech, PowerTech 2021 - Conference Proceedings. - : Institute of Electrical and Electronics Engineers (IEEE).
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Konferensbidrag (refereegranskat)abstract
- In this paper, an Energy Management System (EMS) that manages a Battery Energy Storage System (BESS) is implemented. It performs peak shaving of a local load and provides frequency regulation services using Frequency Containment Reserve (FCR-N) in the Swedish reserve market. The EMS optimizes the approach of BESS resource dispatch distribution between two ancillary services, such that it maximizes profits and resource efficiency while enhancing overall system reliability of the electricity grid. The EMS consists of; a Prognosis Module running a day ahead to allow for identification of intervals for peak shaving and frequency regulation, and a Real-time Operation Module running on the day of operation creating BESS control commands. Implementing the Prognosis module on Öckerö ice-rink results in 12% cost saving on the grid tariff with 21% power peak reduction and three hours of daily frequency reserve. Multiple such systems can be aggregated to improve flexibility of the system.
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| 6. |
- Shafique, Hamza, et al.
(författare)
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Real-time Operation Model for Energy Management System of Battery Energy Storage System - Case Study : The School of Sinntorp
- 2022
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Ingår i: 2022 17th International Conference on Probabilistic Methods Applied to Power Systems, PMAPS 2022. - : Institute of Electrical and Electronics Engineers (IEEE).
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Konferensbidrag (refereegranskat)abstract
- This paper shows the real-time operation model of Energy Management System (EMS) for control of Battery Energy Storage System (BESS). These models are needed to manage uncertain electricity loads, delivery of peak shaving and frequency regulation services and the BESS financial feasibility. The delivery of these services result in economic return for the resource owner and increased grid flexibility. The Energy Management System implemented in this work uses the electricity load and grid frequency data as inputs to generate BESS control commands that deliver the said services. The validation simulation performed on the School of Sinntorp in Sweden returns an annual return on investment of 22% for the BESS and inverter. Implementation of storage systems was shown to expedite the adoption of renewable energy while also solving the challenges that this adoption on scale poses. This active adoption is pivotal in achieving the UN sustainable developmental goals (SDGs) for energy.
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