| 1. |
- Antoniadou-Plytaria, Kyriaki, 1989, et al.
(författare)
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Chalmers Campus as a Testbed for Intelligent Grids and Local Energy Systems
- 2019
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Ingår i: IEEE International Conference on Smart Energy Systems and Technologies (SEST). - 9781728111568
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Konferensbidrag (refereegranskat)abstract
- This paper presents an overview of a testbed for intelligent distribution grids, local energy systems, and energy flexible buildings, which is being developed at the campus of Chalmers University of Technology in Gothenburg, Sweden. It describes the test sites, the functionalities, and the planned demonstration activities within the scope of on-going research projects. The proposed demonstrations include a local energy market platform, energy management solutions for microgrids and smart buildings, as well as voltage control in distribution grids. The paper aims to show how the physical energy supply systems of the university are being adapted to integrate the communication and control set-ups that provide the technical requirements for smart grid interoperability. As an example, the on-site implementation of remote battery control is presented, where initial results show the feasibility and potential benefits of the external control. Finally, challenges and lessons learned during the development of the testbed are highlighted.
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| 2. |
- Fotouhi Ghazvini, Mohammad Ali, 1983, et al.
(författare)
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A Centralized Building Energy Management System for Residential Energy Hubs
- 2019
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Ingår i: SEST 2019 - 2nd International Conference on Smart Energy Systems and Technologies.
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Konferensbidrag (refereegranskat)abstract
- This paper proposes a framework for energy management in modern smart buildings under the context of integrated energy systems. The added value of this work is using the rolling time window framework for decision-making, along with the inclusion of the peak load tariffs. The rolling time window is used to send updated control commands near to real-time. A Swedish multi-family residential building is used in the case study. The results of the case study verify the effectiveness and the validity of the proposed model. The results show that by integrating the electricity and the district heating network with a 11 kW heat pump, the total energy cost reduces around 27%.
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| 3. |
- Fotouhi Ghazvini, Mohammad Ali, 1983, et al.
(författare)
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A Close-to-Real-time Energy Management System for Smart Residential Buildings
- 2019
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Ingår i: 2019 IEEE Milan PowerTech, PowerTech 2019. ; 2019, s. 1-6
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Konferensbidrag (refereegranskat)abstract
- This paper proposes a close to real-time energy management system for multi-family residential buildings. The aim of the model is to optimally manage the controllable energy sources in a rolling time window to reduce the total energy cost of the building, considering the time variable electricity prices. A mixed-integer linear programming model is developed to control the washing machines, dishwashers and the energy storage system in a smart building. The performance of the model is evaluated through simulating the operation of an energy management system during one day using the measurement data from a real building located within Chalmers University of Technology campus. The results show that the proposed model can help reduce the building's energy cost by 9% and reduce the peak demand 18.78% using the resource flexibilities in the building, without causing discomfort for the tenants.
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| 4. |
- Fotouhi Ghazvini, Mohammad Ali, 1983, et al.
(författare)
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A rolling horizon approach for the optimal real-time dispatch of energy sources in smart residential buildings
- 2019
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Konferensbidrag (refereegranskat)abstract
- This paper develops a close-to-real-time energy management system for a smart multi-family residential building with PV production and energy storage systems. The model aims to control the operation of controllable residential appliances to minimize the total energy procurement cost while ensuring the users’ satisfaction. A mixed-integer linear programming model is developed to solve the optimization problem in a rolling time window. The results of the case study verify the effectiveness and validity of the proposed model. Implementing the proposed approach in a residential building reduces the peak demand by 24.5% and the total energy procurement cost by 4.3%.
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| 5. |
- Shokri Gazafroudi, Amin, et al.
(författare)
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Stochastic interval-based optimal offering model for residential energy management systems by household owners
- 2019
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Ingår i: International Journal of Electrical Power and Energy Systems. - : Elsevier BV. - 0142-0615. ; 105, s. 201-219
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Tidskriftsartikel (refereegranskat)abstract
- This paper proposes an optimal bidding strategy for autonomous residential energy management systems. This strategy enables the system to manage its domestic energy production and consumption autonomously, and trade energy with the local market through a novel hybrid interval-stochastic optimization method. This work poses a residential energy management problem which consists of two stages: day-ahead and real-time. The uncertainty in electricity price and PV power generation is modeled by interval-based and stochastic scenarios in the day-ahead and real-time transactions between the smart home and local electricity market. Moreover, the implementation of a battery included to provide energy flexibility in the residential system. In this paper, the smart home acts as a price-taker agent in the local market, and it submits its optimal offering and bidding curves to the local market based on the uncertainties of the system. Finally, the performance of the proposed residential energy management system is evaluated according to the impacts of interval optimistic and flexibility coefficients, optimal bidding strategy, and uncertainty modeling. The evaluation has shown that the proposed optimal offering model is effective in making the home system robust and achieves optimal energy transaction. Thus, the results prove that the proposed optimal offering model for the domestic energy management system is more robust than its non-optimal offering model. Moreover, battery flexibility has a positive effect on the system's total expected profit. With regarding to the bidding strategy, it is not able to impact the smart home's behavior (as a consumer or producer) in the day-ahead local electricity market.
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