| 1. |
- Javidsharifi, Mahshid, et al.
(författare)
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Demand response planning for day-ahead energy management of CHP-equipped consumers
- 2022
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Ingår i: Proceedings - 2022 IEEE 4th Global Power, Energy and Communication Conference, GPECOM 2022. - 9781665469258 ; , s. 461-467
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Konferensbidrag (refereegranskat)abstract
- Due to the growing importance of demand response program (DRP) in demand side management in power systems as well as increasing employment of combined heat and power (CHP) units, the issue of energy management of large consumers equipped with CHP units in the presence of a DRP based on the day-ahead electricity price has been studied in this paper. To solve the considered non-convex and non-linear energy management problem, particle swarm optimization (PSO) algorithm has been used. Also, given the importance of the effect of uncertainties on the planning and operation of units in the energy management, the unscented transformation (UT) method is used for modeling uncertainties related to electricity prices and the amount of electric and thermal loads. In the applied DRP, the consumers can shift a percentage of their load from higher-price hours to lower-price hours to reduce operating costs. No load-shedding is considered in the problem formulation. The consumer energy system consists of two CHP units, one electrical unit, one thermal unit, and a heat buffer tank (HBT) for the storage of surplus thermal energy. The consumer can also buy electricity from the main electricity grid to supply the demanded load based on the price of electricity. The simulation results show that the application of the suggested DRP reduces the operational cost.
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| 2. |
- Javidsharifi, Mahshid, et al.
(författare)
-
Optimum sizing of photovoltaic-battery power supply for drone-based cellular networks
- 2021
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Ingår i: Drones. - : MDPI AG. - 2504-446X. ; 5:4
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Tidskriftsartikel (refereegranskat)abstract
- In order to provide Internet access to rural areas and places without a reliable economic electricity grid, self-sustainable drone-based cellular networks have recently been presented. However, the difficulties of power consumption and mission planning lead to the challenge of optimal sizing of the power supply for future cellular telecommunication networks. In order to deal with this challenge, this paper presents an optimal approach for sizing the photovoltaic (PV)-battery power supply for drone-based cellular networks in remote areas. The main objective of the suggested approach is to minimize the total cost, including the capital and operational expenditures. The suggested framework is applied to an off-grid cellular telecommunication network with drone-based base stations that are powered by PV-battery systems-based recharging sites in a rural location. The PV-battery system is optimally designed for three recharging sites with three different power consumption profiles with different peak and cumulative loads. Results show that the optimal design of the PV-battery system is dependent on geographical data, solar irradiation, and ambient temperature, which affect the output power of the PV system, as well as the power consumption profile, which affects the required number of PV panels and battery capacity.
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| 3. |
- Javidsharifi, Mahshid, et al.
(författare)
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PV-Powered Base Stations Equipped by UAVs in Urban Areas
- 2022
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Ingår i: 2022 IEEE 96th Vehicular Technology Conference, VTC 2022-Fall 2022 - Proceedings. - 1550-2252. - 9781665454681 ; 2022-September
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Konferensbidrag (refereegranskat)abstract
- Recently, the application of unmanned aerial vehicles (UAVs) to support the base stations in cellular telecommunication networks attracts attentions. UAV-assisted base stations can provide the extra users' demand in extreme and/ or unpredictable situations such as Olympic Games to avoid extra cost of installing ground base stations. In this paper, a PV-battery power system is presented to supply UAV-assisted base stations in cellular telecommunication networks in urban areas to prevent environmental issues as well as to reduce the cost of fulfilling the energy demand. First, the energy consumption profile of the batteries of UAVs is estimated. Afterwards, the impact of the PV system sizing and battery capacity are studied based on sensitivity analysis.
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| 4. |
- Javidsharifi, Mahshid, et al.
(författare)
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Quantifying the Impact of Different Parameters on Optimal Operation of Multi-Microgrid Systems
- 2022
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Ingår i: 2022 IEEE 7th Forum on Research and Technologies for Society and Industry Innovation, RTSI 2022. - 9781665497398 ; , s. 88-94
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Konferensbidrag (refereegranskat)abstract
- The multi-objective optimal power management of multi-microgrid systems is solved in this paper. Minimizing the total cost and emission of the system are considered as the objective functions. The multi-objective particle swarm optimization algorithm is applied on a multi-microgrid system that consists of four microgrids each includes diesel generators, wind turbines, photovoltaic units, battery, and local loads. The multi-microgrid system can exchange power with the electricity grid. Moreover, the adjacent microgrids in the multi-microgrid system can share power with each other. The impact of the variation of battery charging and discharging efficiency, the electricity price, the capacity of diesel generators and renewable-based units, the maximum exchangeable power between the multi-microgrid system and the electricity grid and the power sharing among adjacent microgrids on day-Ahead units' scheduling of multi-microgrid are evaluated through sensitivity analysis in simulation results.
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| 5. |
- Javidsharifi, Mahshid, et al.
(författare)
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Stochastic Optimal Strategy for Power Management in Interconnected Multi-Microgrid Systems
- 2022
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Ingår i: Electronics (Switzerland). - : MDPI AG. - 2079-9292. ; 11:9
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Tidskriftsartikel (refereegranskat)abstract
- A novel stochastic strategy for solving the problem of optimal power management of multi-microgrid (MMG) systems is suggested in this paper. The considered objectives are minimizing the total cost and emission of the system. The suggested algorithm is applied on a MMG consisting of four microgrids (MG), each including fossil fuel-based generator units, wind turbine (WT), photovoltaic (PV) panel, battery, and local loads. The unscented transformation (UT) method is applied to deal with the inherent uncertainties of the renewable energy sources (RES) and forecasted values of the load demand and electricity price. The proposed algorithm is applied to solve the power management of a sample MMG system in both deterministic and probabilistic scenarios. It is justified through simulation results that the suggested algorithm is an efficient approach in satisfying the minimization of the cost and the environmental objective functions. When considering uncertainties, it is observed that the maximum achievable profit is about 23% less than that of the deterministic condition, while the minimum emission level increases 22%. It can be concluded that considering uncertainties has a significant effect on the economic index. Therefore, to present more accurate and realistic results it is essential to consider uncertainties in solving the optimal power management of MMG system.
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