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1. PV to Vehicle, PV to Grid, Vehicle to Grid, and Grid to Vehicle Micro Grid System Using Level Three Charging Station

   https://doi.org/10.1109/GreenTech52845.2022.9772041  

   Balal, Afshin; Giesselmann, Michael (March 2022, 2022 IEEE Green Technologies Conference (GreenTech))

   This paper makes use of electric vehicles (EVs) that are simultaneously connected to the Photovoltaic Cells (PV) and the power grid. In micro-grids, batteries of the electric vehicles (EVs) used as a source of power to feed the power grid in the peak demands of electricity. EVs can help regulation of the power grid by storing excess solar energy and returning it to the grid during high demand hours. This paper proposes a new architecture of micro-grids by using a rooftop solar system, Battery Electric Vehicles (BEVs), grid connected inverters, a boost converter, a bidirectional half-bridge converter, output filter, including L, LC, or LCL, and transformers. The main parts of this micro-grid are illustrated and modeled, as well as a simulation of their operation. In addition, simulation results explore the charging and discharging scenarios of the BEVs. 

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2. Optimal Sizing of Battery Energy Storage Systems for Small Modular Reactor based Microgrids

   https://doi.org/10.1109/KPEC51835.2021.9446203  

   Liu, Xuebo; Ross, Molly; Bindra, Hitesh; Wu, Hongyu (April 2021, 2021 IEEE Kansas Power and Energy Conference (KPEC))

   Battery energy storage systems (BESS) are increasingly deployed in microgrids due to their benefits in improving system reliability and reducing operational costs. Meanwhile, advanced small modular reactors (SMRs) offer many advantages, including relatively small physical footprints, reduced capital investment, and the ability to be sited in locations not possible for larger nuclear plants. In this paper, we propose a bi-level operational planning model that enables microgrid planners to determine the optimal BESS size and technology while taking into account the optimal long-term (a yearly simulation with a 15-min resolution) operations of a microgrid with SMRs and wind turbines. Case studies are performed using realistic BESS and grid data for two BESS technologies, i.e., Li-Ion battery and compressed air energy storage. Numerical results show the effectiveness of the proposed bi-level model. The pros and cons of the two BESS technologies are also revealed. 

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3. Addressing the range anxiety of battery electric vehicles with charging en route

   https://doi.org/10.1038/s41598-022-08942-2  

   Chakraborty, Prabuddha; Parker, Robert; Hoque, Tamzidul; Cruz, Jonathan; Du, Lili; Wang, Shuo; Bhunia, Swarup (December 2022, Scientific Reports)

   Abstract Battery electric vehicles (BEVs) have emerged as a promising alternative to traditional internal combustion engine (ICE) vehicles due to benefits in improved fuel economy, lower operating cost, and reduced emission. BEVs use electric motors rather than fossil fuels for propulsion and typically store electric energy in lithium-ion cells. With rising concerns over fossil fuel depletion and the impact of ICE vehicles on the climate, electric mobility is widely considered as the future of sustainable transportation. BEVs promise to drastically reduce greenhouse gas emissions as a result of the transportation sector. However, mass adoption of BEVs faces major barriers due to consumer worries over several important battery-related issues, such as limited range, long charging time, lack of charging stations, and high initial cost. Existing solutions to overcome these barriers, such as building more charging stations, increasing battery capacity, and stationary vehicle-to-vehicle (V2V) charging, often suffer from prohibitive investment costs, incompatibility to existing BEVs, or long travel delays. In this paper, we propose P eer-to- P eer C ar C harging (P2C2), a scalable approach for charging BEVs that alleviates the need for elaborate charging infrastructure. The central idea is to enable BEVs to share charge among each other while in motion through coordination with a cloud-based control system. To re-vitalize a BEV fleet, which is continuously in motion, we introduce Mobile Charging Stations (MoCS), which are high-battery-capacity vehicles used to replenish the overall charge in a vehicle network. Unlike existing V2V charging solutions, the charge sharing in P2C2 takes place while the BEVs are in-motion, which aims at minimizing travel time loss. To reduce BEV-to-BEV contact time without increasing manufacturing costs, we propose to use multiple batteries of varying sizes and charge transfer rates. The faster but smaller batteries are used for charge transfer between vehicles, while the slower but larger ones are used for prolonged charge storage. We have designed the overall P2C2 framework and formalized the decision-making process of the cloud-based control system. We have evaluated the effectiveness of P2C2 using a well-characterized simulation platform and observed dramatic improvement in BEV mobility. Additionally, through statistical analysis, we show that a significant reduction in carbon emission is also possible if MoCS can be powered by renewable energy sources. 

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4. A Method for Charging Electric Vehicles with Battery-supercapacitor Hybrid Energy Storage Systems to Improve Voltage Quality and Battery Lifetime in Islanded Building-level DC Microgrids

   https://doi.org/10.1109/TSTE.2023.3254597  

   Ghorashi Khalil Abadi, Seyyed Ali; Choi, Jeewon; Bidram, Ali (March 2023, IEEE Transactions on Sustainable Energy)

   This paper proposes a methodology to increase the lifetime of the central battery energy storage system (CBESS) in an islanded building-level DC microgrid (MG) and enhance the voltage quality of the system by employing the supercapacitor (SC) of electric vehicles (EVs) that utilize battery-SC hybrid energy storage systems. To this end, an adaptive filtration-based (FB) current-sharing strategy is proposed in the voltage feedback control loop of the MG that smooths the CBESS current to increase its lifetime by allocating a portion of the high-frequency current variations to the EV charger. The bandwidth of this filter is adjusted using a data-driven algorithm to guarantee that only the EV's SC absorbs the high-frequency current variations, thereby enabling the EV's battery energy storage system (BESS) to follow its standard constant current-constant voltage (CC-CV) charging profile. Therefore, the EV's SC can coordinate with the CBESS without impacting the charging profile of the EV's BESS. Also, a small-signal stability analysis is provided indicating that the proposed approach improves the marginal voltage stability of the DC MG leading to better transient response and higher voltage quality. Finally, the performance of the proposed EV charging is validated using MATLAB/Simulink and hardware-in-the-loop (HIL) testing. 

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5. Microgrid Control Strategy Based on Battery Energy Storage System-Virtual Synchronous Generator (BESS-VSG)

   https://doi.org/10.1109/KPEC47870.2020.9167653  

   Gao, Wei (July 2020, 2020 IEEE Kansas Power and Energy Conference (KPEC))

   null (Ed.)

   With more and more renewable energy resources integrated into the power grid, the system is losing inertia because power electronics-based generators do not provide natural inertia. The low inertia will cause the microgrid to be more sensitive to disturbance and thus a small load change may result in a severe deviation in frequency. Based on the basic VSG algorithm, which is to mimic the characteristic of the traditional synchronous generator, the frequency can be controlled to a stable value faster and more smoothly when there is a fluctuation in the PV power generation and/or load change. However, characteristic of the VSG depends on the system structure in consideration of multiple generations, such as Synchronous Generator (SG), PV and Battery Energy Storage System (BESS), which greatly increases the complexity of applying VSG in practical power system. Furthermore, with BESS-VSG, Maximum Power Point (MPP) operation of PV is guaranteed. In addition, an adaptive VSG method is developed for a microgrid system, and the corresponding simulation in Matlab/Simulink shows the effectiveness of the adaptive VSG method. 

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