Real-time energy management of photovoltaic-assisted electric vehicle charging station by markov decision process

Wu, Yu Hou; Zhang, Jian; Ravey, Alexandre; Chrenko, Daniela; Miraoui, Abdellatif

doi:10.1016/j.jpowsour.2020.228504

Cited by 57 publications

(22 citation statements)

References 49 publications

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“…Nefedov et al (2018) exploit electric vehicle batteries for short-term storage of surplus photovoltaic energy, updating plans as vehicles arrive or if they leave unexpectedly. Wu et al (2020) and Seyyedeh Barhagh et al (2020), present similar approaches with the additional capability to consider dynamic electricity prices. Kolodziejczyk et al (2021) operate a system consisting of photovoltaic generation and battery storage on a real-time electricity market with hourly changing prices.…”

Section: Nowcasting For Vpp With Photovoltaic Generationmentioning

confidence: 99%

Solar Irradiance Nowcasting for Virtual Power Plants Using Multimodal Long Short-Term Memory Networks

et al. 2021

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The rapid penetration of photovoltaic generation reduces power grid inertia and increases the need for intelligent energy resources that can cope in real time with the imbalance between power generation and consumption. Virtual power plants are a technology for coordinating such resources and monetizing them, for example on electricity markets with real-time pricing or on frequency reserves markets. Accurate short-term photovoltaic generation forecasts are essential for such virtual power plants. Although significant research has been done on medium- and long-term photovoltaic generation forecasting, the short-term forecasting problem requires special attention to sudden fluctuations due to the high variability of cloud cover and related weather events. Solar irradiance nowcasting aims to resolve this variability by providing reliable short-term forecasts of the expected power generation capacity. Sky images captured in proximity to the photovoltaic panels are used to determine cloud behavior and solar intensity. This is a computationally challenging task for conventional computer vision techniques and only a handful of Artificial Intelligence (AI) methods have been proposed. In this paper, a novel multimodal approach is proposed based on two Long Short-Term Memory Networks (LSTM) that receives a temporal image modality of a stream of sky images, a temporal numerical modality of a time-series of past solar irradiance readings and cloud cover readings as inputs for irradiance nowcasting. The proposed nowcasting pipeline consists of a preprocessing module and an irradiance augmentation module that implements methods for cloud detection, Sun localization and mask generation. The complete approach was empirically evaluated on a real-world solar irradiance case study across the four seasons of the northern hemisphere, resulting in a mean improvement of 39% for multimodality.

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Section: Nowcasting For Vpp With Photovoltaic Generationmentioning

confidence: 99%

Solar Irradiance Nowcasting for Virtual Power Plants Using Multimodal Long Short-Term Memory Networks

et al. 2021

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“…However, the paper is good to implement if energy storage banks are used for standby power for balancing the intermittency issues of photovoltaic. Horizon Markov finding method (MFM) is selected in the paper [21] for the efficient control of a solar-oriented EV charging station. The model features the vehicle to grid (V2G) application to offer ancillary services and facilitates dynamic electric cost depends on the time of use (ToU) tariff and takes into consideration the ambiguity of vehicle owners' parking behaviors.…”

Section: Work On Smart Fast Charging Evmentioning

confidence: 99%

Novel Supervisory Management Scheme of Hybrid Sun Empowered Grid-Assisted Microgrid for Rapid Electric Vehicles Charging Area

et al. 2021

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The spread of electric vehicles (EV) contributes substantial stress to the present overloaded utility grid which creates new chaos for the distribution network. To relieve the grid from congestion, this paper deeply focused on the control and operation of a charging station for a PV/Battery powered workplace charging facility. This control was tested by simulating the fast charging station when connected to specified EVs and under variant solar irradiance conditions, parity states and seasonal weather. The efficacy of the proposed algorithm and experimental results are validated through simulation in Simulink/Matlab. The results showed that the electric station operated smoothly and seamlessly, which confirms the feasibility of using this supervisory strategy. The optimum cost is calculated using heuristic algorithms in compliance with the meta-heuristic barebones Harris hawk algorithm. In order to long run of charging station the sizing components of the EV station is done by meta-heuristic barebones Harris hawk optimization with profit of USD 0.0083/kWh and it is also validated by swarm based memetic grasshopper optimization algorithm (GOA) and canonical particle swarm optimization (PSO).

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“…Using the battery in an EV as energy storage in such vehicle to grid (V2G) combinations, the self-sufficiency of solar selfconsumption of household residentials increases [22]. In relation to V2G Technology, Wu Y. et al proposes a real-time energy management system (EMS), that allows for a 29-55% reduction of the total cost of a Photovoltaic assisted charging station [23].…”

Section: Introductionmentioning

confidence: 99%

Experimental Analysis of Residential Photovoltaic (PV) and Electric Vehicle (EV) Systems in Terms of Annual Energy Utilization

et al. 2021

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Electrification of powertrain systems offers numerous advantages in the global trend in vehicular applications. A wide range of energy sources and zero-emission propulsion in the tank to wheel significantly add to electric vehicles’ (EV) attractiveness. This paper presents analyses of the energy balance between micro-photovoltaic (PV) installation and small electric vehicle in real conditions. It is based on monitoring PV panel’s energy production and car electricity consumption. The methodology included energy data from real household PV installation (the most common renewable energy source in Poland), electric vehicle energy consumption during real driving conditions, and drivetrain operating parameters, all collected over a period of one year by indirect measuring. A correlation between energy produced by the micro-PV installation and small electric car energy consumption was described. In the Winter, small electric car energy consumption amounted to 14.9 kWh per 100 km and was 14% greater than summer, based on test requirements of real driving conditions. The 4.48 kW PV installation located in Poznań produced 4101 kWh energy in 258 days. The calculation indicated 1406 kWh energy was available for EV charging after household electricity consumption subtraction. The zero-emission daily distance analysis was done by the simplified method.

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Real-time energy management of photovoltaic-assisted electric vehicle charging station by markov decision process

Cited by 57 publications

References 49 publications

Solar Irradiance Nowcasting for Virtual Power Plants Using Multimodal Long Short-Term Memory Networks

Solar Irradiance Nowcasting for Virtual Power Plants Using Multimodal Long Short-Term Memory Networks

Novel Supervisory Management Scheme of Hybrid Sun Empowered Grid-Assisted Microgrid for Rapid Electric Vehicles Charging Area

Experimental Analysis of Residential Photovoltaic (PV) and Electric Vehicle (EV) Systems in Terms of Annual Energy Utilization

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