New energy bound-based model for optimal charging of electric vehicles with solar photovoltaic considering low-voltage network's constraints

Borray, Andrés Felipe Cortés; Garcés, Alejandro; Merino, Julia; Mazón, Javier

doi:10.1016/j.ijepes.2021.106862

Cited by 11 publications

(7 citation statements)

References 21 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Several controlled charging-discharging techniques were thoroughly discussed in detail in (Borray et al, 2021), classified as a controlled charge-discharge method, intelligent charging-discharging method, bi-directional charge-discharge method, and multistage hierarchical controlled charge-discharge method. The performance for each method was dictated by the system performance described in forms of overloading, deteriorating power quality and power loss.…”

Section: Ev Charging Strategiesmentioning

confidence: 99%

Optimal Sequential Distribution Planning for Low-Voltage Network With Electric Vehicle Loads

Sangob

Sirisumrannukul

2021

Front. Energy Res.

View full text Add to dashboard Cite

There has been a growing presence of electric vehicles in many countries including Thailand, where many forms of incentives have been provided to build integrated infrastructure, and to encourage drivers to switch to electric vehicles (EVs). Because the immediate entry of EVs unavoidably can alter household load profiles, reinforcement on the existing system based on traditional planning may not be sufficient and can introduce over or under capital and operating expenditure over the time horizon. Therefore, if distribution systems are unreadily prepared for such an uptake, three obvious problems can be expected: 1) voltage regulation, 2) overloads of the distribution feeders and the distribution transformers, and 3) high energy loss. In this paper, an activity-based, time-sequential Monte Carlo Simulation algorithm was comprehensively developed for uncontrollable and smart charging, given annually updated information of EV locations and number of EVs, their energy consumption, hourly average vehicle speed, number of daily trips, travel distance per trip, size of EV batteries, time to arrive home and time to leave home. Minimizing the annual sum of investment and operating costs over a planning period could then be sequentially solved by a Particle Swarm Optimization (PSO) algorithm. The results from a practical 122-bus, 24 kV/400 V distribution system with different scenarios of uncontrollable and smart charging show that the sequential optimization embedded with deterministic decision can help improve customer voltage profile, keep feeder and transformer loading within acceptable operating limits and offer significant cost savings from energy loss. As far as a large number of low-voltage networks, and the associated large sum of cost savings are concerned, the proposed planning framework is practical to be applied and expected to be served as a new guideline for future implementation in Thailand.

show abstract

Section: Ev Charging Strategiesmentioning

confidence: 99%

Optimal Sequential Distribution Planning for Low-Voltage Network With Electric Vehicle Loads

Sangob

Sirisumrannukul

2021

Front. Energy Res.

View full text Add to dashboard Cite

show abstract

“…In order to evaluate the effect of the voltage and loading level of the feeder in the coordination strategy, the linear approximations for these two parameters in ref. [6] were modified to include the PV power curtailment factor ζ i , t . As these approximations depend on the voltage‐and‐loading sensitivity coefficients of the network, these matrices are obtained using the P&O method described in ref.…”

Section: Optimisation Modelmentioning

confidence: 99%

“…Nonetheless, using the meta‐heuristic approach increases the complexity of the problem as it is treated like a non‐linear non‐convex optimisation problem that highly leads to getting stuck in a local solution. In a previous work [6], a coordination EV charging strategy based on a linear programmming model was defined. It aimed to maximise the EV's charging in an unbalanced grid by taking advantage of the PV power without exceeding the operational limits of the LV network, making use of its sensitivity coefficient matrices.…”

Section: Introductionmentioning

confidence: 99%

“…In general terms, the individual or combined analysis of EVs and PVs within a simulation framework are considered either as optimisation problems (e.g. linear [6], non-linear [2,3,7,12] and metaheuristic [5,8]) or deterministic approaches [4,[9][10][11][13][14][15]. However, to the knowledge of the authors, no paper considering a combined testbed for smart EV charging and PV curtailment is not found in the literature.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Optimal coordination of electric vehicle charging and photovoltaic power curtailment in unbalanced low voltage networks: An experimental case

Borray

Rauma

2022

IET Smart Grid

Self Cite

View full text Add to dashboard Cite

This study introduces a quadratic programming-based optimisation method to coordinate electric vehicle (EV) charging and photovoltaic (PV) curtailment in unbalanced low voltage (LV) networks. The proposed model is defined as a convex model that guarantees the optimal global solution of the problem avoiding the complexity of non-linear models and surpassing the limitations of local solutions derived from meta-heuristics algorithms reported in the literature. The coordination is carried out through a centralised controller installed at the header of the LV feeder. The objective of the proposed strategy is to minimise the power curtailment of all PV systems and maximise the power delivered to all EVs by optimising at every time step a suitable setpoint for the PV units and the charging rate of each EV connected without surpassing network constraints. A new energy-boundary model is also proposed to meet the energy requirements of all EVs, which is based on a recurrent function that depends on the arrival-and-desired energy states of the vehicle to compute its charging trajectory optimally. The effectiveness of the proposed coordination strategy was successfully proven through three scenarios in a laboratory environment, making use of two commercial EVs and a PV inverter in a Power Hardware-in-the-Loop setup.

show abstract

“…An essential problem with photovoltaic power plants is their low efficiency and significant energy loss during operation [10]. Therefore the main challenge of solar photovoltaic operations is extracting the maximum power generated.…”

Section: Introductionmentioning

confidence: 99%

Modified Perturb and Observe Approach in MPPT for a Standalone Photovoltaic System

Syahputra¹

2022

JET

View full text Add to dashboard Cite

This paper proposes a modified perturb and observe algorithm approach to increase the output power of an independent photovoltaic system. Today, photovoltaic application as renewable energy power plant has been prevalent. This popularity is because photovoltaic power plants are easy to apply on-grid and off-grid schemes. In standalone power generation applications, the increased photovoltaic output power is of great help to users as it contributes to increasing overall system efficiency. The perturb and observe algorithm has been known as a reliable and inexpensive method. However, the performance still needs to be improved. Therefore, this study proposes a modified perturb and observe algorithm approach. The research results show the superiority of the proposed method.

show abstract

New energy bound-based model for optimal charging of electric vehicles with solar photovoltaic considering low-voltage network's constraints

Cited by 11 publications

References 21 publications

Optimal Sequential Distribution Planning for Low-Voltage Network With Electric Vehicle Loads

Optimal Sequential Distribution Planning for Low-Voltage Network With Electric Vehicle Loads

Optimal coordination of electric vehicle charging and photovoltaic power curtailment in unbalanced low voltage networks: An experimental case

Modified Perturb and Observe Approach in MPPT for a Standalone Photovoltaic System

Contact Info

Product

Resources

About