Smart Microgrids: Optimal Joint Scheduling for Electric Vehicles and Home Appliances

Tushar, Mosaddek Hossain Kamal; Assi, Chadi; Maier, Martin; Uddin, Mohammad Faisal

doi:10.1109/tsg.2013.2290894

Cited by 226 publications

(91 citation statements)

References 17 publications

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“…Uncertainties for the RES are covered by using different stochastic approaches like Markov chains [16] or time series modelling [17] to have a forecast for the electricity generation by PV. In Tushar et al (2014) additionally to the PV prediction for the next 24 h with Markov Chains, the EVs arrival time is modeled as a Poisson Process. Their model is applied in a microgrid including home appliances with the goal to minimize the needed imported electricity from the microgrid.…”

Section: Related Workmentioning

confidence: 99%

Integrating renewable energy sources by electric vehicle fleets under uncertainty

Seddig

Jochem

Fïchtner

2017

Energy

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a b s t r a c tElectric vehicles are one of the concepts towards green and sustainable transportation systems. However, several uncertainties with respect to electricity demand and availability of electric vehicles as well as electricity supply by renewable energy sources influence an optimal scheduling through smart charging strategies. This paper investigates the possibilities to integrate additionally loads of uncertain renewable energy sources by smart charging strategies of three different electric vehicle fleets namely, com mercial customers, commuters, and opportunity parkers. Therefore, data from an empiric field test with a public charging infrastructure in a parking garage with a photovoltaic system is taken. Various stra tegies are analyzed, considering the changing individual electricity demand, restrictions and parking times of electric vehicle fleets by combining a Monte Carlo simulation approach with different meth odologies like a heuristic algorithm, an optimization model and stochastic programming. The numerical results indicate that the domestic photovoltaic generation of the car park can be fully used by the electric vehicle fleets for charging and the utilization of photovoltaic can be doubled when comparing uncon trolled and optimized charging strategies. The commuter fleet has the highest CO 2 emission reduction potential of all three electric vehicle fleets. Moreover, load management decreases costs, even when uncertainties are considered.

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Section: Related Workmentioning

confidence: 99%

Integrating renewable energy sources by electric vehicle fleets under uncertainty

Seddig

Jochem

Fïchtner

2017

Energy

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“…Compared to traditional electrical grids, smart grids are environmentally-friendly and more intelligent in the information communication. Energy generators in traditional electrical grids, which primarily consume fossil fuel as their energy source, produce about 41% of the whole world greenhouse gases and have a huge negative effect on the environment [2]. With the appearance of problems with fossil energy depletion and the greenhouse effect, energy generation in smart grids through renewable energy resources, such as wind power, solar power, and geothermal power, has become an attractive alternative and contributes to solving the problem [3][4][5].…”

Section: Introductionmentioning

confidence: 99%

Game-theoretic energy management with storage capacity optimization in the smart grids

Gao

Liu

Wei

et al. 2018

J. Mod. Power Syst. Clean Energy

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With the development of smart grids, a renewable energy generation system has been introduced into a smart house. The generation system usually supplies a storage system with the capability to store the produced energy for satisfying a user's future demand. In this paper, the main objective is to determine the best strategies of energy consumption and optimal storage capacities for residential users, which are both closely related to the energy cost of the users. Energy management with storage capacity optimization is studied by considering the cost of renewable energy generation, depreciation cost of storage and bidirectional energy trading. To minimize the cost to residential users, the non-cooperative game-theoretic method is employed to formulate the model that combines energy consumption and storage capacity optimization. The distributed algorithm is presented to understand the Nash equilibrium which can guarantee Pareto optimality in terms of minimizing the energy cost. Simulation results show that the proposed game approach can significantly benefit residential users. Furthermore, it also contributes to reducing the peak-to-average ratio (PAR) of overall energy demand.

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“…On the other hand, the islanded mode is turned on and activated when the microgrid is disconnected from the utility grid, in which the necessary power must be locally provided by distributed power resources or power storage systems in the microgrid. For example, in case of blackout, backup battery systems such as uninterruptible power supply systems and plugin electric vehicles automatically discharge necessary power for home appliances connected to the microgrid [10]- [15]. In such an islanded mode, battery systems should regulate the electric voltage to track a predetermined AC voltage reference (usually 50 or 60 Hz sinusoids) as promptly as possible, so that the power supply is of the same quality from the utility grid.…”

Section: Introductionmentioning

confidence: 99%

Robust AC Voltage Regulation of Microgrids in Islanded Mode with Sinusoidal Internal Model

Hayashi

Nagahara

Yamämoto

2017

SICE Journal of Control, Measurement, and System Integration

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: This paper shows that the H ∞ control is an effective tool for electric voltage regulation. We here consider robust AC voltage regulation of microgrids in an islanded mode. When a microgrid is disconnected from a utility grid, it automatically switches to an islanded mode to provide necessary power using a battery system until the grid is recovered.In the islanded mode, it is important to regulate the electric voltage generated in the grid to track a predetermined AC voltage reference. A difficulty is that there exits unmodeled dynamics in the grid that may cause large power fluctuations.To resolve this problem, we adapt the H ∞ control with a sinusoidal internal model to robust AC voltage regulation in microgrids. Simulation and experimental results confirm that the proposed H ∞ control can achieve robust tracking performance.

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Smart Microgrids: Optimal Joint Scheduling for Electric Vehicles and Home Appliances

Cited by 226 publications

References 17 publications

Integrating renewable energy sources by electric vehicle fleets under uncertainty

Integrating renewable energy sources by electric vehicle fleets under uncertainty

Game-theoretic energy management with storage capacity optimization in the smart grids

Robust AC Voltage Regulation of Microgrids in Islanded Mode with Sinusoidal Internal Model

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