Coordination of Generation Scheduling with PEVs Charging in Industrial Microgrids

Derakhshandeh, Sayed Yaser; Masoum, Amir S.; Deilami, Sara; Masoum, Mohammad A. S.; Golshan, Mohammad

doi:10.1109/tpwrs.2013.2257184

Cited by 158 publications

(97 citation statements)

References 30 publications

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“…used a new unit commitment model which can simulate the interactions among plug-in hybrid electric vehicles (PHEVs), wind power, and demand response (DR). The benefits of EVs which work as storage devices are also discussed in different kinds of microgrids, including residential microgrid [22], industrial microgrid [23] and commercial building microgrid [24]. However, the variability of the aggregate battery storage caused by EVs' driving patterns is not discussed.…”

Section: Related Workmentioning

confidence: 99%

“…EV driving patterns which directly determine the parameters of the aggregate battery storage should gain more attention; 2) the variability of aggregate battery caused by individual EV's driving pattern and the battery cycle life reduction caused by V2G implementation are not considered in [20][21][22][23][24]. There are also few works on a proper framework to integrate the coordinated EV charging/discharging allocation into the microgrid energy management; 3) how to restrain the impact of multiple neighboring microgrids on the main grid is another focus of this work, which, however, is not considered by most of related works [10][11][12][13][14][15][16].…”

Section: Related Workmentioning

confidence: 99%

“…Equation (19) defines the minimum SOC when the EV leaves home. The limit of charging/discharging power is shown in (22) and (23). The depth of discharge (DOD) must be less than (1 soc − ) to avoid over-discharge, as shown in (24).…”

Section: Ev Aggregator Scheduling Problemmentioning

confidence: 99%

See 2 more Smart Citations

Integrated Energy Exchange Scheduling for Multimicrogrid System With Electric Vehicles

Wang

Guan

et al. 2016

IEEE Trans. Smart Grid

153

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Abstract-Electric vehicles (EVs) can be considered as flexible mobile battery storages in microgrids. For multiple microgrids in an area, coordinated scheduling on charging and discharging are required to avoid power exchange spikes between the multimicrogrid system and the main grid. In this paper, a two-stage integrated energy exchange scheduling strategy for multimicrogrid system is presented, which considers EVs as storage devices. Then several dual variables, which are representative of the marginal cost of proper constraints, are utilized to form an updated price, thereby being a modification on the original electricity price. With this updated price signal, a price-based decentralized scheduling strategy is presented for the Microgrid Central Controller (MGCC). Simulation results show that the two-stage scheduling strategy reduces the electricity cost and avoids frequent transitions between battery charging/discharging states. With the proposed decentralized scheduling strategy, each microgrid only needs to solve its local problem and limits the total power exchange within the safe range.Index Terms--Microgrid, electric vehicle, energy exchange, dual variable, updated price signal, decentralized scheduling strategy. I. NOMENCLATURE Index:i Index for microgrid,, ( ) i s B t Lower bound of the aggregate batteries' remaining energy in microgrid i during t in scenario s (kWh).Upper bound of the aggregate batteries' remaining energy in microgrid i during t in scenario s (kWh). ( ) C tOriginal electricity price during t (CNY/kWh).

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Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

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Integrated Energy Exchange Scheduling for Multimicrogrid System With Electric Vehicles

Wang

Guan

et al. 2016

IEEE Trans. Smart Grid

153

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“…Another concept is produced using the smart grid and the EVs, called virtual power plant (VPP), where a cluster of vehicles are considered as a power plant and dealt like one in system. [153][154][155], thus serving the increase of commercial RES deployment. The V2G structure is further helpful to integrate RES for charging of EVs, and to the grid as well, as it enables the selling of energy to the grid when there is surplus, for example, when vehicles are parked and the system knows the user will not need the vehicle before a certain time.…”

Section: Positive Impactsmentioning

confidence: 99%

A Comprehensive Study of Key Electric Vehicle (EV) Components, Technologies, Challenges, Impacts, and Future Direction of Development

Un-Noor¹,

Padmanaban²,

Mihet‐Popa³

et al. 2017

Preprint

154

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Electric vehicles (EV) are getting more commonplace in the transportation sector in recent times. As the present trend suggests, this mode of transport is likely to replace the internal combustion engine (ICE) vehicles in near future. Each of the main EV components has a number of technologies that are currently in use or can become prominent in the future. EVs can cause significant impacts on the environment, power system, and other related sectors. The present power system can face huge instabilities with enough EV penetration; but with proper management and coordination, EVs can be turned into a major contributor to the successful implementation of smart grid. There are possibilities of immense environmental benefits as well, as the EVs can extensively reduce the greenhouse gas emission from the transportation sector. However, there are some major obstacles for EVs to overcome before replacing the ICE vehicles totally. This paper is focused on reviewing all the useful data available on EV configurations, energy sources, motors, charging techniques, optimization techniques, impacts, trends, and possible directions of future developments. Its objective is to provide an overall picture of the current EV technology and ways of future development to assist in future researches in this sector.

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“…In [17], an EMS for a virtual power plant was proposed to minimize the electricity generation cost and to utilize renewable energy sufficiently. Authors in [18] presented a dynamic optimal power flow control for power and heat generation scheduling while considering PV generations coupled with storage systems. A flexible battery management system was developed to optimize the duration (hours) of charging and discharging battery for optimal power flow control in distribution networks [19].…”

Section: Introductionmentioning

confidence: 99%

Demand side management of photovoltaic-battery hybrid system

2015

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In the electricity market, customers have many choices to reduce electricity cost if they can economically schedule their power consumption. Renewable hybrid system, which can explore solar or wind sources at low cost, is a popular choice for this purpose nowadays. In this paper optimal energy management for a grid-connected photovoltaic-battery hybrid system is proposed to sufficiently explore solar energy and to benefit customers at demand side. The management of power flow aims to minimize electricity cost subject to a number of constraints, such as power balance, solar output and battery capacity. With respect to demand side management, an optimal control method (open loop) is developed to schedule the power flow of hybrid system over 24 hours, and model predictive control is used as a closed-loop method to dispatch the power flow in real-time when uncertain disturbances occur. In these two kinds of applications, optimal energy management solutions can be obtained with great cost savings and robust control performance.

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Coordination of Generation Scheduling with PEVs Charging in Industrial Microgrids

Cited by 158 publications

References 30 publications

Integrated Energy Exchange Scheduling for Multimicrogrid System With Electric Vehicles

Integrated Energy Exchange Scheduling for Multimicrogrid System With Electric Vehicles

A Comprehensive Study of Key Electric Vehicle (EV) Components, Technologies, Challenges, Impacts, and Future Direction of Development

Demand side management of photovoltaic-battery hybrid system

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