A Two Stage Model for Optimum Allocation of Electric Vehicle Parking Lots in Smart Grids

Moradijoz, Mahnaz; Moazzen, Farid; Allahmoradi, Sarah; Moghaddam, Mohsen Parsa; Haghifam, Mahmoud‐Reza

doi:10.1109/sgc.2018.8777877

Cited by 7 publications

(4 citation statements)

References 12 publications

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“…The model also considers the potential source of electricity in she, that is, EVs and RBE which both are provided by STS. However, the allocation of EVs' parking lots and metro station is a bit challenging and need to be performed using a proper optimization method [37]. Figure 1 illustrates the graphical model of smart island.…”

Section: Features and Capabilitiesmentioning

confidence: 99%

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A novel energy management framework incorporating multi‐carrier energy hub for smart city

Esapour

Moazzen²,

Karimi

et al. 2022

IET Generation Trans & Dist

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The development of advanced and intelligent measurement instruments in recent years has increased the intelligence of modern energy systems, especially power systems. Besides, with the advancement of energy conversion technologies, these systems benefit from multi-carrier energy resources. Accordingly, this paper presents a model of smart city which considers various components, including smart transportation system (STS), microgrid (MG), and smart energy hub (SEH) with the ability of energy transformation. The proposed model addresses the islanded operation of a smart city that makes it a smart island. This island deploys the energy carriers of electricity, heat, gas and water as well. In addition, STS includes electric vehicle (EV) parking lots as well as metro system (MS) that can interactively exchange energy. More precisely, the different components of the smart island are modelled on the assumption of energy interdependency. In the proposed model, the water supply unit in SEH is provided which can be effective in reducing the cost of components by supplying water to them. In order to exchange energy within STS, metro stations have been optimally allocated using intelligent water drops (IWD) optimization method. In addition to smart island modelling, this paper quantifies the uncertainties within STS and MG using cloud theory. Eventually, the proposed model is simulated to ensure its effectiveness and accuracy.

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Section: Features and Capabilitiesmentioning

confidence: 99%

“…Equation ( 36) controls the state of charging or discharging. The balance of SEH in terms of heat and electricity is attained by applying Equations (37) and (38). When it comes to the balance between gas and power, Equation ( 39) adjusts the input to SEH.…”

Section: The Constraints Of Sehmentioning

confidence: 99%

A novel energy management framework incorporating multi‐carrier energy hub for smart city

Esapour

Moazzen²,

Karimi

et al. 2022

IET Generation Trans & Dist

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“…Ref. [20] presents a two‐stage deterministic modelling approach for the optimal allocation of the IPLs in the distribution network. In the first stage, the planning and operational costs are minimized and revenues are maximized considering electrical power losses, investment cost, and revenue of the IPLs.…”

Section: Introductionmentioning

confidence: 99%

Optimal allocation of intelligent parking lots in distribution system: A robust two‐stage optimization model

Mojarad

Sedighizadeh

Dosaranian‐Moghadam

2022

IET Electrical Syst in Trans

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Electrification of transportation is one of the new ways to deal with environmental issues. In order to reach sustainable development, efficient integration of the plug‐in electric vehicles (PEVs) into the distribution network (DN) plays a significant role. Establishing PEV intelligent parking lots (IPLs) is one of the important solutions to develop charging stations. However, one of the problems with IPLs is restrictions created by municipalities and DNs while the common parking lots are not faced with these constraints. The aim of this paper is to optimally allocate IPLs in order to minimize system costs through a two‐stage mathematical model. The system cost involves installation cost, cost of exchanging the electrical power with an upstream grid, cost of the electrical power loss, network reliability cost, and emissions cost. In the first stage, the behaviour of IPLs is optimized taking into account the market interactions for enhancing the profit of the IPL owner. In the second stage, the optimal IPL allocation is performed taking various network constraints into consideration. The robust optimization is developed to hedge the DN operator and the IPL owner against risk imposed uncertain variables. The proposed model is a Robust Mix Integer Linear Problem, which is solved using the CPLEX solver in GAMS software. The effectiveness and the efficiency of the proposed model are evaluated on the IEEE 12‐bus test network.

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“…For example, Reference 19 proposes a two‐stage stochastic optimization model whose first stage deals with the planning decisions pertaining to the optimal allocation of IPLs and the second stage assesses the day‐ahead operation of the specified IPLs under different scenarios of PEVs behaviors. Reference 20 presents a two‐stage deterministic modeling approach for optimal allocation of IPLs in the distribution network. In the first stage, the planning and operational costs are minimized and the revenues are maximized considering electrical power losses, investment cost, and revenue of the IPLs.…”

Section: Introductionmentioning

confidence: 99%

A two‐stage stochastic model based on information gap decision theory method for optimal allocation of intelligent parking lots in distribution systems considering severe uncertainties

Mojarad

Sedighizadeh

Dosaranian‐Moghadam

2021

Int Trans Electr Energ Syst

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Summary Electrification of transportation is one of the new ways to deal with environmental issues. In order to reach sustainable development, efficient integration of the plug‐in electric vehicles (PEVs) into the distribution network (DN) plays a significant role. Establishment of PEV intelligent parking lots (IPLs) is one of the important solutions to develop charging stations. However, one of the problems with IPLs is restrictions created by municipalities and DNs while the common parking lots are not faced with these constraints. The aim of this paper is the optimal allocation of IPLs through a two‐stage mathematical model in order to minimize system costs. The system cost involves installation cost, cost of exchanging electrical power with the upstream grid, cost of the electrical power loss, network reliability cost, and emissions cost. In the first stage, the behavior of IPLs is optimized taking into account the market interactions for enhancing the IPL owner's profit. In the second stage, optimal allocation of the IPL is performed considering various network constraints. Demand response is considered as Time of Use program. Information gap decision theory is developed to hedge the DN operator and IPL owner against the risk imposed by the information gap between the forecasted and actual uncertain variables. The effectiveness and efficiency of the proposed model are evaluated on the IEEE 33‐bus test network. In the end, the presented model with simultaneously optimization can lessen the total cost by 7.74%, 15.48%, and 19.27% compared to cases, which only optimize active power loss, reliability, and emissions, respectively.

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A Two Stage Model for Optimum Allocation of Electric Vehicle Parking Lots in Smart Grids

Cited by 7 publications

References 12 publications

A novel energy management framework incorporating multi‐carrier energy hub for smart city

A novel energy management framework incorporating multi‐carrier energy hub for smart city

Optimal allocation of intelligent parking lots in distribution system: A robust two‐stage optimization model

A two‐stage stochastic model based on information gap decision theory method for optimal allocation of intelligent parking lots in distribution systems considering severe uncertainties

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