Mathematical modeling of electric vehicles contributions in voltage security of smart distribution networks

Pirouzi, Sasan; Aghaei, Jamshid

doi:10.1177/0037549718778766

Cited by 53 publications

(43 citation statements)

References 37 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Also, two strategies for EVs charging based on refs. 26,30 are represented in this section: Strategy I : EVs starts charging action after being connected to the network and, thus, they plugged‐out from the network if EVs battery is fully charged. Strategy II : EVs are charged based on energy price and network operating limits to reduce charging cost and heighten the rate of EVs penetration into the network. …”

Section: Numerical Resultsmentioning

confidence: 99%

See 1 more Smart Citation

Two‐stage coupling of coordinated energy management and self‐healing strategies in a smart distribution network considering coupling neighbouring microgrids according to autonomous decentralized restoration technique

Zaheri

Khederzadeh

2020

Int Trans Electr Energ Syst

View full text Add to dashboard Cite

One of the central approaches in the smart grid is to restore the smart distribution network (SDN) including different renewable sources and storage systems as microgrid formwork under fault conditions. Therefore, the automatic restoration processes need optimal power flow results in the SDN at fault times. Hence, this study proposed the optimal two‐stage coordinated energy management approach (CEMA) and self‐healing strategy (SHS) in the SDN in the presence of coupling neighbouring microgrids (CNMGs) according to autonomous decentralized restoration technique (ADRT). In the first stage, the SDN operation cost receiving from the upstream grid was minimized to obtain flexible and reliable network, followed by addressing network power flow equations, CNMG constraints including the renewable energy sources (RESs), energy storage systems (ESSs) and electric vehicles (EVs), and SDN operating limits. In the second stage, the optimal model of the ADRT formwork was defined based on the multi‐agent system (MAS). Also, the suitable restoration path was obtained with different zone agents distributed across the network CNMGs considering the minimization of the difference between the number of switching operation and priority loads restored as the normalized objective function. Furthermore, the scenario‐based stochastic programming was used to model the uncertainty of energy price, load, RES power, and EVs parameters. Finally, the proposed problem was solved by the Grey Wolf Optimization (GWO) algorithm and simulated on 33‐bus radial distribution network using MATLAB software. According to numerical results, the proposed strategy can offer the self‐healing and flexible‐reliable SDN in addition to the well‐suited overloading management for CNMGs.

show abstract

Section: Numerical Resultsmentioning

confidence: 99%

“…The objective function equation of the first stage problem is presented in Equation (1) that is applied to minimize the SDN expected energy cost of the upstream network 25‐28 . Hence, it has been predicted that the local power sources supply the SDN loads.…”

Section: Two‐stage Model Of the Coupling Of Cema And Shs In Sdnmentioning

confidence: 99%

Two‐stage coupling of coordinated energy management and self‐healing strategies in a smart distribution network considering coupling neighbouring microgrids according to autonomous decentralized restoration technique

Zaheri

Khederzadeh

2020

Int Trans Electr Energ Syst

View full text Add to dashboard Cite

show abstract

“…In the end, the third part of Eq. ( 1) minimizes the symmetry of the VSI [23]. The worst security index (WSI), with a value between 0 and 1, is employed here to analyze voltage security.…”

Section: Iimodel Of Proposed Problemmentioning

confidence: 99%

A Framework of Electricity Market Based on Two-Layer Stochastic Power Management for Microgrids

et al. 2022

View full text Add to dashboard Cite

This article develops a novel multi-microgrids (MMGs) participation framework in the dayahead energy and ancillary services, i.e. services of reactive power and reserve regulation, markets incorporating the smart distribution network (SDN) objectives based on two-layer power management system (PMS). A bi-level optimization structure is introduced wherein the upper level models optimal scheduling of SDN in the presence of MMGs while considering the bilateral coordination between microgrids (MGs) and SDN's operators, i.e. second layer's PMS. This layer is responsible for minimizing energy loss, expected energy not-supplied, and voltage security as the sum of weighted functions. In addition, the proposed problem is subject to linearized AC optimal power flow (LAC-OPF), reliability and security constraints to make it more practical. Lower level addresses participation of MGs in the competitive market based on bilateral coordination among sources, active loads and MGs' operator (first layer's PMS). The problem formulation then tries to minimize the difference between MGs' cost and revenue in markets while satisfying constraints of LAC-OPF equations, reliability, security, and flexibility of the MGs. Karush-Kuhn-Tucker method is exploited to achieve a single-level model. Moreover, a stochastic programming model is introduced to handle the uncertainties of load, renewable power, energy price, the energy demand of mobile storage, and availability of network equipment. The simulation results confirm the capabilities of the suggested stochastic two-layer scheme in simultaneous evaluation of the optimal status of different technical and economic indices of the SDN and MGs.INDEX TERMS Two-layer power management system, Energy and ancillary services markets, Multi-criteria objectives, Multi-microgrids, Multi-objective bi-level optimization.

show abstract

“…Moreover, the EV parking lot model is expressed in (24)-(29) [25], where the balance between EVs' active power from the VPP viewpoint and all EVs batteries in the parking lot is given by (24), and EV charger power losses in the parking lot are calculated by (25). Also, the required energy/charge rate of all EVs batteries in the parking lot is stated by (26) and (27). Moreover, the power/harmonic current capacity limit of all EVs chargers in the parking lot is presented by (28) and (29).…”

Section: Vpp Model (Second Level)mentioning

confidence: 99%

Bi‐level power management strategy in harmonic‐polluted active distribution network including virtual power plants

Rohani

Abasi

Beigzadeh

et al. 2021

IET Renewable Power Gen

View full text Add to dashboard Cite

In this paper, a bi‐level power management strategy is presented for an active distribution network (ADN) in the presence of virtual power plant (VPP). In the proposed strategy, VPP contains renewable energy source (RES), energy storage system (ESS) and electric vehicles (EVs) parking lot coordinated with VPP operator (VPPO), and there is a coordinated framework between VPPO and distribution system operator. The proposed power management strategy (PMS) is considered in the context of the bi‐level optimization problem. In the first level, the optimal harmonic power flow formulation of the ADN is considered by minimizing the summation of energy cost, voltage deviation function and voltage THD% as a normalized objective function. In the second level, the VPP is modeled according to the framework of day‐ahead energy and ancillary services markets. In the next step, the linear format of the proposed non‐linear original problem is obtained with an optimal solution and low calculation burden. Also, the Karush‐Kuhn‐Tucker condition is used to convert the proposed bi‐level PMS approach to a single‐level model, and the scenariobased stochastic programming models the uncertainty of load, energy price, RES power, and EVs demand. Finally, the proposed strategy is applied on the 33‐bus distribution network using GAMS software.

show abstract

Mathematical modeling of electric vehicles contributions in voltage security of smart distribution networks

Cited by 53 publications

References 37 publications

Two‐stage coupling of coordinated energy management and self‐healing strategies in a smart distribution network considering coupling neighbouring microgrids according to autonomous decentralized restoration technique

Two‐stage coupling of coordinated energy management and self‐healing strategies in a smart distribution network considering coupling neighbouring microgrids according to autonomous decentralized restoration technique

A Framework of Electricity Market Based on Two-Layer Stochastic Power Management for Microgrids

Bi‐level power management strategy in harmonic‐polluted active distribution network including virtual power plants

Contact Info

Product

Resources

About