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About

I had my M.Sc. degree in power system electrical engineering from Iran University of Science and Technology (IUST), Tehran, Iran. I pursued my PhD in Industrial Engineering and Management from University of Beira Interior (UBI), Covilhã, Portugal. Currently, I am a Postdoc researcher in CPES. My area of expertise includes electricity markets, electric vehicles integration in power systems, renewable resources uncertainty, stochastic programming and optimization. 

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Details

Details

  • Name

    Nilufar Neyestani
  • Cluster

    Power and Energy
  • Role

    Assistant Researcher
  • Since

    15th May 2016
007
Publications

2020

Wind variability mitigation using multi-energy systems

Authors
Coelho, A; Neyestani, N; Soares, F; Lopes, JP;

Publication
International Journal of Electrical Power and Energy Systems

Abstract
Around the world, there is a great concern with the emission of greenhouse gases, creating great interest in turning the energy systems more sustainable. Multi-energy systems are considered as a potential solution to help to this cause and in recent years, it has gained much attention from both research and industry. In this paper, an optimization model is proposed to use the flexibility of multi-energy systems to mitigate the uncertainty associated with wind generation. The differences between the flexibility provided by multi-energy systems and electrical storage systems in the network were studied. The results prove that the flexibility of the multi-energy systems can benefit the system in several aspects and provide insights on which is the best approach to take full advantage of renewable resources even when a high degree of uncertainty is present. © 2019 Elsevier Ltd

2018

Strategic Behavior of Multi-Energy Players in Electricity Markets as Aggregators of Demand Side Resources using a Bi-level Approach

Authors
Yazdani Damavandi, M; Neyestani, N; Shafie khah, M; Contreras, J; Catalao, JPS;

Publication
IEEE Transactions on Power Systems

Abstract

2018

Effects of PEV Traffic Flows on the Operation of Parking Lots and Charging Stations

Authors
Neyestani, N; Damavandi, MY; Chicco, G; Catalao, JPS;

Publication
IEEE Transactions on Smart Grid

Abstract
The introduction of plug-in electric vehicles (PEVs) in the electrical system is bringing various challenges. The main issue is incorporating the PEV owner’s preferences in the models. One of the main attributes representing the preference of the owners is their travel purposes, impacting on the traffic flow pattern. The PEVs’ traffic pattern defines the required charging schedule of the PEVs and consequently characterizes the operation of the charging facilities such as PEV parking lots (PLs). The deployment of resources such as PEV PL requires a detailed modeling of the factors affecting their operation. In this regard, this paper aims to model the power flow of the PEVs based on their traffic flow. Different travel types and purposes are considered for the PEVs traffic modeling. Two types of charging infrastructure (i.e., PLs and individual charging stations) are considered. The study is performed on a distribution network categorized based on the consumption patterns of the zones. IEEE

2018

Aggregation of Distributed Energy Resources Under the Concept of Multienergy Players in Local Energy Systems

Authors
Yazdani Damavandi, M; Neyestani, N; Chicco, G; Shafie Khah, M; Catalao, J;

Publication
2018 IEEE POWER & ENERGY SOCIETY GENERAL MEETING (PESGM)

Abstract

2017

Plug-In Electric Vehicles Parking Lot Equilibria With Energy and Reserve Markets

Authors
Neyestani, N; Damavandi, MY; Shafie Khah, M; Bakirtzis, AG; Catalao, JPS;

Publication
IEEE TRANSACTIONS ON POWER SYSTEMS

Abstract
This paper proposes a comprehensive model for the interactions of the plug-in electric vehicles (PEVs) involved parties. An aggregator with mixed resources is assumed to be the interface between the parking lot (PL) and the upstream energy and reserve markets. On the other hand, the interactions of the PEV owners and the PL are also modeled as they impose restrictions to the PL's behavior. Therefore, a bilevel problem is constructed where in the upper level the objective of the aggregator is to maximize its profit through its interactions, and in the lower level the PL maximizes its own profit limited to the preferences of PEVs. The objectives of the upper and lower levels are contradictory; hence, an equilibrium point should be found to solve the problem. In this regard, the duality theorem is employed to convert the bilevel model to a mathematical program with equilibrium constraints. The model is implemented on the IEEE 37-bus network with added distributed generations. Various cases are thoroughly investigated and conclusions are duly drawn.