Mohsen Kalantar Neyestanaki

Official source

https://people.epfl.ch/mohsen.kalantar?lang=fr

À propos de ce résultat

Cette page est générée automatiquement et peut contenir des informations qui ne sont pas correctes, complètes, à jour ou pertinentes par rapport à votre recherche. Il en va de même pour toutes les autres pages de ce site. Veillez à vérifier les informations auprès des sources officielles de l'EPFL.

Unités associées (3)

Unités associées

Chargement

Cours enseignés par cette personne

Chargement

Domaines de recherche associés (4)

Domaines de recherche associés

Chargement

Publications associées (6)

Publications associées

Chargement

Personnes menant des recherches similaires (103)

Personnes menant des recherches similaires

Chargement

Environmental concerns are leading to a fast transition in electric power systems towards replacing fossil fuel and nuclear generation with renewable generation. This transition has two significant implications for electric power systems:1-The capacity of conventional dispatchable electric power plants, which are the main providers of power flexibility , is sharply falling. It is notable that the security of electric power systems can be preserved if and only if there is an adequate amount of power flexibility to guarantee the frequency stability, voltage regulation, power quality, and congestion management.2-The share of renewable energy sources (RESs) in the electric power generation portfolio is steeply soaring. It raises a significant stress on electric power systems due to the fact that the generated electricity from RESs is intrinsically intermittent and accompanied with uncertainties.The simultaneous realization of these two issues puts electric power systems in a turning point. This thesis devotes a deep attention to the power flexibility provision issue with the purpose of empowering transmission system operators (TSOs) and distribution system operators (DSOs) to steer electric power systems securely in this emerging architecture. To this end, it sets out to unlock the potential power flexibility of distributed energy resources (DERs) located in distribution networks. The first part of the thesis deals with the problem from TSO's perspective. It develops two decision making tools for TSOs to help them optimally quantify their required power flexibility from flexibility providers (including flexible distribution networks) in a decentralized energy and flexibility market structure. The first tool concentrates solely on active power flexibility and accordingly offers a framework to model aggregated active power flexibility of distribution networks from TSO's point of view. In contrast, the second tool introduces a holistic TSO-DSO coordination framework to enable TSO and DSO to exchange both active/reactive power flexibility. Both developed tools employ mathematical techniques to cast the TSO's decision making process as a two-stage linear stochastic optimization problem while accounting for risk associated to the uncertainties. The frameworks lay a ground for TSO and DSOs to exchange power flexibility without having to reveal their confidential grids data.The second part of the thesis deals with the problem from DSO's perspective. It first concentrates on an active distribution network (ADN) and constructs a set of linear scenario-based robust optimization problems to characterize the maximum active/reactive powers flexibility that the ADN can provide upon request at its point of common coupling (PCC) to the upper-layer grid. Second, it constructs a linear grid&uncertainties-cognizant ADN management method to determine the amount of active/reactive powers flexibility that should be provided by each DER during the real-time operation in such a way that the ADN can provide, with minimum deviation, the active/reactive powers flexibility requested by the upper-layer grid at the PCC.In addition to dealing with the problem from both TSO's and DSO's perspectives, a privileged feature of the thesis is that it offers linear tractable algorithms to deal with all above-mentioned tasks while considering grid's constraints and uncertainties stemming from the forecast errors of demand and renewable generation.

EPFL2022

Chargement

Characterizing the Reserve Provision Capability Area of Active Distribution Networks: A Linear Robust Optimization Method

Mokhtar Bozorg, Mohsen Kalantar Neyestanaki, Fabrizio Sossan

Distributed energy resources (DERs) installed in active distribution networks (ADNs) can be exploited to provide both active and reactive power reserves to the upper-layer grid (i.e., sub-transmission and transmission systems) at their connection point. This paper introduces a method to determine the capability area of an ADN for the provision of both active and reactive power reserves while considering the forecast errors of loads and stochastic generation, as well as the operational constraints of the grid and DERs. The method leverages a linearized load flow model and introduces a set of linear scenario-based robust optimization problems to estimate the reserve provision capability (RPC) area of the ADN. It is proved that, under certain assumptions, the RPC area is convex. The performance of the proposed method is tested on a modified version of the IEEE 33-bus distribution test system.

2021

Chargement

Coordinating Distributed Energy Resources and Utility-Scale Battery Energy Storage System for Power Flexibility Provision Under Uncertainty

Mohsen Kalantar Neyestanaki

Relying on the power flexibility of distributed energy resources (DERs) located in an active distribution network (ADN), this ADN will be able to provide power flexibility to the upper-layer grid at their point of common coupling (PCC). The power flexibility is defined as additional bi-directional active/reactive powers a resource can provide to the grid by adjusting its operating point. In this context, this paper presents a two-stage ADN management method to deliver, at the PCC, the power flexibility that the upper-layer grid operator would request minutes-ahead real-time operation. The first stage updates the power set-points of DERs considering their offer curves as well as the uncertainties stem from the short-term forecast errors of demand and renewable generation profiles. The inter-temporal constraints and losses of the grid are accounted for by exploiting a linearized dynamic optimal power flow model, whereby the first stage is implemented as a linear scenario-based optimization problem. Then, in real-time operation, relying on a linear optimization problem, the second stage adjusts the power flexibility injection of a utility-scale battery energy storage system (ESS) to mitigate the imbalance at the PCC inherent in the above-mentioned uncertainties. The performance of the method is tested on a real ADN.

2021

Chargement

EPFL2022