Transactive Energy Management Framework for Active Distribution Systems

Rajaei, Ali; Fattaheian‐Dehkordi, Sajjad; Fotuhi‐Firuzabad, Mahmud; Lehtonen, Matti

doi:10.1109/sest50973.2021.9543174

Cited by 7 publications

(8 citation statements)

References 14 publications

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“…Nevertheless, the proposed approaches in [30]- [31] have focused on economic dispatch and overlooked the operational constraints of electrical networks. An ADMM-based framework is proposed in [32] to enable the DSO to optimize the energy imbalance in a multi-agent energy system. This paper has utilized TECSs to minimize the cost of the system associated with the energy imbalance between day-ahead and real-time operational planning of the system.…”

Section: Introductionmentioning

confidence: 99%

“…This paper has utilized TECSs to minimize the cost of the system associated with the energy imbalance between day-ahead and real-time operational planning of the system. As a result, in [32], the proposed TECSs are associated with the power request of agents at the real-time operation. However, [32] has not considered the intense-ramping management in local DNs, which is corresponding with the difference between the power request of entities at two sequential time-steps.…”

Section: Introductionmentioning

confidence: 99%

“…As a result, in [32], the proposed TECSs are associated with the power request of agents at the real-time operation. However, [32] has not considered the intense-ramping management in local DNs, which is corresponding with the difference between the power request of entities at two sequential time-steps. On the other hand, [32] has not taken into account the stochastic programming and the conditional value at risk (CVaR) to model the resources uncertainties.…”

Section: Introductionmentioning

confidence: 99%

“…However, [32] has not considered the intense-ramping management in local DNs, which is corresponding with the difference between the power request of entities at two sequential time-steps. On the other hand, [32] has not taken into account the stochastic programming and the conditional value at risk (CVaR) to model the resources uncertainties. Respectively, [32] aims to maximize the profit of the local DN in the real-time operation, while this paper strives to provide operational service to the power grid in case of intense-ramping happening in the DN.…”

Section: Introductionmentioning

confidence: 99%

“…On the other hand, [32] has not taken into account the stochastic programming and the conditional value at risk (CVaR) to model the resources uncertainties. Respectively, [32] aims to maximize the profit of the local DN in the real-time operation, while this paper strives to provide operational service to the power grid in case of intense-ramping happening in the DN. Moreover, energy management in future networked-MG systems is studied in [33] utilizing the ADMM-algorithm.…”

Section: Introductionmentioning

confidence: 99%

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A Distributed Framework for Intense Ramping Management in Distribution Networks

Fattaheian‐Dehkordi

Abbaspour

Fotuhi‐Firuzabad

et al. 2023

IEEE Trans. Smart Grid

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High-penetration of renewable energy sources (RESs) in power networks has resulted in new operational challenges in the system. Accordingly, due to the uncertainty as well as variability of power-outputs of RESs, the flexibility ramping capacity of the system should be improved. Accordingly, system operators would rely on local responsive resources (LRSs) in distribution networks (DNs) to guarantee the demand-supply balance in each area of the system and minimize its associated ramping requirements. Nevertheless, the introduction of multimicrogrid (multi-MG) structures would limit the direct-access of system operators over the LRSs scheduling. As a result, this paper aims to develop a novel framework for intense-ramping management in multi-MG systems to settle the demand-supply gap in the system while addressing the distributed nature of the network. Respectively, alternating direction method of multipliers (ADMM) is employed to develop a decentralized coordination scheme in the system. Moreover, transactive energy control signals are utilized in the context of the ADMM-algorithm in order to exploit the LRSs scheduling to address the ramping constraints of the overall system. Lastly, the scheme is simulated on 37-bus and 123-bus DNs to analyze its efficacy in the management of intense ramping conditions in multi-MG DNs.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

A Distributed Framework for Intense Ramping Management in Distribution Networks

Fattaheian‐Dehkordi

Abbaspour

Fotuhi‐Firuzabad

et al. 2023

IEEE Trans. Smart Grid

Self Cite

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Distributed reactive power management in multi‐agent energy systems considering voltage profile improvement

Tofighi‐Milani,

Fattaheian‐Dehkordi,

Fotuhi‐Firuzabad

et al. 2023

IET Generation Trans & Dist

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In recent years, distributed structures have been developed in distribution networks as a result of privatization as well as integration of independently operated distributed energy resources (DERs) into the grid. In this context, effective management techniques seem to be necessary to enable decentralized operation of systems that have been consisted of multiple agents. Accordingly, novel management schemes should be applied in such systems to enable the distributed reactive power management, which would finally improve voltage profile in the network. As a result, this paper develops a distributed algorithm for reactive power management in multi‐agent distribution systems with the aim of improving the voltage profile of the grid. Correspondingly, in the proposed framework, several cost functions are developed to model the effects of reactive power management on the system from the distribution system operator (DSO) as well as agents’ perspectives. Consequently, the proposed reactive power management algorithm would result in voltage profile improvement, while each agent of the system merely strives to maximize its own profits. Accordingly, the proposed scheme ensures the privacy of independent agents. Finally, the proposed scheme is applied on the modified IEEE‐37‐bus test system to investigate its effectiveness on Peer‐to‐Peer (P2P) reactive power management in multi‐agent systems.

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