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Your search keyword '"Dehghanian, Payman"' showing total 182 results
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182 results on '"Dehghanian, Payman"'

1. A Federated Deep Learning Approach for Privacy-Preserving Real-Time Transient Stability Predictions in Power Systems

Author

Hijazi, Maeshal and Dehghanian, Payman

Subjects
Electrical Engineering and Systems Science - Systems and Control
Abstract

Maintaining the privacy of power system data is essential for protecting sensitive information and ensuring the operation security of critical infrastructure. Therefore, the adoption of centralized deep learning (DL) transient stability assessment (TSA) frameworks can introduce risks to electric utilities. This is because these frameworks make utility data susceptible to cyber threats and communication issues when transmitting data to a central server for training a single TSA model. Additionally, the centralized approach demands significant computational resources, which may not always be readily available. In light of these challenges, this paper introduces a federated DL-based TSA framework designed to identify the operating states of the power system. Instead of local utilities transmitting their data to a central server for centralized model training, they independently train their own TSA models using their respective datasets. Subsequently, the parameters of each local TSA model are sent to a central server for model aggregation, and the resulting model is shared back with the local clients. This approach not only preserves the integrity of local utility data, making it resilient against cyber threats but also reduces the computational demands for local TSA model training. The proposed approach is tested on four local clients each having the IEEE 39-bus test system., Comment: 2024 International Conference on Smart Grid Synchronized Measurements & Analytics (SGSMA)

Published
2024

15. Fueling the seaport of the future: Investments in low‐carbon energy technologies for operational resilience in seaport multi‐energy systems.

Author

Xie, Chengzhi, Dehghanian, Payman, and Estebsari, Abouzar

Subjects
*WIND power, *HARBORS, *RENEWABLE energy sources, *SOLAR heating, *EXTREME weather, *CLEAN energy, *REMOTE control
Abstract

The ability to withstand and recover from disruptions is essential for seaport energy systems, and in light of the growing push for decarbonization, incorporating clean energy sources has become increasingly imperative to ensure resilience. This paper proposes a resilience enhancement planning strategy for a seaport multi‐energy system that integrates various energy modalities and sources, including heating, cooling, hydrogen, solar, and wind power. The planning strategy aims to ensure the reliable operation of the system during contingency events, such as power outages, equipment failures, or extreme weather incidents. The proposed optimization model is designed as a mixed‐integer nonlinear programming formulation, in which McCormick inequalities and other linearization techniques are utilized to tackle the model nonlinearities. The model allocates fuel cell electric trucks (FCETs), renewable energy sources, hydrogen refueling stations, and remote control switches such that the system resilience is enhanced while incorporating natural‐gas‐powered combined cooling, heating, and power system to minimize the operation and unserved demand costs. The model considers various factors such as the availability of renewable energy sources, the demand for heating, cooling, electricity, and hydrogen, the operation of remote control switches to help system reconfiguration, the travel behaviour of FCETs, and the power output of FCETs via vehicle‐to‐grid interface. The numerical results demonstrate that the proposed strategy can significantly improve the resilience of the seaport multi‐energy system and reduce the risk of service disruptions during contingency scenarios. [ABSTRACT FROM AUTHOR]

Published
2024
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17. Parameterized Wildfire Fragility Functions for Overhead Power Line Conductors

Author

Nazemi, Mostafa, Dehghanian, Payman, Darestani, Yousef, and Su, Jinshun

Abstract

Wildfires have been, recently more-frequently, posing significant threats to the safety and reliability of electric power delivery infrastructure, calling for the development of dedicated risk and vulnerability assessment frameworks. Fragility functions are essential tools for probabilistic risk assessment to estimate the failure likelihood of the system components as a function of hazard intensity. Widely exposed to the environment and atmospheric stressors, overhead power line conductors are among the most susceptible electric delivery infrastructure to approaching wildfires. Beyond the state-of-the-art fragility models, this article proposes novel parameterized wildfire fragility functions that can capture the impact of different environmental conditions and wildfire severity measures on overhead power line conductors. In doing so, wildfire behaviour is comprehensively characterized in order to model the temperature change in overhead conductors in the face of progressing wildfires. A novel parametric fragility model, which is a function of a set of physical and environmental features (e.g., conductor height, landscape slope, the dryness of fuel, fuel depth, wind speed, flame length), is then suggested to assess the failure likelihood of conductors given a permissible safety conductor temperature rise. A set of fire features (e.g., fire line intensity, fire rate of spread, and the angle of the fire approaching the conductors) is embedded in the proposed fragility model to capture the wildfire uncertainties. The numerical results reveal that, unlike the commonly-used fragility models, the proposed parameterized fragility function is able to accurately represent the impact of critical physical, environmental, and fire features in determining the vulnerability of power distribution lines when facing wildfire emergencies.

Published
2024
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18. Aggregated Operation Scheme for Distributed Photovoltaic and Energy Storage System Enabling Multi-Service Provision

Author

Wang, Yanling, Li, Yajie, Yang, Yanhong, Gao, Zhengnan, Dehghanian, Payman, Yang, Dechang, and Ding, Zhaohao

Abstract

The aggregated entity formed by the distributed photovoltaic (DPV) and energy storage system has the capability to offer multiple services in the electricity markets, reaping the advantages of both energy arbitrage and frequency regulation. This article focuses on developing a bidding strategy and operation plan for an aggregated entity from a profit pursuit perspective. We propose a multi-stage stochastic programming optimization model that divides the original problem into three stages, allowing for feasible and more realistic decision-making while maintaining the relationships among decisions. The proposed model includes a new multi-service portfolio that balances the profit of the two markets and accounts for uncertainties in market prices, DPV output, and regulation signals. To motivate collaboration among stakeholders, we also develop a profit allocation model rooted in the principles of Nash bargaining theory. This model serves as a compelling incentive for all parties involved, encouraging mutually beneficial cooperation. Finally, a numerical case study demonstrates the validity of the proposed models.

Published
2024
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19. Integrated Energy Management Scheme Considering Transportation Flexibility for Highway Service Zones

Author

Ding, Zhaohao, Zhang, Yu, Yang, Dechang, Dai, Liang, Wang, Dawei, Xu, Hongke, Zhao, Long, and Dehghanian, Payman

Abstract

The highway transportation system exhibits immense potential for adaptive functioning due to its distinctive operational attributes. This capability permits to harness more renewable energy, leading to a reduction in energy consumption costs. In this article, an integrative energy system optimization model is introduced from the standpoint of highway service zone operators. To simulate the behavior of electric vehicles on highways, an expanded network flow model is formulated considering driving, queueing, and charging actions. This model comprehensively integrates dimensions of time, space, and the state of charge of the vehicles. Consequently, the proposed model is proficient in representing the spatiotemporal and flexible operational traits inherent to electric vehicles. Through a series of numerical case studies executed on a real-world highway system, the effectiveness of the proposed model is demonstrated. These findings substantiate the potential utility and efficacy of our model in enhancing the operation optimization of energy systems within highway transportation systems.

Published
2024
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31. A local flexibility market framework for exploiting DERs' flexibility capabilities by a technical virtual power plant.

Author

Pourghaderi, Niloofar, Fotuhi‐Firuzabad, Mahmud, Moeini‐Aghtaie, Moein, Kabirifar, Milad, and Dehghanian, Payman

Subjects
POWER distribution networks, BILEVEL programming, MARKET equilibrium, MIXED integer linear programming, TEST systems, POWER resources
Abstract

This paper presents a new intra‐day intra‐hourly local flexibility market (LFM) framework to exploit distributed energy resources' (DERs) flexibility capabilities. A technical virtual power plant (TVPP) operates the LFM in which the DER aggregators participate. The TVPP offers the provided flexibility capabilities to wholesale flexibility market (WFM) as well as compensating the intra‐hourly variability in power distribution network. In the proposed framework, the TVPP clears the LFM by considering hierarchical transactions with the aggregator agents to find the market equilibrium in which the DERs' flexibility capabilities are optimally exploited while all participating agents make profit by trading flexibility capabilities in the LFM. A bilevel optimization model with multiple lower levels is considered to address different agents' preferences and transactions in the LFM. In the upper‐level problem, the TVPP aims at maximizing its profit while each lower‐level problem represents an aggregator agent's optimization problem. The proposed model is reformulated into a single‐level mixed integer linear programming problem and is implemented on the distribution network connected to Bus 5 of the Roy Billinton test system (RBTS) as well as a 119‐bus test system. The results demonstrate the effectiveness of the model to utilize DERs' flexibility and provide revenue opportunities for different agents. [ABSTRACT FROM AUTHOR]

Published
2023
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38. Optimal Operation of Integrated Water–Power Systems Under Contingencies.

Author

Alhazmi, Mohannad, Dehghanian, Payman, Nazemi, Mostafa, Wang, Fei, and Alfadda, Abdullah

Subjects
*WATER power, *INTERCONNECTED power systems, *SMART power grids, *LINEAR programming, *ELECTRIC lines, *RELIABILITY in engineering
Abstract

With the sharply growing complexity and rapid deployment of smart technologies in our modern society, risk-aware management and coordination in day-to-day operation of the interlinked critical infrastructures is urgently needed. In particular, the interconnected water and power systems (WaPS) are in need of joint and cooperative operation to maximize the economic benefits during normal operating conditions and resilience services during emergencies. While contingency analysis is used to assist the system operators in gaining knowledge of the system’s static security, such understanding is more challenging to achieve in the case of integrated WaPS. This article proposes a novel optimization model for under-emergency operation of the integrated WaPS, considering contingencies in both networks. In order to ensure the delivery of water demand, the proposed formulation considers the hydraulic constraints of the water networks, which is naturally a nonlinear model. The proposed nonlinear model is approximated using a piece-wise linearization approach to convert the optimization model into a mixed-integer linear programming formulation. The proposed analytics are applied to a modified IEEE 24-bus reliability test system that is jointly operated with two and three commercial-scale water networks. The proposed model is evaluated using various disaster severity levels (i.e., $N-k$ contingency scenarios) and verify the promising performance of the proposed integrated WaPS model when facing failures and threatening high impact low probability emergencies. [ABSTRACT FROM AUTHOR]

Published
2022
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