Decision Support System for Emergencies in Microgrids

Fotopoulou, Maria; Rakopoulos, Dimitrios C.; Petridis, Stefanos

doi:10.3390/s22239457

Cited by 11 publications

(11 citation statements)

References 31 publications

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“…Meanwhile, in order to better meet the needs of actual operation, considering a capacity configuration scheme for high renewable energy penetration scenarios in reference [25] and the power system challenged by emergency mentioned in reference [26], and considering the ability of the cloud-edge computing method to adapt to uncertainty and emergency will be the next research direction.…”

Section: Discussionmentioning

confidence: 99%

A Cloud-Edge Computing Method for Integrated Electricity-Gas System Dispatch

Li,

Wang

2023

Processes

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An integrated electric–gas system (IEGS) is the manifestation and development direction of a modern smart power system. This paper employs the cloud-edge computing method to research IEGS’s optimal dispatch to satisfy data protection requirements between power systems and natural gas systems and reduce data transmission pressure. Based on cloud-edge computing architecture, this paper constructs a cloud-edge computing method based on the Multi-agent Deep Deterministic Policy Gradient (MADDPG) algorithm to solve optimal dispatch problems. Then, this paper proposes an IEGS dispatch strategy based on cloud-edge computing, which conducts distributed computing independently at the edge of power and natural gas, and the cloud implements global dispatch based on boundary information and edge learning parameters. This method does not require the exchange of all information between the power system and natural gas system, effectively protecting data privacy. This paper takes the improved IEGS of the IEEE 9 node and Gas 8 node as an example to analyze. The equipment output of this dispatch method is within a reasonable range, and the cost is reduced by 0.21% to 1.03% compared with other methods, which verifies the effectiveness of the cloud-edge computing method in solving dispatch problems.

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Section: Discussionmentioning

confidence: 99%

A Cloud-Edge Computing Method for Integrated Electricity-Gas System Dispatch

Li,

Wang

2023

Processes

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“…While performing the techno-economic analysis, the total of two types of costs, i.e., power outage cost and investment cost is computed to select the optimum total size of MERs. The power outage cost C outage is calculated for each total MER size based on (15).…”

Section: Determination Of Optimum Total Size Of Mersmentioning

confidence: 99%

“…The scheduling constraints for MERs are meticulously derived, taking into account their intricate interactions with the distribution system. In [15], an optimal decision support system is presented to assist microgrid operators in managing various emergencies, including extreme weather and technical issues, by maximizing the autonomy of the microgrid and prioritizing renewable energy sources. In [16], an emergency power supply recovery strategy for distribution networks with microgrid support is investigated to address uncertainties caused by renewable energy sources, demonstrating its effectiveness in improving energy safety and stabilty in such networks.…”

Section: Introductionmentioning

confidence: 99%

Optimal Sizing of Movable Energy Resources for Enhanced Resilience in Distribution Systems: A Techno-Economic Analysis

Gautam,

Ben-Idris

2023

Electronics

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This article introduces a techno-economic analysis aimed at identifying the optimal total size of movable energy resources (MERs) to enhance the resilience of electric power supply. The core focus of this approach is to determine the total size of MERs required within the distribution network to expedite restoration after extreme events. Leveraging distribution line fragility curves, the proposed methodology generates numerous line outage scenarios, with scenario reduction techniques employed to minimize computational burden. For each reduced multiple line outage scenario, a systematic reconfiguration of the distribution network, represented as a graph, is executed using tie-switches within the system. To evaluate each locational combination of MERs for a specific number of these resources, the expected load curtailment (ELC) is calculated by summing the load curtailment within microgrids formed due to multiple line outages. This process is repeated for all possible locational combinations of MERs to determine minimal ELC for each MER total size. For every MER total size, the minimal ELCs are determined. Finally, a techno-economic analysis is performed using power outage cost and investment cost of MERs to pinpoint an optimal total size of MERs for the distribution system. To demonstrate the effectiveness of the proposed approach, case studies are conducted on the 33-node and the modified IEEE 123-node distribution test systems.

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“…The proposed idea successfully optimized operational costs by 12% over a time horizon of 8 days. In [52], authors discuss the decision support system in microgrids for emergencies, such as blackouts, switching to islanded mode, etc. The objective of developing this support system optimizer is to maximize the autonomy of microgrids for supporting renewable energy production.…”

Section: Related Researchmentioning

confidence: 99%

An Enhanced Multi-Objective Optimizer for Stochastic Generation Optimization in Islanded Renewable Energy Microgrids

et al. 2023

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A microgrid is an autonomous electrical system that consists of renewable energy and efficiently achieves power balance in a network. The complexity in the distribution network arises due to the intermittent nature of renewable generation units and varying power. One of the important objectives of a microgrid is to perform energy management based on situational awareness and solve an optimization problem. This paper proposes an enhanced multi-objective multi-verse optimizer algorithm (MOMVO) for stochastic generation power optimization in a renewable energy-based islanded microgrid framework. The proposed algorithm is utilized for optimum power scheduling among various available generation sources to minimize the microgrid’s generation costs and power losses. The performance of MOMVO is assessed on a 6-unit and 10-unit test system. Simulation results show that the proposed algorithm outperforms other metaheuristic algorithms for multi-objective optimization.

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Decision Support System for Emergencies in Microgrids

Cited by 11 publications

References 31 publications

A Cloud-Edge Computing Method for Integrated Electricity-Gas System Dispatch

A Cloud-Edge Computing Method for Integrated Electricity-Gas System Dispatch

Optimal Sizing of Movable Energy Resources for Enhanced Resilience in Distribution Systems: A Techno-Economic Analysis

An Enhanced Multi-Objective Optimizer for Stochastic Generation Optimization in Islanded Renewable Energy Microgrids

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