Risk‐based many‐objective configuration of power system fault current limiters utilising NSGA‐III

Guo, Chao; Ye, Chengjin; Ding, Yi; Liu, Shengyuan; Wang, Peng

doi:10.1049/iet-gtd.2020.0482

Cited by 11 publications

(10 citation statements)

References 32 publications

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“…Based on the four types of PM models that include single-and bi-objective models with and without the constraint, PM strategies in the green industry were extensively investigated. For the bi-objective PM optimization, NSGA-III [24][25][26][27][28] was employed, which was previously adopted to solve various multi-objective optimization problems, with modifications made for specific problems [29][30][31][32][33]. The algorithm was further developed to optimize the competitive PM alternatives in the Pareto front in the form of maintenance activities in the degradation states of components.…”

Section: Related Workmentioning

confidence: 99%

Condition-Based Multi-State-System Maintenance Models for Smart Grid System with Stochastic Power Supply and Demand

Wang

Huang²,

You

2022

Sustainability

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This study established power-related efficiency measures from the perspective of reliability, namely, power system availability, expected power deficiency, accumulated power deficiency, instantaneous power capacity, and accumulated power capacity for a hybrid power system (HPS) in a generic smart grid. Methodologically, a power supply–demand stochastic model that simultaneously considers the inherently stochastic nature of power supply and demand was developed to quantify their interrelationship and characterize the dynamic behavior of an HPS in a continuous-time Markov chain. Preventive maintenance (PM) models were also constructed to determine the optimal PM strategy in alignment with specific scenarios that reflect the power performance requirements and resource limitations. A sensitivity analysis was conducted using the design of experiments (DOE) scheme that simulated climate change and revealed that extreme climate worsens power-related efficiency measures. This analysis provides further insight into the extent to which extreme climate conditions diminish the engineers and designers of smart grid systems’ power-related efficiency measures. The proposed approach will potentially contribute to sustainability and maintainability in the clean energy industry.

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Section: Related Workmentioning

confidence: 99%

Condition-Based Multi-State-System Maintenance Models for Smart Grid System with Stochastic Power Supply and Demand

Wang

Huang²,

You

2022

Sustainability

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“…Decentralization of the energy production units has been proven to be a workable solution to tackle many obstacles, including economic, environmental and reliability issues [1]. Distributed energy resources (DERs) are far cheaper than conventional large-scale power plants, which attributes to the proliferation of private investors, leading to the emergence of a free market environment, wherein so-called invisible hands of the economy foster efficiency and increase reliability [2]. In outdated energy provision systems, distribution systems (DS) were inactive price-taker energy consumers.…”

Section: Motivationmentioning

confidence: 99%

A robust decision framework for strategic behaviour of integrated energy service provider with embedded natural gas and power systems in day‐ahead wholesale market

Nasiri

Zeynali

Ravadanegh

et al. 2021

IET Generation Trans & Dist

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The rampant growth in penetration of gas-fired distributed units (GFDUs) is recasting the role of the integrated energy service provider (IESP) as a price-maker player. Nevertheless, it is threatening the well-being and reliability of the natural gas networks (NGNs). In this regard, this paper investigates the strategic participation of integrated 20-node NGN and an 33-bus active distribution system (ADS) in the day-ahead wholesale market (WM), which consists of a six-bus transmission network (TN), through a bi-level optimization framework. The upper-level objective is to minimize the operational costs of the IESP as well as the cost of energy that is purchased/sold in day-ahead WM. The lower-level problem models the optimal response of the wholesale market operator (WMO) that has the objective of maximizing social well-fare by clearing the day-ahead wholesale market. To alleviate the NGN's pipeline congestion, the linepack capability of the pipelines is deployed, while demand response program (DRP) and interruptible loads (IL) are integrated into the ADS side. As a computationally efficient method, robust optimization (RO) is utilized to handle the uncertainties. The results emphasize the necessity of integrating NGN into this problem. Eventually, different case studies illustrate the impact of line pack and DRP in reducing market-clearing price.

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“…The nondominated sorting genetic algorithm III (NSGA-III) [21][22][23] has been successfully adopted to solve various multiobjective optimisation problems, and variants have been developed for specific problems [24][25][26][27][28]. Bhesdadiya et al [21] applied NSGA-III to lower the emission value and fuel cost of fossil fuel power plants while providing a sustainable and reliable power supply.…”

Section: Main Transmission Gearbox (Mtg)mentioning

confidence: 99%

“…Bhesdadiya et al [21] applied NSGA-III to lower the emission value and fuel cost of fossil fuel power plants while providing a sustainable and reliable power supply. Guo et al [22] proposed a risk-based multiobjective framework for a fault current limiter (FCL) that employs a data-driven proportional hazard model to consider equipment ageing, weather statistics, and surrounding conditions for evaluating the nodal shortcircuit fault probability. NSGA-III was used to configure the FCL in a more economical manner.…”

Section: Main Transmission Gearbox (Mtg)mentioning

confidence: 99%

Multiobjective Multistate System Preventive Maintenance Model with Human Reliability

Huang

Wang

Chen

2021

International Journal of Aerospace Engineering

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Modern equipment is designed to operate under deteriorating performance conditions resulting from internal ageing and/or external environmental impacts influencing downstream maintenance. This study focuses on the development of a multistate system (MSS) that considers a human reliability factor associated with maintenance personnel—a condition-based multiobjective MSS preventive maintenance model (MSSPMM). The study assumes that no more than one maintenance activity is performed to achieve the most appropriate preventive maintenance (PM) strategy and easy implementation and to reduce maintenance error due to human reliability. The MSS performance based on mean system unavailability and total maintenance cost is evaluated using a stochastic model approach, and then, the MSSPMM is used for optimisation. A customised version of the nondominated sorting genetic algorithm III is employed to ensure efficient solution of the PM model with human reliability—which is considered a constrained multiobjective combinatorial optimisation problem. The optimised solutions are determined from the nondominated Pareto frontier comprising the diversified PM alternatives. A helicopter power transmission system is used as an example to illustrate the efficacy and applicability of the proposed approach through sensitivity analyses with relevant parameters.

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Risk‐based many‐objective configuration of power system fault current limiters utilising NSGA‐III

Cited by 11 publications

References 32 publications

Condition-Based Multi-State-System Maintenance Models for Smart Grid System with Stochastic Power Supply and Demand

Condition-Based Multi-State-System Maintenance Models for Smart Grid System with Stochastic Power Supply and Demand

A robust decision framework for strategic behaviour of integrated energy service provider with embedded natural gas and power systems in day‐ahead wholesale market

Multiobjective Multistate System Preventive Maintenance Model with Human Reliability

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