Operational reliability and non-deterministic resilience estimation of active distribution network incorporating effect of real-time dynamic hosting capacity

Active distribution networks are increasingly recognized essential for achieving sustainable development goals. Traditionally, hosting capacity was considered as a static measure for planning distributed energy resources integration. This work introduces the concept of dynamic hosting capacity, which recurrently re-evaluates hosting capacity in response to erratic modern grid conditions. The introduction of dynamic hosting capacity facilitated testing variations of power injection from minimum to 100%, sustaining power system governing parameter limits. This embarked the need of operational reliability assessment and enhancing situational awareness for optimum power injection and balance. To achieve operational reliability analysis based on dynamic hosting capacity, hybrid probability distribution function-based Monte Carlo simulation is proposed. This resulted in 85-90%. improvisation of solar photovoltaic generation and load alignment, as this methodology provides comprehensive and accurate assessment of system performance under diverse uncertainties. The framework's validation includes projection of time-varying operational reliability indices, over time independent reliability indices i.e., dynamic loss of load probability, dynamic loss of load expectation, dynamic loss of load duration, dynamic loss of load frequency, dynamic grid margin, and dynamic grid dependency. This resulted in 30% improvement in assessment of grid margin, facilitating reliable uncertainty handling competence. Additionally, expectation maximization algorithm is proposed to evaluate non-deterministic resilience due to ambiguities associated with solar photovoltaic distributed energy resources. The non-deterministic resilience assessment testified 80% bounce-back rate, demonstrating better adaptability and robustness. The entire analysis is conducted in MATLAB, validated using Typhoon Hardware-in-Loop real-time platform, and compared with existing literatures to demonstrate its effectiveness. • Significance of DHC over static HC for operational reliability estimation of ADN. • Operational reliability assessment considering DHC using hybrid PDF-MCS approach. • Operational reliability corroboration of ADN using time-varying reliability indices. • Estimation of NDR using EM algorithm, to enhance SA due to PVDER uncertainties. • Typhoon HIL validation certifying injections without governing parameter violation.

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Publication Details

Journal
Sustainable Energy Grids and Networks
Published
2024-10-11
DOI
https://doi.org/10.1016/j.segan.2024.101541
Citations
3
Primary Topic
Optimal Power Flow Distribution
Type
article
Field-Weighted Citation Impact
0.63
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article

Operational reliability and non-deterministic resilience estimation of active distribution network incorporating effect of real-time dynamic hosting capacity

Dusmanta Kumar Mohanta, Soham Dutta, Sonal, Sourav Kumar Sahu et al.
3 citations
Sustainable Energy Grids and Networks
Optimal Power Flow Distribution
0.63
article

Operational reliability and non-deterministic resilience estimation of active distribution network incorporating effect of real-time dynamic hosting capacity

Dusmanta Kumar Mohanta, Soham Dutta, Sonal, Sourav Kumar Sahu, Debomita Ghosh
article en
3 citations

Abstract

Active distribution networks are increasingly recognized essential for achieving sustainable development goals. Traditionally, hosting capacity was considered as a static measure for planning distributed energy resources integration. This work introduces the concept of dynamic hosting capacity, which recurrently re-evaluates hosting capacity in response to erratic modern grid conditions. The introduction of dynamic hosting capacity facilitated testing variations of power injection from minimum to 100%, sustaining power system governing parameter limits. This embarked the need of operational reliability assessment and enhancing situational awareness for optimum power injection and balance. To achieve operational reliability analysis based on dynamic hosting capacity, hybrid probability distribution function-based Monte Carlo simulation is proposed. This resulted in 85-90%. improvisation of solar photovoltaic generation and load alignment, as this methodology provides comprehensive and accurate assessment of system performance under diverse uncertainties. The framework's validation includes projection of time-varying operational reliability indices, over time independent reliability indices i.e., dynamic loss of load probability, dynamic loss of load expectation, dynamic loss of load duration, dynamic loss of load frequency, dynamic grid margin, and dynamic grid dependency. This resulted in 30% improvement in assessment of grid margin, facilitating reliable uncertainty handling competence. Additionally, expectation maximization algorithm is proposed to evaluate non-deterministic resilience due to ambiguities associated with solar photovoltaic distributed energy resources. The non-deterministic resilience assessment testified 80% bounce-back rate, demonstrating better adaptability and robustness. The entire analysis is conducted in MATLAB, validated using Typhoon Hardware-in-Loop real-time platform, and compared with existing literatures to demonstrate its effectiveness. • Significance of DHC over static HC for operational reliability estimation of ADN. • Operational reliability assessment considering DHC using hybrid PDF-MCS approach. • Operational reliability corroboration of ADN using time-varying reliability indices. • Estimation of NDR using EM algorithm, to enhance SA due to PVDER uncertainties. • Typhoon HIL validation certifying injections without governing parameter violation.

Sustainable Energy Grids and NetworksVol. 40
Birla Institute of Technology, Mesra (IN), Magna International (Germany) (DE), Manipal Academy of Higher Education (IN)
Openalex Percentile: Top 31%
Optimal Power Flow Distribution
0.63
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