Uncertainty quantification in low voltage distribution grids: Comparing Monte Carlo and general polynomial chaos approaches

Koirala, Arpan; Acker, Tom Van; D’hulst, Reinhilde; Hertem, Dirk Van

doi:10.1016/j.segan.2022.100763

Cited by 14 publications

(8 citation statements)

References 50 publications

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“…One of the limitations of gPC-CC-OPF is that the moment based reformulation in (20), wherein we assumed the λ i (ε v ) to be based on the Gaussian distribution where its value is 1.65 for v = 0.05 [18], [19]. But the input we assume is not Gaussian, and the non-Gaussian uncertainties propagated…”

Section: Tuning Of Moment-based Chance-constraintsmentioning

confidence: 99%

“…Instead of running the OPF for HC calculation for all time period t ∈ T , the search space is reduced by only investigating the time-point τ where the probability that the maximum voltage in the feeder is higher than U max is highest, i.e., p ov t = P(max(U i,t ) > U max ) is the highest. This instance is found a priori by using PPF from [20] for all timestamps, assuming high PV penetration. The remainder of the CC-OPF formulation is described for single-period optimization for τ time where p ov τ = max(p ov t ).…”

mentioning

confidence: 99%

See 1 more Smart Citation

Chance-Constrained Optimization Based PV Hosting Capacity Calculation Using General Polynomial Chaos

Koirala

Acker

Hashmi

et al. 2024

IEEE Trans. Power Syst.

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Section: Tuning Of Moment-based Chance-constraintsmentioning

confidence: 99%

mentioning

confidence: 99%

Chance-Constrained Optimization Based PV Hosting Capacity Calculation Using General Polynomial Chaos

Koirala

Acker

Hashmi

et al. 2024

IEEE Trans. Power Syst.

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“…The authors in Ref. [35] studied the congestion in lines caused due to the uncertainty in PV power injection in low voltage distribution system using Monte Carlo approach.…”

Section: Introductionmentioning

confidence: 99%

“…Further, the risks associated with DSO due to uncertain renewable generation and load demand are addressed in Refs. [35–37]. The authors in Ref.…”

Section: Introductionmentioning

confidence: 99%

Risk‐return optimised energy asset allocation in transmission‐distribution system using tangency portfolio and Black–Litterman model

Jisma

Mohan

Thomas

2023

IET Energy Syst Integration

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The application of Markowitz and tangency portfolio and Black–Litterman models is extended by the authors to energy portfolio selection in transmission‐distribution environments with high penetration of renewable energy. As Transmission System Operator (TSO) and Distribution System Operator (DSO) contextually take mutualistic or conflicting positions in their portfolio selection process, their risk‐return interactions and behaviours depend on their subjective views on generation and operation. Here, the financial portfolio allocation tool Black–Litterman Model is adapted to incorporate subjective views of the operators to arrive at more intuitive portfolios. The best portfolios are searched within the acceptable risk‐return search space of each operator defined by their Markowitz efficient frontiers (EF), for Pareto‐optimising their profits. The tangency portfolio approach, which is generally used to determine the portfolio of risky and risk‐free assets in finance, is used here to determine the portfolio of renewable (energy‐risky) and fuel‐based sources (energy‐risk‐free). The proposed methodology is adopted in an HV–MV interconnected test system operated by one TSO and two DSOs, having wind, solar, coal, gas and nuclear generation technologies. It is observed that completely customisable portfolios can be constructed for TSO and DSO based on their inherent financial and energy risk‐return behaviours and posterior views.

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“…After this implementation of gPC to power flow calculations, [18] filled the research gap in applying gPC to probabilistic continuation power flow problem in the presence of dependent random variables. Following these promising applications, in [19], the non-intrusive gPC based power flow calculation method is compared with Monte Carlo (MC) simulation based methods for an existing low voltage distribution system in Belgium, showing the superiority of gPC on MC simulations. An iterative algorithm is developed in [20] to help with the adoption of gPC in SOPF problems with large systems while maintaining high accuracy.…”

mentioning

confidence: 99%

Controllability and Flexibility of HVDC Converters in Hybrid AC/DC Grids: A Stochastic Approach

Yurtseven¹,

Koirala²,

Ergun³

et al. 2023

Preprint

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<p>HVDC networks play an ever-more-significant role in today's and future power systems due to the rapid adoption of intermittent energy sources. In order to maximize the utilization of transmission grids for power systems with high share of renewable energy sources (RES) there is a need for an adequate quantification tool that is capable of accurately representing the uncertain operational characteristics of RES along with reflecting the control capabilities of HVDC converter stations. In that manner, the development of such a tool as a non-sampling one-shot mathematical structure is invaluable from the operational decision making point-of-view. This paper presents a mathematical chance-constrained framework for solving stochastic optimal power flow problem for hybrid AC/DC grids, which includes HVDC controllability and the uncertainties brought about by load and renewable energy generation, by using an intrusive general polynomial chaos approach. Three case studies are conducted on 5-bus and 67-bus hybrid AC/DC test systems to highlight the efficacy of the proposed method with a focus on the added flexibility of HVDC converters and the effects of various chance-constraint levels as well as to validate the method against Monte-Carlo simulations.</p>

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Uncertainty quantification in low voltage distribution grids: Comparing Monte Carlo and general polynomial chaos approaches

Cited by 14 publications

References 50 publications

Chance-Constrained Optimization Based PV Hosting Capacity Calculation Using General Polynomial Chaos

Chance-Constrained Optimization Based PV Hosting Capacity Calculation Using General Polynomial Chaos

Risk‐return optimised energy asset allocation in transmission‐distribution system using tangency portfolio and Black–Litterman model

Controllability and Flexibility of HVDC Converters in Hybrid AC/DC Grids: A Stochastic Approach

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