A gradient descent direction based-cumulants method for probabilistic energy flow analysis of individual-based integrated energy systems

Zheng, Jiayu; Xiao, Wenting; Wu, Chuanlong; Li, Zhigang; Wang, L.X.

doi:10.1016/j.energy.2022.126290

Cited by 24 publications

(6 citation statements)

References 31 publications

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“…The Monte Carlo methodology [43] was employed to assess the effectiveness of the algorithm in comparison to the proposed algorithm. By utilizing the Monte Carlo method, a random sample of 100 wind speed data points from the fan was obtained to determine the optimal value of the objective function.…”

Section: Algorithm Comparisonsmentioning

confidence: 99%

Set-Based Group Search Optimizer for Stochastic Many-Objective Optimal Power Flow

Zheng,

Tao,

et al. 2023

Applied Sciences

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The conventional optimal power flow (OPF) is confronted with challenges in tackling more than three objectives and the stochastic characteristics due to the uncertainty and intermittence of the RESs. However, there are few methods available that simultaneously address high-dimensional objective optimization and uncertainty handling. This paper proposes a set-based group search optimizer (SetGSO) to tackle the stochastic many-objective optimal power flow (MaOPF) of power systems penetrated with renewable energy sources. The proposed SetGSO depicts the original stochastic variables by set-based individuals under the evolutionary strategy of the basic GSO, without using repeated sampling or probabilistic information. Consequently, two metrics, hyper-volume and average imprecision, are introduced to transform the stochastic MaOPF into a deterministic bi-objective OPF, guaranteeing a much superior Pareto-optimal front. Finally, our method was evaluated on three modified bus systems containing renewable energy sources, and compared with the basic GSO using Monte Carlo sampling (GSO-MC) and a set-based genetic algorithm (SetGA) in solving the stochastic MaOPF. The numerical results demonstrate a saving of 90% of the computation time in the proposed SetGSO method compared to sampling-based approaches and it achieves improvements in both the hyper-volume and average imprecision indicators, with a maximum enhancement of approximately 30% and 7% compared to SetGA.

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Section: Algorithm Comparisonsmentioning

confidence: 99%

Set-Based Group Search Optimizer for Stochastic Many-Objective Optimal Power Flow

Zheng,

Tao,

et al. 2023

Applied Sciences

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“…On the other hand, the type of load demands tends to be diversifed, which is no longer just a simple power load [10]. It may be coupled with gas or heating/cooling subsystems to form an integrated energy system with multienergy complementarity [11,12]. In the new type of power system, the load-side components mainly include electric vehicles, electric boilers, and heat pumps.…”

Section: Introductionmentioning

confidence: 99%

“…In addition, it is also proved that the Cornish-Fisher series expansion works better than the Gram-Charlier for non-Gaussian for random input variable. Te authors in reference [12] presented a gradient descent direction iterative method based on cumulants to analyse the PPF of a heterogeneous integrated energy systems. Te authors in reference [21] proved that the point estimate method (PE) with 2m + 1 scheme has precise results, smaller computational burden, and time, compared to MCS and PE with 2m scheme.…”

Section: Introductionmentioning

confidence: 99%

Random Fuzzy Power Flow Analysis for Power System considering the Uncertainties of Renewable Energy and Load Demands

Zheng

Xiao

2023

International Transactions on Electrical Energy Systems

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Due to the strong uncertainties of renewable energy and load demands, the new type of power systems is facing severe challenges in terms of generation control and load dispatch. Considering the uncertainties of the penetrated renewable energy and diversified load demands, this paper proposes a random fuzzy power flow analysis method (RFPF) to exactly depict the impact on the various flows of power systems. In the RFPF, the random fuzzy models of wind turbine generators, photovoltaic generators, and load demands are established utilizing the stochastic probability functions and fuzzy interval to reveal the uncertainties with high precision. Afterwards, the random fuzzy mean value is developed as an index of accuracy, and the fuzzy number of the output variables is extracted under the 95% confidence level. Furthermore, the proposed RFPF model is executed by applying a three-point estimate method (3PE) to figure out the corresponding power flow of the power system, costing less computation burden compared with the Monte Carlo simulation. Simulation studies conducted on the IEEE-33 system verifies the accuracy of the RFPF and the efficiency of the 3PE.

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“…T HE energy crisis and environment deterioration problems urge people to accelerate energy transformation processes [1]. The attention towards multienergy integrated microgrid is increasing at a fast pace, because of its benefits in terms of low carbon footprint, renewable energy accommodation, power quality, reliability and resiliency, and economics [2], [3]. For example, in [4], an optimal deployment concerning capacity sizes for combined electricity and heat systems within microgrids was presented to optimize both the carbon dioxide emission and net cost.…”

Section: Introductionmentioning

confidence: 99%

Flexibility Exploitation With Nonlinear Integrated Demand Response for Multi-Energy System Against Load Estimation Mistake

et al. 2023

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Integrated demand response contributes to flexibility improvement in multi-energy system. Yet, the challenge posed by the load estimation mistake needs to be addressed to explore the available flexibility. In this paper, we present a price-based nonlinear integrated demand response for multi-energy microgrid against estimation mistakes of both electricity and gas loads. Among them, we develop a period partition method to describe load characteristics and reach a reasonable time-of-use pricing. Besides, a credibility theory-based risk measurement is presented to evaluate the uncertain wind power. Finally, case studies demonstrate the feasibility and effectiveness of the proposed method in flattening load curve, reducing operation cost and promoting the accommodation of wind power.INDEX TERMS Credibility, flexibility, integrated demand response, load mistake, multi-energy system.

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A gradient descent direction based-cumulants method for probabilistic energy flow analysis of individual-based integrated energy systems

Cited by 24 publications

References 31 publications

Set-Based Group Search Optimizer for Stochastic Many-Objective Optimal Power Flow

Set-Based Group Search Optimizer for Stochastic Many-Objective Optimal Power Flow

Random Fuzzy Power Flow Analysis for Power System considering the Uncertainties of Renewable Energy and Load Demands

Flexibility Exploitation With Nonlinear Integrated Demand Response for Multi-Energy System Against Load Estimation Mistake

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