Robust Transmission Network Expansion Planning Method With Taguchi's Orthogonal Array Testing

Yu, Hoi-Lai; Chung, C.Y.; Wong, K.P.

doi:10.1109/tpwrs.2010.2082576

Cited by 120 publications

(93 citation statements)

References 17 publications

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“…In Type I, worst-case uncertainty scenarios are incorporated into the problem. Taguchi's orthogonal array testing (TOAT) [12] is used for that purpose. In type II [13], for each uncertain parameter an allowable range is specified, and then the problem is solved while the uncertainty is bound in the specified range.…”

Section: Indicesmentioning

confidence: 99%

Reliability‐based model for generation and transmission expansion planning

Ahmadi

Mavalizadeh

Zobaa

et al. 2017

IET Generation, Transmission & Distribution

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This paper presents a mixed integer linear multi-objective model based on information gap decision theory (IGDT), which is used to solve coordinated multiyear generation and transmission expansion planning (G&TEP) problems. The model maximizes the robustness of each uncertain parameter while a maximum allowable budget range is set. Fuel transportation price is considered. The results provide a numerical tool for system planner to help him adjust the appropriate level of robustness for each uncertain parameter of the problem. Extra limits on security, gaseous emission, and fuel availability are considered. A multi-objective method called the ε-constraint method is used here to maximize the robust region of load and investment costs simultaneously. The model is implemented on a six-bus Garver test system and 24 bus IEEE test system. The numerical results show the good performance of the model.

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Section: Indicesmentioning

confidence: 99%

Reliability‐based model for generation and transmission expansion planning

Ahmadi

Mavalizadeh

Zobaa

et al. 2017

IET Generation, Transmission & Distribution

View full text Add to dashboard Cite

show abstract

“…By incorporating the typical scenario set, the classical multi-scenario TNEP model is formulated by [6,8]: The objective of Equation (11) is to find the minimum cost planning scheme that satisfies the load demand and renewable power consumption in all typical scenarios. It can be observed that a sufficiently large penalty factor β can effectively drive both the load shedding and renewable generation curtailment to zero.…”

Section: Classical Multi-scenario Tnep Modelmentioning

confidence: 99%

“…[7] applied the Monte Carlo simulation (MCS) to simulate the uncertainties of outages and load forecasting in the coordinated generation-transmission expansion planning. In addition, the robust TNEP design based on extreme scenarios was adopted by [8,9] to improve the robustness of planning schemes. Nevertheless, the above multi-scenario methods still have limitations, as they tend to generate a large number of scenarios to achieve accurate simulation of uncertainties, which may cause a heavy computational burden.…”

Section: Introductionmentioning

confidence: 99%

Flexible Transmission Network Expansion Planning Considering Uncertain Renewable Generation and Load Demand Based on Hybrid Clustering Analysis

Wang

2015

Applied Sciences

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This paper presents a flexible transmission network expansion planning (TNEP) approach considering uncertainty. A novel hybrid clustering technique, which integrates the graph partitioning method and rough fuzzy clustering, is proposed to cope with uncertain renewable generation and load demand. The proposed clustering method is capable of recognizing the actual cluster distribution of complex datasets and providing high-quality clustering results. By clustering the hourly data for renewable generation and load demand, a multi-scenario model is proposed to consider the corresponding uncertainties in TNEP. Furthermore, due to the peak distribution characteristics of renewable generation and heavy investment in transmission, the traditional TNEP, which caters to rated renewable power output, is usually uneconomic. To improve the economic efficiency, the multi-objective optimization is incorporated into the multi-scenario TNEP model, while the curtailment of renewable generation is considered as one of the optimization objectives. The solution framework applies a modified NSGA-II algorithm to obtain a set of Pareto optimal planning schemes with different levels of investment costs and renewable generation curtailments. Numerical results on the IEEE RTS-24 system demonstrated the robustness and effectiveness of the proposed approach.

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“…If the system is large, the computational burden may become too heavy to be tolerated. Hence, we employ the Taguchi's orthogonal array testing (TOAT) [19] with the probability re-assignment that developed in our study for reducing information redundancy, as given below:…”

Section: Scenario Synthesis and Redundancy Reductionmentioning

confidence: 99%

“…Step 3: Construct the orthogonal arrays (OAs) [19] in a size of m rows and n columns, where m is the number of refined scenarios generated by the TOAT and n is the number of uncertain variables input from Step 2. m is much smaller than the number of initial scenarios, and they are regarded as the representative scenarios while preserving good statistical information.…”

Section: Scenario Synthesis and Redundancy Reductionmentioning

confidence: 99%

Active Distribution System Planning for Low-carbon Objective using Cuckoo Search Algorithm

Zeng¹,

Zhang²,

Zhang³

et al. 2014

Journal of Electrical Engineering and Technology

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-In this study, a method for the low-carbon active distribution system (ADS) planning is proposed. It takes into account the impacts of both network capacity and demand correlation to the renewable energy accommodation, and incorporates demand response (DR) as an available resource in the ADS planning. The problem is formulated as a mixed integer nonlinear programming model, whereby the optimal allocation of renewable energy sources and the design of DR contract (i.e. payment incentives and default penalties) are determined simultaneously, in order to achieve the minimization of total cost and CO 2 emissions subjected to the system constraints. The uncertainties that involved are also considered by using the scenario synthesis method with the improved Taguchi's orthogonal array testing for reducing information redundancy. A novel cuckoo search (CS) is applied for the planning optimization. The case study results confirm the effectiveness and superiority of the proposed method.

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Robust Transmission Network Expansion Planning Method With Taguchi's Orthogonal Array Testing

Cited by 120 publications

References 17 publications

Reliability‐based model for generation and transmission expansion planning

Reliability‐based model for generation and transmission expansion planning

Flexible Transmission Network Expansion Planning Considering Uncertain Renewable Generation and Load Demand Based on Hybrid Clustering Analysis

Active Distribution System Planning for Low-carbon Objective using Cuckoo Search Algorithm

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