A hierarchical multi‐area capacity planning model considering configuration ratios of renewable energy and energy storage systems with multi‐area coordination

Li, Qingtao; Wang, Jianxue; Chen, Jie; Ding, Tao; Gu, Chenjia

doi:10.1049/gtd2.12923

Cited by 6 publications

(1 citation statement)

References 46 publications

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“…This transformation leads to a significant increase in the pressure on the system peak and frequency regulation [14], fundamentally altering the criteria for the selection of typical operational scenarios. These changes include reducing the net load peak values, intensifying the flexibility requirements, and augmenting disparities in the net load peak-to-valley differentials, among other factors [15]. In summary, the scenarios that feature high renewable energy penetration significantly modify the operational characteristics of conventional power systems.…”

Section: Introductionmentioning

confidence: 99%

A closed‐loop representative day selection framework for generation and transmission expansion planning with demand response

Liu,

Li,

Liu

et al. 2024

Energy Conversion and Econom

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In power systems with a high proportion of renewable energy resources (RES), the inherent stochasticity and volatility of RES necessitate careful consideration in power system planning. Scenario analysis is commonly employed to address the stochastic nature in power system planning. Existing studies generally adopt an open‐loop structure, where representative days are selected first and planning decisions are subsequently made. However, this method may not accurately represent the operating status of a system owing to changes in the power generation structure during the planning process. To address this limitation, this paper introduces a closed‐loop framework for representative day selection within the context of generation and transmission expansion planning (G&TEP), incorporating demand response (DR). The framework comprises three layers: representative day selection, planning decisions, and long‐term operational simulation. Initially, an approach for selecting representative days is proposed by combining the clustering and optimization‐based methods. Subsequently, a G&TEP model that incorporates DR is presented in the second layer. Lastly, the framework encompasses a three‐layer closed‐loop structure, enabling dynamic adjustments and enhancements to the representative day selection process to ensure optimality. Case studies on the reliability and operational test system of a power grid with large‐scale renewable integration (XJTU‐ROTS) demonstrate the effectiveness of our proposed framework.

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Section: Introductionmentioning

confidence: 99%

A closed‐loop representative day selection framework for generation and transmission expansion planning with demand response

Liu,

Li,

Liu

et al. 2024

Energy Conversion and Econom

Self Cite

View full text Add to dashboard Cite

show abstract

A network search space reduction method for robust coordinated energy storage and transmission expansion planning

Yang,

Wang,

Zhang

et al. 2024

IET Generation Trans & Dist

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The development of renewable energy will increase the demand for flexible resources in power systems due to the strong uncertainties. To allocate resources and cope with these uncertainties, it is beneficial to apply robust coordinated energy storage and transmission expansion planning (ES&TEP). The large candidate line set can significantly increase the computational complexity of robust optimization models. However, there is currently no suitable network search space reduction (NSSR) method to address this problem. This paper designs a NSSR method based on redundancy constraint identification that only requires information on component power ranges rather than fixed power curves, which can be well adapted to robust optimization. Additionally, this method requires only basic numerical calculations and ensures convergence within a finite number of iterations. The classical stochastic robust ES&TEP model and the column and constraint generation (C&CG) algorithm are used to validate the effectiveness of the NSSR method. In the case studies, the numerical results confirm the rationality and effectiveness of the approach proposed in this paper. By selecting appropriate parameters, the candidate line set can be reduced by over 70% and the computational efficiency can be improved by an order of magnitude.

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The Multiobjective Control Based on Tolerance Optimization in a Multienergy System

Ma,

Li,

Jiang

et al. 2024

International Transactions on Electrical Energy Systems

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To address the issue of multiobjective control in multienergy systems with diverse operational objectives, a two-stage optimization framework based on expected point tolerance has been proposed in this paper. In the first stage, a single objective function is used for optimization control to obtain the expected point of the multiobjective optimization problem. Then, in the second stage, by defining the allowable deviation between each optimization objective and the expected point, the original multiobjective optimization problem is transformed into a single objective optimization problem solution with tolerance measurement. Finally, in the simulation scene of a multienergy system, it is demonstrated that compared with the optimal results under each single objective method, the proposed method increases power line loss, maximum voltage deviation, new energy consumption, and economy by 2.22, 2.30, 1.02, and 2.45 times, respectively. Compared with the suboptimal results, the proposed method reduces power line loss by 22.26, 1.74, 1.09, and 0.97 times, respectively. Combining the shape of the Pareto frontier, it is demonstrated that the proposed method can comprehensively consider the needs of multiple power optimization objectives for forming a more reasonable and effective system optimization scheduling and also provide a new approach for solving multiobjective optimization problems.

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A hierarchical multi‐area capacity planning model considering configuration ratios of renewable energy and energy storage systems with multi‐area coordination

Cited by 6 publications

References 46 publications

A closed‐loop representative day selection framework for generation and transmission expansion planning with demand response

A closed‐loop representative day selection framework for generation and transmission expansion planning with demand response

A network search space reduction method for robust coordinated energy storage and transmission expansion planning

The Multiobjective Control Based on Tolerance Optimization in a Multienergy System

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