A two-stage constructive heuristic algorithm to handle integer investment variables in transmission network expansion planning

Oliveira, Ezequiel da Silva; Silva, Ivo Chaves da; Oliveira, Leonardo W. de; Mendonça, Isabela Miranda de; Gomes, Phillipe Vilaça; Saraiva, João Tomé

doi:10.1016/j.epsr.2020.106905

Cited by 7 publications

(6 citation statements)

References 15 publications

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“…In addition, although Case 14 consumes the least computational time, the computational accuracy is relatively low. This indicates that when applying the NSSR method, TABLE 12 The optimal constructed lines for different parameters (118-bus). it is necessary to select the appropriate values of 𝛼 L to balance accuracy and efficiency.…”

Section: 22mentioning

confidence: 97%

“…This method is suitable for the case where the construction number of lines allowed in the corridor is sufficiently large. References [11,12] construct heuristic algorithms to simplify the search space of the planning model, which are essentially used in the model-solving process and are better suited for stochastic planning calculations. However, since the algorithms are not independent of the model-solving process, it would complicate the iterative process if applied to robust optimization.…”

Section: Introductionmentioning

confidence: 99%

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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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Section: 22mentioning

confidence: 97%

Section: Introductionmentioning

confidence: 99%

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

View full text Add to dashboard Cite

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“…A novel ant colony-based TEP has been proposed in [36], which considers the expansion of the TS lines and adding additional series compensators to them. A novel constructive heuristic approach has been introduced in [37] to improve the quality of solutions in a TEP problem. A novel TEP based on a multi-stage deep Q-network method has been expressed in [38].…”

Section: Literature Reviewmentioning

confidence: 99%

“…Refs. [8,9,29,[36][37][38] did not consider the uncertainties. However, [11-19, 22-23, 25-28, 30, 32-35] have considered the uncertainties of the RESs and load demand.…”

Section: Literature Reviewmentioning

confidence: 99%

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Stochastic multi‐stage joint expansion planning of transmission system and energy hubs in the presence of correlated uncertainties

Allahvirdizadeh

Galvani

Shayanfar

2023

IET Renewable Power Gen

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Deployment of Energy Hubs (EHs) across the power grid can alleviate the Transmission System (TS) capacity and substitute the conventional fossil fuel‐based thermal units. Therefore, this paper presents a tri‐level multi‐stage Joint Expansion Planning of the Transmission system and EHs (JEPT&EHs). In this approach, the Cholesky decomposition technique combined with the Nataf transformation is applied to make the uncertain input parameters correlated. Then, the k‐means data‐clustering method is employed to reduce the initial correlated samples. In the first level, the Transmission System Operator (TSO) optimizes the planning and scheduling strategies associated with the TS capacity requirements and operation costs of the conventional generators. In the second level, the financers specify the expansion of the EHs based on the Locational Marginal Prices (LMPs). In the third level, the Direct Current Optimal Power Flow (DCOPF) is determined to update the LMPs by the Independent System Operator (ISO). The optimization problem is an Equilibrium Problem with Equilibrium Constraints (EPEC) since there are multiple financers across the TS. The proposed model is implemented on the IEEE standard 30 bus TS to present the effectiveness of the EHs' deployment and the impact of the correlations in the total costs of the TSO and financers.

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Mindful consumption – A systematic review and research agenda

Garg,

Bansal,

Rathi

et al. 2024

Journal of Cleaner Production

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A two-stage constructive heuristic algorithm to handle integer investment variables in transmission network expansion planning

Cited by 7 publications

References 15 publications

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

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

Stochastic multi‐stage joint expansion planning of transmission system and energy hubs in the presence of correlated uncertainties

Mindful consumption – A systematic review and research agenda

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