An inexact column-and-constraint generation method to solve two-stage robust optimization problems

Tsang, Man Yiu; Shehadeh, Karmel S.; Curtis, Frank E.

doi:10.1016/j.orl.2022.12.002

Cited by 12 publications

(4 citation statements)

References 19 publications

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“…17.36%. In Case II, transmission line 9-21 is to be built, strengthening the renewable energy transmitted from the group (25,26,27,28,29,30) to the rest of the system. In Case III, when the uncertainty on the PDFs is considered, the second-stage cost increases by 109.55%, where the storage expansion results are adjusted, i.e.…”

Section: Simulation Results Of Ieee-30 Bus Test Systemmentioning

confidence: 99%

“…With the increase of scenarios, the objective value converges to 1888 M$. When it comes to Cases V and VI, the nested C&CG converges in 2855.10 and 7322.03 s in Cases V and VI, respectively, which is much longer than the solution time in Cases I–IV, as the worst scenarios are to be explored by the inner C&CG iteration, which is strongly affected by the mixed‐integer gap of the master problem in the inner iterations [25]. These results verify the superiority of the proposed algorithm regarding computational time and scalability.…”

Section: Case Studiesmentioning

confidence: 99%

“…To further improve the robustness of discrete support-based ambiguity sets and balance the computational requirements, the Wasserstein-distance-based ambiguity sets with continuous support are adopted to guide the short-term operation within the high penetration of renewable energy resources [22,23]. It is important to note that these ambiguity sets primarily address exogenous uncertainties, such as climate conditions and loads [24,25].…”

Section: Literature Reviewmentioning

confidence: 99%

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Decision‐dependent distributionally robust integrated generation, transmission, and storage expansion planning: An enhanced Benders decomposition approach

Qiu,

Dan,

et al. 2023

IET Renewable Power Gen

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Integrated generation, transmission, and storage expansion planning (IGT&SP) is the cornerstone to realize low‐carbon transition considering security constraints in the long run. A novel IGT&SP planning scheme is proposed to balance the planning cost, i.e. renewable energy sources (RESs) and energy storage systems, based on the distributionally ambiguity sets. A novel decision‐dependent ambiguity set is proposed to capture the relation between the uncertainties of RES output and long‐term planning. A two‐stage risk‐averse distributionally robust optimization is formulated, where the RESs, energy storage systems, and transmission line expansion are optimized in the first stage and a unit commitment problem is proposed in the second‐stage optimization to assess the performance of the expanded system. This problem is reformulated into a two‐stage optimization problem with complete mixed‐integer recourse, where the state variable is binary. A novel enhanced Benders decomposition algorithm is proposed to solve the IGT&SEP efficiently, where the cutting planes are generated by a primal‐dual relaxation of the recourse problem. Simulations are conducted on the modified IEEE‐30 test system and modified IEEE‐118 test system. Compared with adjustable robust optimization and L1‐norm Wasserstein distance‐based distributionally robust optimization, numerical results verify the effectiveness of the proposed IGT&SP, together with the solution algorithm.

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Section: Simulation Results Of Ieee-30 Bus Test Systemmentioning

confidence: 99%

Section: Case Studiesmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

See 1 more Smart Citation

Decision‐dependent distributionally robust integrated generation, transmission, and storage expansion planning: An enhanced Benders decomposition approach

Qiu,

Dan,

et al. 2023

IET Renewable Power Gen

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“…For the above two-stage robust optimization model, due to the difficulty in solving the main problem, the i-C&CG algorithm is adopted herein [34]. i-C&CG algorithm is similar to C&CG) algorithm in that the alternate solution of the original problem consists of a main problem and a subproblem.…”

Section: An I-candcg Algorithmmentioning

confidence: 99%

Collaborative planning of data center and energy storage based on i-C&CG solving algorithm

2024

Journal of Electrical Systems

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With the rapid development of new power systems and advanced technologies such as artificial intelligence, the penetration rate of renewable energy is increasing, and the electricity consumption required for computing power calculation is surging. On the one hand, the uncertainty of wind power output has in-creasingly serious impact on the operation safety of power system. On the other hand, internet data center (IDC) needs to consume a lot of power to maintain the computing power system. Therefore, a two-stage robust collaborative programming model of IDC and BESS with life constraints is proposed herein. Plan storage capacity and data center server configuration with the goal of minimizing system operation and planning costs. An inexact column-and-constraint generation (i-C&CG) algorithm is proposed herein to solve the problem, and the IEEE-30 nodes system is simulated. The planning considering the life constraints of BESS are more reasonable, and i-C&CG algorithm can reduce the difficulty of solving two-stage robust planning problem of power system.

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A data-driven robust optimization framework for CCHP-P2G system considering the correlation of RES output

Haider,

Yang,

Rashed

et al. 2024

Electr Eng

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An inexact column-and-constraint generation method to solve two-stage robust optimization problems

Cited by 12 publications

References 19 publications

Decision‐dependent distributionally robust integrated generation, transmission, and storage expansion planning: An enhanced Benders decomposition approach

Decision‐dependent distributionally robust integrated generation, transmission, and storage expansion planning: An enhanced Benders decomposition approach

Collaborative planning of data center and energy storage based on i-C&CG solving algorithm

A data-driven robust optimization framework for CCHP-P2G system considering the correlation of RES output

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