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Towards the Power Synergy Hub (PSHub): Coordinating the energy dispatch of super grid by modified Benders decomposition
KTH, School of Electrical Engineering (EES), Electric Power and Energy Systems.ORCID iD: 0000-0003-0471-9066
Comillas Pontifical University.
KTH, School of Electrical Engineering (EES), Electric Power and Energy Systems.
2017 (English)In: Applied Energy, ISSN 0306-2619, E-ISSN 1872-9118, Vol. 205, p. 1419-1434Article in journal (Refereed) Published
Abstract [en]

The challenge of operating ultra-large-scale power system or super grid is addressed in this paper. We set up the concept of power synergy hub (PSHub) serving as the operation hub coordinating the energy dispatch of multiple nations or regions across the continent to achieve global optimal targets. An efficient mechanism based on the modified Benders decomposition (BD) is proposed to coordinate the operations of national or regional power networks. The key contribution is that we take the total power outputs of regional power networks as the complicating variables to formulate the master problem and subproblems in the modified BD. Instead of using DC optimal power flow model (DC OPF), we propose to use convex AC optimal power flow model based on second-order cone programming (SOC-ACOPF) to operate the super grid. A comprehensive investigation proves that the SOC-ACOPF outperforms DC OPF in terms of accuracy. Numerical evaluations also show that our SOC-ACOPF model has stronger convergence capability and computational efficiency over other considered SOC-ACOPF models. The convergence of the modified BD is guaranteed by the convexity of SOC-ACOPF. A parallel computation framework in GAMS is proposed to assist real-time operation of the super grid. Compared with operating super grid in a centralized way, the modified BD approach shows stronger convergence capability, computational efficiency and robustness.

Place, publisher, year, edition, pages
Elsevier, 2017. Vol. 205, p. 1419-1434
Keywords [en]
Super grid, Power synergy hub, Energy dispatch, Optimal power flow, Modified Benders decomposition, Parallel computation
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Research subject
Electrical Engineering
Identifiers
URN: urn:nbn:se:kth:diva-217500DOI: 10.1016/j.apenergy.2017.09.086ISI: 000414817100112Scopus ID: 2-s2.0-85029576803OAI: oai:DiVA.org:kth-217500DiVA, id: diva2:1156595
Note

QC 20171114

Available from: 2017-11-13 Created: 2017-11-13 Last updated: 2018-05-07Bibliographically approved
In thesis
1. Convex Optimal Power Flow Based on Second-Order Cone Programming: Models, Algorithms and Applications
Open this publication in new window or tab >>Convex Optimal Power Flow Based on Second-Order Cone Programming: Models, Algorithms and Applications
2018 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Optimal power flow (OPF) is the fundamental mathematical model to optimally operate the power system. Improving the solution quality of OPF can help the power industry save billions of dollars annually. Past decades have witnessed enormous research efforts on OPF since J. Carpentier proposed the fully formulated alternating current OPF (ACOPF) model which is nonconvex. This thesis proposes three convex OPF models (SOC-ACOPF) based on second-order cone programming (SOCP) and McCormick envelope. The underlying idea of the proposed SOC-ACOPF models is to drop assumptions of the original SOC-ACOPF model by convex relaxation and approximation methods. A heuristic algorithm to recover feasible OPF solution from the relaxed solution of the proposed SOC-ACOPF models is developed. The quality of solutions with respect to global optimum is evaluated using MATPOWER and LINDOGLOBAL. A computational comparison with other SOC-ACOPF models in the literature is also conducted. The numerical results show robust performance of the proposed SOC-ACOPF models and the feasible solution recovery algorithm. We then propose to speed up solving large-scale SOC-ACOPF problem by decomposition and parallelization. We use spectral factorization to partition large power network to multiple subnetworks connected by tie-lines. A modified Benders decomposition algorithm (M-BDA) is proposed to solve the SOC-ACOPF problem iteratively. Taking the total power output of each subnetwork as the complicating variable, we formulate the SOC-ACOPF problem of tie-lines as the master problem and the SOC-ACOPF problems of the subnetworks as the subproblems in the proposed M-BDA. The feasibility of the proposed M-BDA is analytically proved. A GAMS grid computing framework is designed to compute the formulated subproblems in parallel. The numerical results show that the proposed M-BDA can solve large-scale SOC-ACOPF problem efficiently. Accelerated M-BDA by parallel computing converges within few iterations.Finally, various applications of our SOC-ACOPF models and M-BDA including distribution locational marginal pricing (DLMP), wind power integration and ultra-large-scale power network or super grid operation are demonstrated.

Place, publisher, year, edition, pages
KTH Royal Institute of Technology, 2018. p. 212
Keywords
Optimal Power Flow, Second-Order Cone Programming, Distribution Locational Marginal Pricing, Wind Power, Super Grid
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Research subject
Electrical Engineering
Identifiers
urn:nbn:se:kth:diva-227044 (URN)9789177296782 (ISBN)
Public defence
2018-05-29, Kollegiesalen, Brinellvägen 8, Stockholm, 09:00 (English)
Opponent
Supervisors
Note

QC 20180507

Available from: 2018-05-07 Created: 2018-05-02 Last updated: 2018-05-17Bibliographically approved

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