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Hierarchical coordination of TSO-DSO economic dispatch considering large-scale integration of distributed energy resources
KTH, School of Electrical Engineering (EES), Electric Power and Energy Systems.ORCID iD: 0000-0003-0471-9066
KTH, School of Electrical Engineering (EES), Electric Power and Energy Systems.
2017 (English)In: Applied Energy, ISSN 0306-2619, E-ISSN 1872-9118, Vol. 195, p. 600-615Article in journal (Refereed) Published
Abstract [en]

This paper proposes a hierarchical coordination mechanism for coordinating the economic dispatch of transmission system operator (TSO) and distribution system operator (DSO). The challenge of dispatching large-scale distributed energy resources (DERs) is addressed. The coordination problem of dispatching energy and reserve is formulated. Benders decomposition is the underlying mathematical foundation of the proposed hierarchical coordination mechanism. We define the generalized bid function to approximate the dispatch cost of distribution network by a series of affine functions. The generalized bid function is communicated from DSO to TSO. By using convex AC optimal power flow model, the convergence of hierarchical coordination is guaranteed. A grid computing structure in General Algebraic Modeling System (GAMS) to accelerate the computation is proposed. The generalized bid function is simulated for various test cases. We also demonstrate the effect of DERs on the voltage magnitude and phase angle. The numerical results show that the hierarchical coordination using the generalized bid function converges to very close results compared with the results of centralized dispatch. Hierarchical coordination is capable of managing various network congestion scenarios and power loads. The generalized bid function provides a unified format of communication between TSO and DSO.

Place, publisher, year, edition, pages
Elsevier, 2017. Vol. 195, p. 600-615
Keywords [en]
DERs, Economic dispatch, Hierarchical coordination, Generalized bid function, Benders decomposition, Grid computing
National Category
Other Electrical Engineering, Electronic Engineering, Information Engineering
Research subject
Electrical Engineering
Identifiers
URN: urn:nbn:se:kth:diva-204865DOI: 10.1016/j.apenergy.2017.03.042Scopus ID: 2-s2.0-85016041367OAI: oai:DiVA.org:kth-204865DiVA, id: diva2:1086387
Note

QC 20170419

Available from: 2017-04-02 Created: 2017-04-02 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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