Distribution Locational Marginal Pricing through Quadratic Programming for Congestion Management in Distribution Networks

Shaojun Huang; Qiuwei Wu; Shmuel S. Oren; Ruoyang Li; Zhaoxi Liu

doi:10.1109/TPWRS.2014.2359977

Distribution Locational Marginal Pricing through Quadratic Programming for Congestion Management in Distribution Networks

Shaojun Huang, Qiuwei Wu, Shmuel S. Oren, Ruoyang Li, Zhaoxi Liu

University of California at Berkeley

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Abstract

This paper presents the distribution locational mar- ginal pricing (DLMP) method through quadratic programming (QP) designed to alleviate the congestion that might occur in a distribution network with high penetration of flexible demands. In the DLMP method, the distribution system operator (DSO) calculates dynamic tariffs and publishes them to the aggregators, who make the optimal energy plans for the flexible demands. The DLMP through QP instead of linear programing as studied in previous literatures solves the multiple solution issue of the ag- gregator optimization which may cause the decentralized conges- tion management by DLMP to fail. It is proven in this paper, using convex optimization theory, the aggregator’s optimization problem through QP is strictly convex and has a unique solution. The Karush–Kuhn–Tucker (KKT) conditions and the unique solution of the aggregator optimi zation ensure that the central- ized DSO optimization and the decentralized aggregator optimi- zation converge. Case studies using a distribution network with high penetration of electric vehicles (EVs) and heat pumps (HPs) validate the equivalence of the two optimization setups, and the efficacy of the proposed DLMP through QP for congestion man- agement.

Original language	English
Journal	IEEE Transactions on Power Systems
Volume	30
Issue number	4
Pages (from-to)	2170 - 2178
Number of pages	9
ISSN	0885-8950
DOIs	https://doi.org/10.1109/TPWRS.2014.2359977
Publication status	Published - 2015

Bibliographical note

(c) 2015 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.

Keywords

Congestion management
Distribution location- al marginal pricing (DLMP)
Distribution system operator (DSO)
Electric Vehicle (EV)
Heat pump (HP)

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Quadratic programming DLMP 20140809Accepted author manuscript, 170 KB

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title = "Distribution Locational Marginal Pricing through Quadratic Programming for Congestion Management in Distribution Networks",

abstract = "This paper presents the distribution locational mar- ginal pricing (DLMP) method through quadratic programming (QP) designed to alleviate the congestion that might occur in a distribution network with high penetration of flexible demands. In the DLMP method, the distribution system operator (DSO) calculates dynamic tariffs and publishes them to the aggregators, who make the optimal energy plans for the flexible demands. The DLMP through QP instead of linear programing as studied in previous literatures solves the multiple solution issue of the ag- gregator optimization which may cause the decentralized conges- tion management by DLMP to fail. It is proven in this paper, using convex optimization theory, the aggregator{\textquoteright}s optimization problem through QP is strictly convex and has a unique solution. The Karush–Kuhn–Tucker (KKT) conditions and the unique solution of the aggregator optimi zation ensure that the central- ized DSO optimization and the decentralized aggregator optimi- zation converge. Case studies using a distribution network with high penetration of electric vehicles (EVs) and heat pumps (HPs) validate the equivalence of the two optimization setups, and the efficacy of the proposed DLMP through QP for congestion man- agement. ",

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note = "(c) 2015 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.",

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Distribution Locational Marginal Pricing through Quadratic Programming for Congestion Management in Distribution Networks

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