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A Distributed Economic Dispatch Mechanism to Implement Distribution Locational Marginal Pricing
KTH, School of Electrical Engineering and Computer Science (EECS), Electric Power and Energy Systems.ORCID iD: 0000-0003-0471-9066
KTH, School of Electrical Engineering and Computer Science (EECS), Electric Power and Energy Systems.
2018 (English)In: 2018 POWER SYSTEMS COMPUTATION CONFERENCE (PSCC), IEEE , 2018Conference paper, Published paper (Refereed)
Abstract [en]

We address the challenges of power flow computation and network operator coordination to implement distribution locational marginal pricing (DLMP) in this paper. Compared with other dynamic pricing schemes, DLMP can give clearer economic signals regarding distributed energy resources (DERs) investment, demand side response, congestion management and network reinforcement. Without neglecting the power loss of distribution network, the second-order cone AC optimal power flow (SOPF) model is used here to calculate DLMP. A distributed economic dispatch mechanism based on the modified Benders decomposition and distributed generation cost (DGC) is proposed to reduce the dispatch complexity in facing high penetration of DERs. The key contribution is that we take the tie-line power flow as the complicating variable to formulate the modified Benders decomposition algorithm. The concept of DGC is proposed to reallocate the global dispatch cost to economically incentivize the regional network operators for coordination. The distributed economic dispatch mechanism is implemented in GAMS grid computing platform. Numerical results show that SOPF can give accurate power flow and DLMP results. The fast convergence of the proposed distributed dispatch is guaranteed by the convexity of the SOPF model and efficient grid computing technique.

Place, publisher, year, edition, pages
IEEE , 2018.
Keywords [en]
Terms Distribution locational marginal pricing, optimal power flow, Benders decomposition, distributed economic dispatch, GAMS grid computing
National Category
Other Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
URN: urn:nbn:se:kth:diva-238166DOI: 10.23919/PSCC.2018.8442804ISI: 000447282400117Scopus ID: 2-s2.0-85054011288OAI: oai:DiVA.org:kth-238166DiVA, id: diva2:1261382
Conference
2018 POWER SYSTEMS COMPUTATION CONFERENCE (PSCC)
Note

QC 20181107

Available from: 2018-11-07 Created: 2018-11-07 Last updated: 2018-11-07Bibliographically approved

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Yuan, ZhaoHesamzadeh, Mohammad Reza

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