A Hierarchical Real-Time Balancing Market Considering Multi-Microgrids With Distributed Sustainable Resources

A hierarchical market structure is proposed in this paper for multiple microgrids to participate in transmission-level real-time balancing markets and to provide ancillary services to the utility grid. At the distribution level, local microgrids with distributed sustainable resources, such as demand...

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Vydané v:IEEE transactions on sustainable energy Ročník 11; číslo 1; s. 72 - 83
Hlavní autori: Du, Yan, Li, Fangxing
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Piscataway IEEE 01.01.2020
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Predmet:
Ancillary services
Balancing
Complementarity
Computer simulation
Constraints
Convexification
Electric power distribution
Electric power grids
Electricity supply industry
Energy management
Energy storage
hierarchical balancing market
Kuhn-Tucker method
Load flow
Load management
Mathematical model
mathematical program with complementary constraints (MPCC)
Mathematical programming
Microgrids
Mixed integer
multi-microgrid
multivariate regression
Optimization
Power flow
Real time
Real-time systems
Structural hierarchy
Topology
ISSN:1949-3029, 1949-3037
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Shrnutí:A hierarchical market structure is proposed in this paper for multiple microgrids to participate in transmission-level real-time balancing markets and to provide ancillary services to the utility grid. At the distribution level, local microgrids with distributed sustainable resources, such as demand response, distributed renewables, and energy storage, are economically dispatched by a distribution system operator (DSO). A bi-level optimization model is formulated to guarantee the goals of both DSO and microgrids. It is solved by developing Karush-Kuhn-Tucker conditions and combining the two problems into one mathematical programming with complementarity constraints. Furthermore, since the physical topology and distribution power flow constraints are enclosed to form a non-convex optimal power flow model, a convexification technique is implemented to transform the original problem into a mixed integer quadratic constrained problem for better computation performance. At the transmission level, DSOs strategically bid with generation companies to win the desired share of the market managed by a transmission system operator. A multivariate linear regression is developed to capture the correlation between the bid gained and the prices offered by the DSO and its opponents to maximize its possibility of winning the bid. Simulation studies on IEEE test systems verify the proposed framework.
Bibliografia:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:1949-3029
1949-3037
DOI:10.1109/TSTE.2018.2884223