Multi-Area Interchange Scheduling Under Uncertainty

Ji, Yuting; Tong, Lang

doi:10.1109/tpwrs.2017.2727326

Cited by 20 publications

(16 citation statements)

References 15 publications

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“…1, which takes the distribution network with DG (i.e., the distribution network includes two different entities: DNO and DG owner) as an example. And the original distribution network and be decomposed into two regions (i.e., distribution network region and DG region) through duplicating boundary bus N. More details about region decomposition could be found in [23], [24].…”

Section: A Virtual Region Decompositionmentioning

confidence: 99%

“…Besides, nodes 18 and 26 are equipped with 10MW and 8MW wind turbines (WT) respectively. In addition, the load connected with nodes 15,16,19,20,23,24,30 and 31 are assumed FL (i.e.,prosumers) and the others are CL. The load data of distribution are derived from the actual operation data in Henan Province, China, and the total prediction load curve (i.e., the sum of CL and FL before implementing DR program) and the prediction output of WT in a typical day are shown in Fig.…”

Section: A Basic Datamentioning

confidence: 99%

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Distributed Optimal Dispatching of Multi-Entity Distribution Network With Demand Response and Edge Computing

Wang

Peng

2020

IEEE Access

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With large-scale penetrations of distributed generation (DG) and flexible loads, there will be multiple entities in traditional distribution network, such as distribution network operator (DNO), DG owner, and prosumers. Aiming at the collaborative optimization problem of distribution network among multiple entities, a distributed optimal scheduling approach of distribution network considering demand response and edge computing is proposed in this paper. Firstly, the virtual region decomposition method is proposed to divide the original distribution network into multiple regions according to different entities, and the bi-level optimization framework based on edge computing is constructed. Secondly, the optimal models of DNO, DG owner, and prosumers are established respectively, and the distributed optimal scheduling approach of distribution network with collaboration of control center and edge nodes is proposed. Then, the KKT conditions are adopted to realize the transformation of optimal models of DG owner and prosumers. Finally, the proposed distributed optimization scheduling approach is verified based on the modified IEEE33-node system. The results show that the proposed distributed optimal scheduling method can achieve better collaborative optimization among different entities in distribution network compared with the centralized optimization method. INDEX TERMS Demand response, edge computing, distributed optimization, KKT transformation, optimal dispatching.

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Section: A Virtual Region Decompositionmentioning

confidence: 99%

Section: A Basic Datamentioning

confidence: 99%

Distributed Optimal Dispatching of Multi-Entity Distribution Network With Demand Response and Edge Computing

Wang

Peng

2020

IEEE Access

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“…This is due to the way regional system operators and the higher-level system operator (or coordinator) are organised, e.g. the hierarchical control architecture in China [3,4], and the proxy bus systems in the US [5,6]. Although easy to implement, current methods may suffer from suboptimality or market inefficiency [4,6].…”

Section: Parameters Nl a Gmentioning

confidence: 99%

Global solution method for decentralised multi‐area SCUC and savings allocation based on MILP value functions

Zheng

Chen

et al. 2020

IET Generation, Transmission & Distribution

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“…In practice, an ISO may need to set multiple interfaces simultaneously. An extension to interchange scheduling involving more than two areas is nontrivial, see [19]. Generalizations to CTS to a stochastic setting is considered in [20].…”

Section: Literature Reviewmentioning

confidence: 99%

“…When there are more than two areas, tie-line congestions may induce positive shadow prices ρ for interface bids over other interfaces. Nevertheless, the calculation of ρ is the same as in(19), and the shadow price should be evenly split by neighboring areas.…”

mentioning

confidence: 99%

Generalized Coordinated Transaction Scheduling: A Market Approach to Seamless Interfaces

Guo

Tong

2018

IEEE Trans. Power Syst.

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A generalization of the coordinated transaction scheduling (CTS)-the state-of-the-art interchange scheduling-is proposed. Referred to as generalized coordinated transaction scheduling (GCTS), the proposed approach addresses major seams issues of CTS: the ad hoc use of proxy buses, the presence of loop flow as a result of proxy bus approximation, and difficulties in dealing with multiple interfaces. By allowing market participants to submit bids across market boundaries, GCTS also generalizes the joint economic dispatch that achieves seamless interchange without market participants. It is shown that GCTS asymptotically achieves seamless interface under certain conditions. GCTS is also shown to be revenue adequate in that each regional market has a non-negative net revenue that is equal to its congestion rent. Numerical examples are presented to illustrate the quantitative improvement of the proposed approach.

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Multi-Area Interchange Scheduling Under Uncertainty

Cited by 20 publications

References 15 publications

Distributed Optimal Dispatching of Multi-Entity Distribution Network With Demand Response and Edge Computing

Distributed Optimal Dispatching of Multi-Entity Distribution Network With Demand Response and Edge Computing

Global solution method for decentralised multi‐area SCUC and savings allocation based on MILP value functions

Generalized Coordinated Transaction Scheduling: A Market Approach to Seamless Interfaces

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