Substation Capacity Planning Method Considering Interruptible Load

Jiang, Shiyao; Zeng, Yuanyuan; Cheng, Lin; Tian, Liting; Zhao, Jiazhu; Yan, Bowen; Wang, Xin; Li, Canbing

doi:10.1109/powercon.2018.8602045

Cited by 4 publications

(3 citation statements)

References 11 publications

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“…Thus, the actual time of limited access for consumers could be further reduced. Another legal possibility for implementing those DR operations is the introduction of interruptible contracts [16,25,41]. The interruptible contracts allow DSO to shed some consumer load in exchange for financial payment to consumers.…”

Section: Discussionmentioning

confidence: 99%

“…Esmat and Usaola [15] developed an algorithm allowing to minimize the total cost of congestion management and taking into account payback effects. Jiang et al [16] incorporated interruptible loads into substation capacity planning. Mullen [17] investigated the important interactions between demand-side response, load recovery, peak pricing, and network capacity margins.…”

Section: Introductionmentioning

confidence: 99%

“…Figure16. Yearly temperature duration curves: 75% reserve in "energy-shedding" mode leading to less than 1% energy curtailment, as seen in Figure14d.…”

mentioning

confidence: 98%

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Demand Response Coupled with Dynamic Thermal Rating for Increased Transformer Reserve and Lifetime

et al. 2021

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(1) Background: This paper proposes a strategy coupling Demand Response Program with Dynamic Thermal Rating to ensure a transformer reserve for the load connection. This solution is an alternative to expensive grid reinforcements. (2) Methods: The proposed methodology firstly considers the N-1 mode under strict assumptions on load and ambient temperature and then identifies critical periods of the year when transformer constraints are violated. For each critical period, the integrated management/sizing problem is solved in YALMIP to find the minimal Demand Response needed to ensure a load connection. However, due to the nonlinear thermal model of transformers, the optimization problem becomes intractable at long periods. To overcome this problem, a validated piece-wise linearization is applied here. (3) Results: It is possible to increase reserve margins significantly compared to conventional approaches. These high reserve margins could be achieved for relatively small Demand Response volumes. For instance, a reserve margin of 75% (of transformer nominal rating) can be ensured if only 1% of the annual energy is curtailed. Moreover, the maximal amplitude of Demand Response (in kW) should be activated only 2–3 h during a year. (4) Conclusions: Improvements for combining Demand Response with Dynamic Thermal Rating are suggested. Results could be used to develop consumer connection agreements with variable network access.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%