Distribution Network Marginal Costs -- Part II: Case Study Based Numerical Findings
| Autor: | Andrianesis, Panagiotis, Caramanis, Michael |
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| Rok vydání: | 2019 |
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| Druh dokumentu: | Working Paper |
| Popis: | This two-part paper considers the day-ahead operational planning problem of a radial distribution network hosting Distributed Energy Resources (DERs), such as Solar Photovoltaic (PV) and Electric Vehicles (EVs). In Part I, we develop a novel AC Optimal Power Flow (OPF) model that estimates dynamic Distribution nodal Location Marginal Costs (DLMCs) of real and reactive power including transformer degradation. These all-inclusive DLMCs are key in the co-optimization of the distribution network and DER schedules. Part II discusses the implication of using DLMCs to represent the benefit of shifting real/reactive power across time and achieve optimal Distribution Network and DER operation. Moreover, it evaluates, elaborates and analyzes the novel AC OPF through extensive numerical results of actual distribution feeder-based case studies involving a wealth of future EV and PV adoption scenarios. Optimal schedules are compared to schedules that rely on apparently reasonable approaches, namely Business as Usual (i.e., do nothing), Time of Use, and traditional line loss minimization. The overwhelming evidence of extensive numerical results supports the significant benefits of internalizing short-run marginal asset - primarily transformer - degradation. Apart from optimal short-run scheduling, the proposed approach can harvest otherwise idle DER (PV/EV) reactive power compensation capabilities, increase distribution network DER (PV/EV) hosting capacity, and mitigate investments in distribution infrastructure that would be otherwise required to support distribution utilities' obligation to serve. Finally, numerical evidence on the benefits of AC OPF modeling intertemporal transformer life degradation suggests that it may be worth considering the introduction of intra-day markets. Comment: 8 pages |
| Databáze: | arXiv |
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