Control of an Autonomous Energy Complex with Renewable Energy Sources, taking into account the Type of Input Information Uncertainty

Симанков, Владимир Сергеевич; Buchatskiy, Pavel Yu.; Shopin, Andrey V.; Teploukhov, Semen V.; Buchatskaya, Victoria V.

doi:10.1109/cts53513.2021.9562875

Cited by 2 publications

(1 citation statement)

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“…The proposed algorithm employs the demand forecast as the primary source of data; thus, if the forecast is inaccurate, the inaccuracy caused propagates to the algorithm's outputs, as shown in Figure 19. One of the primary causes of uncertainty is the influence of the DRG [52] which may differ from the predicted condition. In such a case, the algorithm will be unable to fully achieve load-levelling because it operates in a "open-loop" form, with no ability to enable ex post modifications.…”

Section: Discussionmentioning

confidence: 99%

A Novel Unidirectional Smart Charging Management Algorithm for Electric Buses

et al. 2023

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The difficulty of controlling the charging of electric buses (EBs) and their effects on network demand are discussed in this study. The solutions suggest a call for worldwide, complex infrastructures that manage EVs and EBs equally. Additionally, the Distribution Network (DN) must be prepared for an increased prevalence of reverse power flow caused by widespread distributed renewable generation. This paper focuses exclusively on EBs since they have higher capacity and predictable charging patterns, which makes them more significant for the DN in the context of a transition to complete vehicle electrification and technologies that are mature enough to be hosted. The proposed algorithm employs the Day-Ahead Energy Market (DAEM) in the Smart Charging (SC) to forecast the network operating circumstances. Additionally, the technique makes it possible to facilitate distributed photovoltaic (PV) generation, allowing network demand to be referenced depending on net demand. It also identifies an appropriate individual charger current per vehicle and per-time-step with load-levelling or peak-shaving as its primary goal. The final real demand demonstrates that a coarse correction of the demand is possible. According to the analysis of the DN voltage profile and associated line losses, the ideal node position location of the CS is dependent on PV penetration.

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Section: Discussionmentioning

confidence: 99%