Abstract
The increasing use of distributed generation and electric vehicle charging stations provokes violations of the operational limits in low voltage grids. The mitigation of voltage limit violations is addressed by Volt/var control strategies, while thermal overload is avoided by using congestion management. Congestions in low voltage grids can be managed by coordinating the active power contributions of the connected elements. As a prerequisite, the system state must be carefully observed. This study presents and investigates a method for the sparse measurement-based detection of feeder congestions that bypasses the major hurdles of distribution system state estimation. Furthermore, the developed method is used to enable congestion management by the centralized coordination of the distributed electric vehicle charging stations. Different algorithms are presented and tested by conducting load flow simulations on a real urban low voltage grid for several scenarios. Results show that the proposed method reliably detects all congestions, but in some cases, overloads are detected when none are present. A minimal detection accuracy of 73.07% is found across all simulations. The coordination algorithms react to detected congestions by reducing the power consumption of the corresponding charging stations. When properly designed, this strategy avoids congestions reliably but conservatively. Unnecessary reduction of the charging power may occur. In total, the presented solution offers an acceptable performance while requiring low implementation effort; no complex adaptations are required after grid reinforcement and expansion.
Highlights
The electricity grid is traditionally divided into the transmission level, which includes the high and very high voltage grids, and the distribution level, which includes the medium and low voltage grids [1]
The distributed power injections and absorptions may provoke voltage limit violations [2,3] and congestions [3,4,5], i.e., transformer and line overloading. Both types of limit violations are separately addressed by two different operation processes: Volt/var control and congestion management
This assumption is justified by the following considerations: Due to the spatial proximity of customer plants (CP) connected to one low voltage (LV) grid, their PV systems always inject simultaneously
Summary
The electricity grid is traditionally divided into the transmission level, which includes the high and very high voltage grids, and the distribution level, which includes the medium and low voltage grids [1]. 22.1.1.1.1..MMaatthheemmaatticicaallFFoorrmmuulalattioionn EEuurrooppeeaannLLVV ggrriiddss aarree ttyyppiiccaallllyy ooff aa rraaddiiaall ssttrruuccttuurree,, aanndd tthhee CCPPss aarree ccoonnnneecctteedd ssoommeewwhheerreeaalolonnggththeefefeeeddeersrs[2[299].].TThheeddeteatialieldedstsrtuructcuturereofoaf nanLLVVggrirdidwwitihthFF ffeeeeddeerrssiiss sscchheemmaatitzizeeddininFFigiguurere11aa. Condition (5b) roots on the assumption that the feeder is sufficiently dimensioned to cope with the installed PV rating, so that upstream (from feeder end to distribution substation) active power flows do not cause an exceedance of the specified loading limit This assumption is justified by the following considerations: Due to the spatial proximity of CPs connected to one LV grid, their PV systems always inject simultaneously. The estimation of the reactive power contribution of Q(U) controlled PV systems is hardly possible without using exact feeder models and state estimation, as it depends on the local feeder voltage It is very conservative, the use of the maximal possible value according to the specified control characteristic is suggested, Equation (11). ∑∀ f Pfsrc > 0 where LoadinglDimTiRt is the limit of the DTR loading, specified by the grid operator
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