This paper presents a novel algorithm for nighttime detection of the lane markers painted on a road at night. First of all, the proposed algorithm uses neighborhood average filtering, 8-directional Sobel operator and thresholding segmentation based on OTSU's to handle raw lane images taken from a digital CCD camera. Secondly, combining intensity map and gradient map, we analyze the distribution features of pixels on boundaries of lanes in the nighttime and construct 4 feature sets for these points, which are helpful to supply with sufficient data related to lane boundaries to detect lane markers much more robustly. Then, the searching method in multiple directions-horizontal, vertical and diagonal directions, is conducted to eliminate the noise points on lane boundaries. Adapted Hough transformation is utilized to obtain the feature parameters related to the lane edge. The proposed algorithm can not only significantly improve detection performance for the lane marker, but it requires less computational power. Finally, the algorithm is proved to be reliable and robust in lane detection in a nighttime scenario.

Swap charging (SC) technology offers the possibility of swapping the batteries of electric vehicles (EVs), providing a perfect solution for achieving a long-distance freeway trip. Based on SC technology, a shared SC system (SSCS) concept is proposed to overcome the difficulties in optimal swap battery strategies for a large number of EVs with charging requests and to consider the variance in the battery charging rate simultaneously. To realize the optimal SSCS design, a binary integer programming model is developed to balance the tradeoff between the detour travel cost and the total battery recharge cost in the SSCS. The proposed method is verified with a numerical example of the freeway system in Guangdong Province, China, and can obtain an exact solution using off-the-shelf commercial solvers (e.g., Gurobi).

In this study, optimal reactive power regulation in distribution networks is achieved through the use of distributed reactive power regulators that can 1) perceive their own voltage magnitude and the P/Q flows in the connected branches, 2) communicate with nearby regulators, and 3) adjust the reactive power injections into the grid to minimize system power losses and maintain the bus voltages of nearby loads. Compared with many existing distributed reactive power regulation strategies, the proposed method can estimate and maintain the bus voltage of unmeasurable load buses within the limitations. Furthermore, this method releases the hardly achieved bus voltage angle requirement, which makes it practical for real-world. INDEX TERMS Distributed reactive power regulation, distributed optimization, branch flow measurement, linear model approximation.

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This paper proposes a dynamic-decision-based realtime dispatch method to coordinate the economic objective with multiple types of security dispatch objectives while reducing constraint violations in the process of adjusting the system operation point to the optimum. In each decision moment, the following tasks are executed in turn: ① locally linearizing the system model at the current operation point with the online model identification by using measurements; ② narrowing down the gaps between unsatisfied security requirements and their security thresholds in order of priority; ③ minimizing the generation cost; ④ minimizing the security indicators within their security thresholds. Compared with the existing real-time dispatch strategies, the proposed method can adjust the deviations caused by unpredictable power flow fluctuations, avoid dispatch bias caused by model parameter errors, and reduce the constraint violations in the dispatch decision process. The effectiveness of the proposed method is verified with the IEEE 39-bus system.