An increase in the neutral current results in a malfunction of the low energy over current (LCO) protective relay and raises the neutral-to-ground voltage in three-phase, four-wire radial distribution feeders. Thus, the key point for mitigating its effect is to keep the current under a specific level. The most common approach for reducing the neutral current caused by the inherent imbalance of distribution feeders is to rearrange the phase connection between the distribution transformers and the load tapped-off points by using the metaheuristics algorithms. However, the primary task is to obtain the effective load data for phase rearrangement; otherwise, the outcomes would not be worthy of practical application. In this paper, the effective load data can be received from the feeder terminal unit (FTU) installed along the feeder of Taipower. The net load data consisting of customers’ power consumption and the power generation of distributed energy resources (DERs) were measured and transmitted to the feeder dispatch control center (FDCC). This paper proposes a method of establishing the equivalent full-scale net load model based on FTU data format, and the long short-term memory (LSTM) was adopted for monthly load forecasting. Furthermore, the full-scale net load model was built by the monthly per hour load data. Next, the particle swarm optimization (PSO) algorithm was applied to rearrange the phase connection of the distribution transformers with the aim of minimizing the neutral current. The outcomes of this paper are helpful for the optimal setting of the limit current of the LCO relay and to avoid its malfunction. Furthermore, the proposed method can also improve the three-phase imbalance of distribution feeders, thus reducing extra power loss and increasing the operating efficiency of three-phase induction motors.

This study proposes an adaptive Kalman filter (AKF) control algorithm for capacitive touch panels (CTPs) under the radiation effect of commercial fluorescent lamp. The predicted covariance matrix of proposed algorithm is timely updated by 2D gesture compensation. It adaptively adjusts the filter correction manner between fast tracking and smoothing modes. The trajectory area and velocity concept builds up the compensation method and proves in the real time practice by a microprocessor unit. The electromagnetic radiation effect is investigated to obtain the lamp emission noise level. A comprehensive system structure provides the flexibility and efficiency in competing with different algorithms for comparison. A microprocessor unit completed the AKF method calculation in 8.23 ms under fluorescent lamp lightening condition in real time. All Python environments are implemented in the merit of hardware peripheral support, rich programming environments and open source modules.

Three-phase balancing can improve the operation efficiency of distribution networks. The common approach is phase arrangement of each tapped-off point in unbalanced distribution networks. This complex problem requires searching for an optimal combination. Metaheuristic algorithms can efficiently solve this complicated problem. In this study, 10 common metaheuristic algorithms are applied in the IEEE 37- bus test system for optimal phase arrangement, and the performance of each of them is compared and discussed. The outcomes of this work are helpful for realizing energy loss reduction by phase balancing, which applies metaheuristic algorithms in unbalanced distribution networks.