Coordinated Control of Voltage Balancers for the Regulation of Unbalanced Voltage in a Multi-Node Bipolar DC Distribution Network

In a bipolar DC distribution network, the unbalanced load resistance, line resistance and renewable energy source will cause an unbalanced current for each node of the neutral line and lead to its unbalanced voltage. This is a unique power quality problem of bipolar DC distribution networks, which will increase the power loss in the network and lead to overcurrent protection of the neutral line in serious cases. A voltage balancer can be adopted to suppress the unbalanced voltage and current. However, the existing literature does not consider the consistent application of multiple voltage balancers in a multi-node bipolar DC distribution network. This paper creatively proposes a consensus control topology combining primary control and secondary control in a radial multi-node bipolar DC distribution network with voltage balancers. In this paper, the formulas for the positive and negative current and duty cycle of a bipolar DC distribution network with voltage balancers are derived, and improved voltage balancer modeling based on a consensus algorithm is built. The radial multi-node bipolar DC distribution network is established in MATLAB/Simulink. The simulation results compare the consensus control with the traditional droop control and verify the effectiveness of the new control structure with voltage balancers.

Standardizing Performance Metrics for Building-Level Electrical Distribution Systems

Building-level electrical distribution systems comprise a myriad of current-carrying equipment, conversion devices, and protection devices that deliver power from the utility or local distributed energy resources to end-use building loads. Electric power has traditionally been generated, transmitted, and distributed in ac. However, the last decade has seen a significant increase in the integration of native dc equipment that has elevated the importance of dc distribution systems. Numerous studies have comparatively examined the performance of various electrical distribution systems in buildings but have failed to achieve uniform conclusions, primarily because of a lack of consistent and analogous performance evaluation methods. This paper aims to fill this gap by providing a standard set of metrics and measurement boundaries to consistently evaluate the performance of ac, dc, or hybrid ac/dc electrical distribution systems. The efficacy of the proposed approach is evaluated on a representative medium-sized commercial office building model with ac distribution and an equivalent hybrid ac/dc and dc distribution model, wherein the ac distribution model is concluded to be the most efficient. The simulation results show variation in computed metrics with different selected boundaries that verify the effectiveness of the proposed approach in ensuring consistent computation of the performance of building-level electrical distribution systems. This paper provides an initial set of guidelines for building energy system stakeholders to adopt appropriate solutions, thus leading to more efficient energy systems.

Fault Location with High Precision of Flexible DC Distribution System Using Wavelet Transform and Convolution Neural Network

Though flexible DC distribution system (FDCDS) is becoming a new hotspot in power systems lately because of the rapid development of power electronic devices and massive use of renewable energy, the failure to realize accurate fault location with high precision restricts its further application. Thus, a novel precise pole-to-ground fault location method of FDCDS based on wavelet transform (WT) and convolution neural network (CNN) is proposed in this paper for the limitation on the number of measuring points and high difficulty in extracting characteristics of FDCDS. The fault voltage signal is decomposed with multi-resolution by discrete wavelet transform (DWT), and then the transient energy function is constructed to select the frequency bands containing rich fault characteristics for signal reconstruction. The reconstructed signal forms two-dimensional time-frequency images through continuous wavelet transform (CWT), which are used as the input of CNN classifier after image enhancement to form the mapping relation between the fault feature and fault position using the powerful generalization ability of CNN, so as to complete fault location with high precision. The sample data on PSCAD/EMTDC verifies the accuracy and reliability of the proposed method, which can achieve fault location with positioning precision of 30 m. The proposed method overcomes the influence of the control strategy of the converter and the number of input capacitors of the bridge arm in the time-domain analysis, and still has strong robustness in the case that FDCDS is connected with many distributed generations (DGs) with output fluctuation. Furthermore, four other methods for fault location as comparisons are given to reflect the validity and anti-interference ability of proposed methods in various noises.