This paper aims at presenting a thorough literature survey on existing electric drives developed for solar tracking systems in concentrated solar power plants (CSP) plants. To start with, a brief background on CSP and its low-cost initiatives are presented, followed by introducing specific requirements for the electric motor-gearbox system. In addition, existing drives adopting different types of electric motors are systematically reviewed. Finally, a comparative study of different commercial drives reveals that the drive cost per unit area and its cost share of the entire heliostat will increase with heliostats going smaller, thereby indicating more potentials and opportunities to further optimize electric drives and cut down the cost for heliostats with a small mirror size and better exploit sunlight for the maximum energy yield for solar tracking control.

Ultra-high speed machines have become more and more interesting to researchers in the past few decades. Switched reluctance machines (SRMs) are very attractive to researchers due to their simple geometry. However, traditional control methods are not suitable for ultra-high speed applications because of their super-high switching frequency. In this paper, a constant volts per hertz control for ultra-high speed SRMs over the entire speed range from 0 to 1 million rpm is proposed. The main idea is to reach one pulse per stroke over the entire speed range by controlling the supply voltage over rotational speed to be a constant value and fixing the switching on and off angles close but before the machine goes into saturation. A Simulink closed loop control model is built based on the finite element model to validate the proposed control. The results show that the switching frequency is decreased to a minimum value.

For the widely-adopted inverter-fed drives, the stator winding insulation is more prone to various stresses compared to the line-start machines, i.e. the high rates of voltage change due to inverter switching (dv/dt), which will result in higher chances of insulation breakdown. To better illustrate the dynamic behaviors of the IPM machines under the stator turn fault, this paper presents a transient model of the in the dqrrotor reference frame where most control algorithms are designed upon, instead of the traditional modeling work commonly adopted in the abc reference frame. In addition, a state-space representation of the dynamic equations is provided by considering the shifts of the three-phase line-to-neutral voltages. Finally, a simplified form of the proposed model in the early-stage turn fault period is proposed and various machine characteristics are illustrated in detail with different severities of the stator turn fault. This model is beneficial for investigating the machine characteristics under various motor control algorithms as the turn fault propagates to the neighboring turns and eventually turn into a complete line-to-ground fault.

Non-intrusive load monitoring (NEM) is a load monitoring technique proposed to be used in today's residential energy auditor. It is expected to automatically provide the information of the type, energy consumption, and operation status of the electric loads without getting access to the loads. However, there still not exists any commercialized product so far, mainly because of the extraordinary large load sets comparing with the limited learning data. The fast emerging of new types of loads further aggravates the problem. This paper proposes an adaptive non-intrusive load identification model to address this problem. The proposed model is not dedicated to identify all the loads around the world, but it will grasp knowledge from samples that are not identified in the real application, and gradually form a new learning procedure so as to identify more and more new samples correctly. Random forest algorithm is introduced here to realize the objective and a case study is carried out to verify the effectiveness of the model.

This paper presents a methods of utilizing building-level demand response in microgrid frequency regulation. Based on an in-depth study of building loads, a bi-level framework of building demand response control is presented to determine the controllability and demand response participation timescale of different loads. Based on this framework, the internal control scheme of buildings is presented in analogy to negative generators. The contribution of building-level demand response to microgrid frequency regulation is discussed in details. The large power loss on transmission lines in microgrids is considered, and the heterogeneity among buildings in their contribution to system frequency deviation is discussed. A test case is studied to prove the efficacy of building-level demand response in microgrid frequency regulation, and the advantage of building-level demand response over single-load demand response.

Inductive charging for Electric Vehicles (EVs) applies high frequency alternating currents in the transmitter pad or coil to inductively transfer power through loosely coupled induction to the receiving coil in EVs. The emerging of multiple EVs calls for a universal charging system that can charge most EVs efficiently and safely in variable external environments. This paper presents a comprehensive summary of considerations for designing a universal inductive charger, including that in hardware design such as topology, charging pads and batteries, and transient information such as voltage/current, status, weather, faults. Different options are provided and compared, and the suggested solution is reached after the analysis.

Miscellaneous electric loads (MELs) currently consume more electricity than any other single major category of electric appliances. MELs provide valuable energy consumption and performance information which can be utilized to meet the raising needs and opportunities of energy saving, demand response, peak shaving, and building management. A reliable intelligent method to identify different MELs is a prerequisite of all purposes. A support-vector-machine (SVM) based hybrid identification method of MELs is proposed in this paper. Studies on applying only SVM as well as a combination of SVM and supervised Self-Organizing Map (SSOM) are presented. SSOM first cluster a large number of MELs into several classes. MELs with similar feature values fall into the same class. SVM is then utilized to identify similar MELs. The proposed method shows satisfactory accuracy in tests using real-world data.

This paper presents a new isolated bidirectional DC/DC converter for auxiliary power supplies in electric vehicles where high power density, bidirectional power flow and electric isolation are required. Compared to conventional bidirectional converters, this modified half-bridge circuit further minimizes components to 2 capacitors without any other change based on the existing highest power density circuit. With a novel PWM plus phase-shift (PPS) control strategy, it minimizes device current stresses over a wide input voltage range. Moreover, a natural zero-voltage switching method for the whole switches is achieved without additional device to reduce switching loss and device inrush voltage stresses. These advantages make the new converter promising for high power density applications, especially to overcome the high device current stresses problem caused by wide range ultra-capacitor voltage variation. In this paper, firstly, a complete design consideration and principle of the new topology is presented; secondly, an analysis of static state mode is provided; finally, a 15V/50W prototype is built up after a 60V/4kW modeling simulation on computer and it successfully proved this converter's device current stresses minimization and high power density characteristics.

In building energy management area, many studies have been done on energy saving technologies of the high-power loads like HVACs, pumps and compressors, which will exert a great influence on demand side management. However, another group of loads defined as plug-in loads are also widely used and consume over 37% of the electricity in buildings. Usage of plug-in loads is typically directly affected by the consumer and real time pricing, and an effective management of these loads will also provide significant energy saving. To better understand the loads in residential home, this paper presents a comprehensive study of the plug-in load topologies at residential home.

Dramatic reductions in sensor, computing and communications costs, coupled with significant performance enhancements has increased the possibility of realizing widely and massively distributed power line sensor networks (PLSNs) to monitor utility asset status for enhancing line reliability and utilization. One of the important applications of such a PLSN is to evaluate the overhead power line dynamic current capacity down to dasiaper spanpsila level of granularity. Due to the inherent non-linearity of overhead conductor thermal behavior, it is usually quite complex to directly calculate the conductor temperature. Therefore the prediction for the conductor dynamic thermal behavior becomes difficult. In this work, an echo state network (ESN) is proposed to identify the overhead conductor thermal dynamics in real-time. The well trained ESN model is used to predict the dynamic thermal behavior, and thus to evaluate the dynamic current capacity of the line under current ambient weather conditions. This paper addresses the design and implementation issues for such an ESN for this specific application. Simulation results reveal that the ESN model is very effective to predict the conductor temperature and to identify the conductor thermal dynamics subject to wide variations in line current and ambient weather conditions.

An efficient multi-objective design method with Particle Swarm Optimization (PSO) is developed for Surface Mount Permanent Magnet machines to reduce the complexity in the PMSM machine design. First an analytical model of the PMSM machine’s geometry is developed and results are verified by finite element analysis. With proper design specification and assumption, the design input variables in this model can be reduced to as low as two, which significantly simplifies the optimization process. PSO is then applied to this analytical model. Compared to the traditional machine design methods, this proposed algorithm finds the optimized solution with fast computation and high convergence.

This paper describes a single phase switched rectifier for current control using model reference adaptive control (MRAC) with a continually on-line trained artificial neural network (COT-ANN). The results obtained with the proposed scheme are similar to the ones obtained in a previous work but using a simpler control structure. Simulations are used to test the validity of the proposed algorithm and the results are later verified by a practical implementation of this system.

This paper deals with modern control systems technology that is frequently applied to power conversion systems. The discussion goes far beyond the basic level of switch control in switching regulators. System-level control issues are important in expanding the market base of power electronics. Improvement in system performance involves not only the use of advanced control techniques, but also the integration of several converters or converter systems into a larger system. A fully controlled rectifier and an induction motor drive system are presented as typical applications to illustrate the use of many techniques for controlling power converters. The paper then points out how a wide variety of control techniques can be applied to enhance the controller performance and bandwidth in power electronics. These techniques include observers and adaptive control, nonlinear control, sliding and dead-beat control, and intelligent control. Finally, the paper points out how power electronic system performance can be enhanced through the use of condition monitoring and diagnostics.