• Energy Research

Abstract This paper examines dynamic operation and control strategies for a microgrid hybrid wind–PV (photovoltaic)–FC (fuel cell) based power supply system. The system consists of the PV power, wind power, FC power, SVC (static var compensator) and an intelligent power controller. A simulation model for this hybrid energy system was developed using MATLAB/Simulink. An SVC was used to supply reactive power and regulate the voltage of the hybrid system. A GRNN (General Regression Neural Network) with an Improved PSO (Particle Swarm Optimization) algorithm, which has a non-linear characteristic, was applied to analyze the performance of the PV generation system. A high-performance on-line training RBFNSM (radial basis function network-sliding mode) algorithm was designed to derive the optimal turbine speed to extract maximum power from the wind. To achieve a fast and stable response for real power control, the intelligent controller consists of an RBFNSM and a GRNN for MPPT (maximum power point tracking) control. As a result, the validity of this paper was demonstrated through simulation of proposed algorithm.

An application of plant growth simulation algorithm-enhanced honey-bee mating optimization is proposed to solve the fault section estimation problem in a power system. This approach is proposed because the local search capability of the honey-bee mating optimization is highly dependent on the parameter decisions. An inappropriate selection of parameters may affect the computation efficiency. This paper hence has added the plant growth simulation algorithm to enhance the honey-bee mating optimization so that the work of external parameter settings can be economized while the overall computation can be improved. In order to validate the effectiveness of this method, we have conducted the approach on practical power systems. Test results confirm the feasibility of this proposed method for the application considered.

This study proposes combining fuzzy inference system and support vector machine based voltage relays for voltage disturbance detection in micro-distribution systems (MDSs). Moreover, the coordination characteristic curves of the trigger time versus dynamic errors are proposed for under-voltage and over-voltage protection. Modified coordination characteristic curves use a critical trigger time to isolate the faults. An support vector machine (SVM) is a multi-layer decision-making model, which detects voltage disturbances, such as voltage swell, voltage sag, voltage unbalance, and faults. Computer simulations are conducted, using an IEEE 30-bus power system and micro-distribution systems, to show the effectiveness of the proposed voltage relays.

Abstract A hybrid power control system is proposed in the paper, consisting of solar power, wind power, and a diesel-engine. To achieve a fast and stable response for the real power control, an intelligent controller was proposed, which consists of the Wilcoxon (radial basis function network) RBFN and the improved (Elman neural network) ENN for (maximum power point tracking) MPPT. The pitch angle control of wind power uses improved ENN controller, and the output is fed to the wind turbine to achieve the MPPT. The solar array is integrated with an RBFN control algorithm to track the maximum power. MATLAB (MATrix LABoratory)/Simulink was used to build the dynamic model and simulate the solar and diesel-wind hybrid power system.

This paper endeavors to apply a novel intelligent damping controller (NIDC) for the static synchronous compensator (STATCOM) to reduce the power fluctuations, voltage support and damping in a hybrid power multi-system. In this paper, we discuss the integration of an offshore wind farm (OWF) and a seashore wave power farm (SWPF) via a high-voltage, alternating current (HVAC) electric power transmission line that connects the STATCOM and the 12-bus hybrid power multi-system. The hybrid multi-system consists of a battery energy storage system (BESS) and a micro-turbine generation (MTG). The proposed NIDC consists of a designed proportional–integral–derivative (PID) linear controller, an adaptive critic network and a proposed functional link-based novel recurrent fuzzy neural network (FLNRFNN). Test results show that the proposed controller can achieve better damping characteristics and effectively stabilize the network under unstable conditions.

A direct building algorithm for microgrid distribution ground fault (MGDGF) analysis is proposed in this paper. Four possibilities of the network topology changes were considered with the proposed iterative process for ground fault analysis. This paper also discusses the ground fault model of a battery energy storage system (BESS) as a distributed energy resource (DER), which can be used for both islanded and grid-connected modes. The proposed algorithm is robust and accurate. Test results demonstrate the potential of the proposed algorithm in MGDGF applications.

This paper endeavors to apply a hybrid bird-mating optimization approach to connection decisions of distribution transformers. It is expected that with the aid of hybrid bird-mating approach, the voltage imbalance and deviation can be mitigated, hence ensuring a satisfactory supplying power more effectively. To evaluate the effectiveness of this method, it has been tested through practical distribution systems with comparisons to other methods. Test results help confirm the feasibility of the approach, serving as beneficial references for the improvement of electric power grid operations.

A novel unsymmetrical faults analysis method with hybrid compensation for microgrid (MG) distribution systems is proposed. The method employs the actual three-phase models to handle unsymmetrical faults. Two matrices, which are built from the topological characteristics of MG distribution networks, and then combined with the proposed hybrid compensation method for injecting branch mismatch currents caused by the fault are used to analyze the branch mismatch currents and bus mismatch voltages directly. An unsymmetrical fault, with appropriate fault boundary conditions can be obtained. The proposed method can then be developed from these two matrices and be used to solve the various types of single or simultaneous unsymmetrical faults. This paper also discusses modeling of a microturbine generation (MTG) as a distributed generator (DG), which delivered for both islanded and grid-connected modes of operation. Test results show that the proposed method is efficient, accurate and easy to program for unsymmetrical faults analysis.

This letter presents a design for a novel voltage controller (NVC) which can exhibit three different reactions using the integration of a vanadium redox battery (VRB) with solar energy, and uses only electrochemical potentials with optimal external bias voltage control to carry out hydrogen production and the conversion of carbon dioxide (CO2) into methane and methanol. This NVC is simply constructed by using dynamic switch and control strategies with a time-variant control system. In this design, the interval voltage bias solutions obtained by the proposed NVC exhibit better voltage ranges and good agreement with the practical scenarios, which will bring significant benefits to operation for continuous reduction of CO2 into value-added clean fuels using the integration of a VRB with solar energy or any other renewable energy resource for future applications.