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Magnetizing inrush current will occur when the transformer is energized without load, which will cause that the already energized neighboring transformers generate sympathetic inrush current. The currents have influence on the operation of HVDC system if they occur in the converter transformers due to their characteristics. In this paper, the inrush current generating mechanism is discussed firstly. Then the model of HVDC system is constructed in PSCAD/EMTDC based on the planned Shanxi-Jiangsu HVDC transmission system. After that, a process simulation, where one pole of HVDC system is in operation while the other pole's transformers are put into operation, is carried out. In this process, this paper studies the influence of fairly large inrush current on the operation of HVDC system. The simulation result shows that the inrush current and sympathetic inrush during energization of the converter transformers cause the fluctuation of operation of HVDC system.

The dimension of the power systems model may easily reach the order of thousands of state variable in applications such as dynamic simulation, control, etc. So the model reduction is a very important topic in power community. The cost and complication of the controller increases as the system order goes high. This problem can be overcome if a good reduced-order model is available for the original higher-order system and if it is possible to design a controller using a lower-order model, which will stabilize the original higher-order system when placed in the closed loop. The linear quadratic Gaussian/Loop transfer Recovery (LQG/LTR) controller is a robust and stable control which is a systematic method with a view of engineering. In the present work, based on modified particle swarm optimization (MPSO), a simple method for finding reduced order models for multi input multi output (MIMO) large scale systems is investigated. Depended on the linear reducing equations design a robust controller using LQG/LTR technique for the system. The main feature of the proposed technique is that it is applicable to all systems and not limited to only stable or strictly proper systems. Therefore, it is most suitable for power systems. LQG/LTR guarantees both good robustness and performance.

Renewable energy is one of the most important sources used for the production of electrical energy due to its natural availability and lack of harmful effects on the environment. From these sources, wind energy is often located in remote areas where exposure to disturbance sometimes affects its functioning. This paper consists of two parts. In the first, we propose a new Modified Bacterial Foraging-Particle Swarm Optimisation (MBF-PSO). This is improved by new inertia Weight (w new ), using mixed parameters of the PSO and BF to find a new formula for w new . In the second part, we present the influence of different sorts of disturbance on the performance of a Doubly-Fed Induction Generator (DFIG) driven by the Wind Turbine (WT) with variable speeds and connected to the grid. Three optimisation strategies are investigated here for tuning the PID controller of DFIG. Finally, the results of the proposed strategies show that the MBF-PSO strategy is most effective in the stabilisation and improves the quality of the power.

Assuming that all electric vehicles (EVs) integrated to the grid are managed by aggregators, it is possible to make full use of the controllability of the charging EVs. Based on this, the charging load of each EV aggregator is defined as one of the optimal scheduling variables in the unit commitment (UC) model. This can be accomplished by assessing the upper and lower limit of charging load of each EV aggregator in different scenarios, which is simulated by Monte Carlo method. According to this, a UC model is proposed for optimal coordination of EV aggregators and wind generation, considering the EV owner's requirement, the range of charging load and the unit constraints. Using the10-units system as the test system, the results of UC models with different EVs charging strategies and the wind power integration indicators such as utilization rate are investigated. Simulation results show that both the abandoned wind power and the unit operating costs can be decreased more effectively in the proposed UC model.

Nowadays, growing number of electric vehicles (EVs) can not only be controllable load to regulate power system, but also serve as distributed energy storage unit that can feedback to the grid by vehicle-to-grid (V2G). Therefore, ancillary services for the grid such as frequency regulation can potentially be provided by the use of EVs with scheduling capacity. However, the scheduling capacity is limited by factors such as the constraints of customers travel demand and the battery life. Based on this, a centralized control mode is applied for distributed EVs and a mathematical model with charging and discharging static frequency characteristics of aggregators is established, considering EVs scheduling capacity. According to this, load frequency control models both for single and two-area power systems are proposed. The simulation results show that using EVs scheduling capacity for frequency regulation can effectively help reducing the system frequency deviation and thus improving the electricity quality. Furthermore, the reserve capacity of traditional frequency regulation units can be decreased and especially power system economics has developed.

Since Hulunbuir-LiaoNing HVDC transmission project was put into operation, low amplitude subsynchronous oscillation had occurred frequently and exceedingly in Hulunbuir power plant, such problem was of serious concern to power plant and power system operators. This paper calculated the complex torque coefficients of the units in Hulunbuir power plant using complex torque coefficient method based on Complex Frequency Domain Port-equivalence Conductance Matrix (CPCM), analyzed the subsynchronous oscillation damping characteristics, built the simulation model of Hulunbuir AC-DC hybrid power system based on PSCAD/EMTDC, and verified the effectiveness of the analysis results using time-domain simulation method. Theoretical analysis and simulation results showed that the units' subsynchronous damping characteristics in Hulunbuir power plant were weak, therefore subsynchronous oscillation was easily stimulated by system disturbance but the convergence was weak. Analysis results can adequately explain why low amplitude subsynchronous oscillation had occurred frequently and exceedingly in Hulunbuir power plant.

With the extensive use of PMUs in power system, how to implement the optimal PMU placement for complete system observability is becoming more and more significant. Against simple genetic algorithm, easy to fall into local minima, this paper proposed a simple and effective adaptive genetic algorithm, aimed at determining the optimal placement of PMUs. The proposed algorithm provides adaptive crossover and mutation probability in iterations and has better convergence and global search ability than simple genetic algorithm, confirmed in many practical applications. Generally speaking, minimum PMU placement problem has multiple solutions, and this paper proposed an index of observability redundancy to rank these multiple solutions. Moreover, several observability rules were also put forward and proved with great help in obtaining the optimal solution. Simulations using MATLAB are conducted on IEEE 7 bus, 14 bus, 24 bus, 30 bus, 57 bus, 118 bus and New England 39 bus test systems in order to verify the validity of this adaptive method. Results compared with other existing methods show that the proposed adaptive method is simple to realize and obtains the optimal solution with high redundancy in very few generations, which is much more effective than the results by major existing algorithms and shows a good reference value.

An improved nonlinear control strategy is proposed in this paper. The main improvement made by the authors to the traditional nonlinear control which is based on the differential geometric theory is that an appropriate output function is selected to introduce a nonlinear transformation. Although, such transformation can only partially linearize the nonlinear system, it does provide a way to realize a multi-index control for high order nonlinear systems. Furthermore, with appropriate treatments for the remained part of the nonlinear system after partial linearization, satisfactory performance of the controller can be obtained. The proposed nonlinear control scheme was used to design a coordinated control for a TCSC and a hydro-turbine generator including the excitation and the governor. As the controlled system is a high order nonlinear system characterized with a non-minimum phase problem, design a coordinated control for such system is quite difficult by the conventional nonlinear control theory. Simulation results show very encouraging result. Both dynamic characteristics and the control accuracy of the controlled system are considerably improved.