Volume 18, Issue 3 -

Nowadays the contribution of smart load technologies to power system frequency regulation is spurred due to the increasing penetration of renewable energy resources. This paper presents a comprehensive and up-to-date critical review on different decentralized load control strategies. This includes a joint literature- as well as simulation-based investigation in order to scrutinize different decentralized frequency-based load modulation strategies through organizing a taxonomy table and performing different simulation scenarios. Furthermore, the effectiveness of different gain tuning procedures in each control action are scrutinized and compared in terms of frequency nadir and steady state error. The detailed simulation is performed using SimPowerSystem (SPS) toolbox, in phasor mode, on IEEE 39-bus New England test system.

Today, electric power and energy measurements are widely required, practically in all the research, industrial and consumer applications. Power measurements are of importance primarily for the test, monitoring and maintenance of energy supply networks and electric equipment. The measurement of both electric power and energy is a still open research problem in the electrical engineering community. Phenomena like harmonic distortion, noise, transients, over-voltages and voltage dips have increased the difficulty in achieving accurate measurements, compared with the case of sinusoidal signals. Many of the non-active power component definitions that have been proposed cannot be implemented in the traditional electro-mechanical or solid-state meters, but require the adoption of more expensive and time-consuming digital techniques; recently, some new approaches for the definition of power quantities have been investigated. In this paper, a survey of the classical and innovative definitions is proposed, with the aim of summarize the different points of view outlined by the researchers. A case study of power factor correction in nonsinusoidal conditions is also presented, to give a numerical comparison about the power quantities measured according to the various approaches.

Majority of the power plants in the world is based on coal. Pulverized coal is used to generate pressurized steam to drive turbines where-by chemical energy is converted to electrical energy. Modeling of the steam generator in thermal power plant plays a major role as it comprises of interactive units like economizer, drum and super-heater. Experiments across different units of the power plant are carried out to build correlations between input and output. Main objective of the work is to compare performances arising out by considering the system-model as three individual units or as one integrated boiler unit. In order to do this, multiple regression equations are derived based on quadratic models. The dependability of the pressure and temperature on the other variables are analyzed using the statistical analysis tool and validation of the derived model with the plant data is performed. Significance of regressions were evaluated based on ANOVA which in combination with standardized residuals distribution and their means for confidence levels of 95 and 99 %, helped in validating the model. Operating parameters are optimized using RSM supported by design of experiments with Box-Behnken design. These models will be helpful in understanding and designing the safe operation and control of thermal power plants.

The Doubly Fed Induction Generator DFIG wind turbines are the most chosen for the grid connection thanks to its dynamic, but the disconnection of these wind turbines during line fault to protect its converters don’t conform the new grid codes which prohibit disconnection of wind turbine during line fault, and recommend them to contribute in grid stability. This paper proposes a new model of DFIG wind turbine connection between them, where the number of converters in grid side is reduced and the connection of wind turbines in parallel to the grid is transformed to series-parallel connection, the aim of this new model of connection are to reduce the converters number in the grid side, limit current transient in converters, double the voltage, and reduce the investment cost. The total power generated by the farm before this new connection will be kept unchanged thanks to the installed switch in the model, a fuzzy logic program is developed to control switches.

Because of nonlinear I-V curves of photovoltaic panels, a maximum power point tracking (MPPT) technique is necessary to absorb maximum power. In this article state-space averaging method is utilized to express behavior of boost chopper converter. To generate the best operating point (PV panel desired voltage), incremental conductance is used. A Robust feedback linearization controller is proposed to deliver the PV panel to maximum power point. The controller is robust to environment variations, load uncertainties and load voltage disturbances. Stability of proposed controller is proved based on Lyapunov theorem. A boost chopper is used between PV panel and load to realize proposed MPPT technique. Boost chopper parameters are designed properly to operate converter in continues conduction mode (CCM). To evaluate MPPT technique some simulations in irradiance variation, temperature variation, load variation and load voltage disturbance are presented and discussed.

This paper presents an active power control of SPV (Solar Photovoltaic) grid tied system with the DSTATCOM (Distribution Static Compensator) capabilities using recursive least square (RLS) control algorithm with IC (Incremental Conductance) maximum power point tracking. The system serves dual purpose of working as a SPV-DSTATCOM and DSTATCOM in presence and absence of solar power, respectively. The SPV-DSTACOM provides compensating currents along with active current component thus fulfilling active power demand of connected load and feeds active power to the grid along with improving the power quality. Moreover, when the solar power is not available during night or low solar irradiation conditions, the system works as a DSTATCOM providing compensating current which improves the power quality of the system during load unbalance, harmonics and reactive power. A RLS based adaptive algorithm is used to do these functions at good convergence than conventional LMS (Least Mean Square) algorithm. Thus, the proposed system is capable to meet peak power demand when the solar energy is available and it improves the system power quality during day and night. The system responses under varying conditions is demonstrated on s developed prototype.

In the power supply system of high speed railway, the generated harmonics can not only influence the electric energy quality of power system, occur the voltage fluctuation and flicker, and affect the service life of traction equipment and traction transformer of electric power substation, but also cause the secondary protection misoperation of automatic control system, and affect the normal operation of the train. With the increase of overhead contact line transmission, the generated harmonics increased the communication interference. Therefore, on the basis of analyzing the generation and spectrum of harmonics in power system, an improved S transform method is introduced in order to propose a harmonic measurement and analysis method based on improved S transform for power supply system of high speed railway in this paper. The proposed method can effectively realize the harmonic measurement and analysis of power supply system. In order to testify the effectiveness of the proposed harmonic measurement and analysis method, Yingkou substation of Harbin-Dalian high speed railway is selected in here. The actual analysis calculation and experiment results show that the proposed method can effectively measure and analyze the harmonic in the power supply system of high speed railway. It provides a theoretical basis for solving the practical engineering problem of power supply.

Electric Vehicles (EV) can be connected to the grid for power transaction and also serve as distributed resource (DR) or distributed energy storage system (DESS). The concept of connecting group of EVs or gridable EVs (GEV) to the grid is called Vehicle-to-Grid (V2G). V2G is a prominent energy storage system as it is flexible and can be used to support the grid requirements in order to meet the time varying load demand. Optimal placement of GEV aggregation in power distribution network is very challenging and helps in maintaining stability of the power system for a shorter duration of time. In this paper, algorithm is developed for estimating parameters like P loss , Q loss , V pu based on past history and wireless access support for Control and Monitoring Unit (CMU) to aggregator agent communication is proposed using Long Term Evolution (LTE) protocol. The load flow studies are carried using MiPOWER software in order to obtain the optimal location for the placement of GEV aggregation in power distribution network. LTE physical layer is modeled using MATLAB/SIMULINK and the performance is analyzed using bit error rate (BER) v/s signal to noise ratio (SNR) curves.

A steady usage growth of various smart meters/sensors types comes along with the development of Smart Grid. Due to that smart meters/sensors usually produce data continuously, the state-of-the-art storage architecture will no longer be sustainable under such a dramatic data increase circumstance. It is crucial that these data shall be stored for both short and long term analysis to seek valuable information. This paper proposed a scalable and distributed storage architecture for time series data, and further substantiated the proposed storage framework on a proof-of-concept testbed using a cluster of low-cost and credit-card-sized single-board computers. We evaluated the proposed distributed storage framework and proof-of-concept testbed with a comprehensive set of performance measures. Results showed that low-cost hardware and open source technologies could be utilized for large-scale time series data storage.

State estimation is an integral component of energy management systems used for the monitoring and control of operation of transmission networks worldwide. However, it has so far not yet been widely adopted in the distribution networks due to their passive nature with no active generation. But this scenario is challenged by the integration of distributed generators (DGs) at this level. Various static and dynamic state estimators have been researched for the transmission systems. These cannot be directly applied to the distribution systems due to their different philosophy of operation. Thus the performance of these estimators need to be re-evaluated for the distribution systems. This paper presents a computational and statistical performance of famous static estimator such as weighted least squares (WLS) and dynamic state estimators such as extended Kalman filter (EKF) and unscented Kalman filter (UKF) for electric distribution system. Additionally, an improved-UKF (IUKF) is also proposed which enhances the robustness and numerical stability of the existing UKF algorithm. All the estimators are tested for load variation and bad data for IEEE-30, 33 and 69 bus radial distribution networks using statistical performance metrics such as Maximum Absolute Deviation (MAD), Maximum Absolute Percent Error (MAPE), Root Mean Square Error (RMSE) and Overall Performance index (J). Based on these metrics, IUKF outperforms other estimators under the simulated noisy measurement conditions.

This paper investigates a frequency selection method of triple frequency in earth capacitance measurement. Based on the researches about the triple frequency method, the measurement principle of the proposed method is presented in detail. In this paper, the accurate earth capacitance in the distribution network can be calculated by establishing corresponding equations with injecting three different frequencies of current signals to the triangle open-side of voltage transformer (VT). Furthermore, the influences of selected frequency on the calculated results of the capacitive current are further analyzed. In order to improve the measurement accuracy, the initial selected frequencies of injected zero-sequence current signal should be set small as the larger earth capacitance in the distributed network is more common. Then the value of selected frequency should be increased correspondingly with the small capacitance in the distribution network. Finally, the correctness of theoretical analysis and feasibility of frequency selection method are verified with the simulation and experimental results of the earth capacitance measurement in distribution network.

This paper presents a real time price based energy management system for DC microgrid. The DC distribution system is considered as a prospective system according to the increase of DC loads and DC output type distribution energy resources (DERs) such as photovoltaic (PV) systems, battery bank (BB), and hybrid car (HC). The control objective is to achieve the optimal cost of energy. The proposed control scheme is developed based on the source as well as load scheduling of the DC microgrid. The source scheduling algorithm is based on the selection of cheapest power source to supply the load of DC microgrid and achieve the optimal electricity price. The BB and HC charges in regular hours at the less electricity price to supply the future load during the higher electricity price of the public utility. The load scheduling algorithm shifts the deferrable load of the building from peak hours to the regular hours to obtain the lowest cost of energy for the building. The proposed scheme significantly decreases the peak demand, which is the main cause of load shedding. Dynamic simulation is presented to access the control performance with price fluctuations and robustness of the system.