Data-driven next-generation smart grid towards sustainable energy evolution: techniques and technology review

Meteorological changes urge engineering communities to look for sustainable and clean energy technologies to keep the environment safe by reducing CO2 emissions. The structure of these technologies relies on the deep integration of advanced data-driven techniques which can ensure efcient energy generation, transmission, and distribution. After conducting thorough research for more than a decade, the concept of the smart grid (SG) has emerged, and its practice around the world paves the ways for efcient use of reliable energy technology. However, many developing features evoke keen interest and their improvements can be regarded as the next-generation smart grid (NGSG). Also, to deal with the non-linearity and uncertainty, the emergence of data-driven NGSG technology can become a great initiative to reduce the diverse impact of non-linearity. This paper exhibits the conceptual framework of NGSG by enabling some intelligent technical features to ensure its reliable operation, including intelligent control, agent-based energy conversion, edge computing for energy management, internet of things (IoT) enabled inverter, agent-oriented demand side management, etc. Also, a study on the development of data-driven NGSG is discussed to facilitate the use of emerging data-driven techniques (DDTs) for the sustainable operation of the SG. The prospects of DDTs in the NGSG and their adaptation challenges in real-time are also explored in this paper from various points of view including engineering, technology, et al. Finally, the trends of DDTs towards securing sustainable and clean energy evolution from the NGSG technology in order to keep the environment safe is also studied, while some major future issues are highlighted. This paper can ofer extended support for engineers and researchers in the context of data-driven technology and the SG.     

Application of energy capacitor system to wind power generation

In this paper, it is reported that energy capacitor system (ECS), which combines power electronic devices and electric double‐layer capacitor, can significantly decrease voltage and power fluctuations of grid‐connected fixed‐speed wind generator. The proper selection of wind farm output power reference is still a problem for smoothing the wind farm output power. This paper proposes exponential moving average to generate the reference output power of a grid‐connected wind farm. The objective of the control system is to follow the line power reference by absorbing or providing real power to or from the ECS. Moreover, the necessary reactive power can also be supplied to keep the wind farm terminal voltage at the desired reference level. Real wind speed data were used in the simulation analyses, which validate the effectiveness of the proposed control strategy. Simulation results clearly show that our proposed ECS can be suitable for wind power application. Copyright © 2007 John Wiley & Sons, Ltd.     

Electrolyzer switching strategy for hydrogen generation from variable speed wind generator

This paper presents a new switching strategy for electrolyzer used in hydrogen generation which is connected to the terminal of a wind farm. The output of wind generator, in general, fluctuates greatly due to the random wind speed variations, which has a serious influence on the power system operation. In this study, the wind farm is composed of variable speed wind turbines (VSWT) driving permanent magnet synchronous generators (PMSG). The hydrogen generator (HG) is composed of rectifier and 10 electrolyzer units where each unit is controlled by the chopper circuit. To smoothen the wind farm line power, at first, a reference for the line power is generated from the difference of exponential moving average of wind farm output and its standard deviation. Then the switching strategy is developed in such a way that the proposed cooperative system can smoothen the wind farm line power fluctuation as well as generating hydrogen gas absorbing the fluctuating portion of wind farm output that lies above the reference line power. This novel switching strategy helps each electrolyzer unit working in full load and shift operation conditions and hence increases its lifespan and efficiency. The performance of the proposed system is investigated by simulation analyses, in which simulations are performed by using PSCAD/EMTDC.     

Design and Validation of a Generalized Multilevel Inverter with Simplified Switching Technique

Abstract—

This paper proposes a generalized 3-phase cascaded multilevel inverter (CMLI) along with a simplified space vector pulse width modulation (SVPWM) based on 2-level inverter (2LI) topology. While conventional cascaded H-bridge inverters (CHBIs) call for a number of DC sources which increase the cost and complexity of their implementation, the proposed CMLI requires one DC source only. On the other hand, the complexity of SVPWM lies in the switching diagram that consists of a large number of triangles comprising uneven numbers of switching vectors. The generalized 3-phase CMLI proposed in this paper is aimed at reducing the number of switching vectors of each triangle. The hypothesis of the proposed CMLI-SVPWM is firstly illustrated through extensive simulation analysis using MATLAB/SIMULINK software. Feasibility of the proposed inverter is then validated through experimental measurements on a hardware prototype. Results reveal the superiority of the proposed inverter over existing ones in terms of the quality of the output voltage and current waveforms and the overall efficiency.     

Speed control of grid-connected switched reluctance generator driven by variable speed wind turbine using adaptive neural network controller

In wind energy conversion system, variable speed operation is becoming popular nowadays, where conventional synchronous generators, permanent magnet synchronous generators, and doubly fed induction generators are commercially used as wind generators. Along with the existing and classical solutions of the aforementioned machines used in wind power applications, the switched reluctance generator (SRG) can also be considered as a wind generator due to its inherent characteristics such as simple construction, robustness, low manufacturing cost, etc. This paper presents a novel speed control of switched reluctance generator by using adaptive neural network (ANN) controller. The SRG is driven by variable speed wind turbine and it is connected to the grid through an asymmetric half bridge converter, DC-link, and DC-AC inverter system. Speed control is very important for variable speed operation of SRG to ensure maximum power delivery to the grid for any particular wind speed. Detailed modeling and control strategies of SRG as well as other individual components including wind turbine, converter, and inverter systems are presented. The effectiveness of the proposed system is verified with simulation results using the real wind speed data measured at Hokkaido Island, Japan. The dynamic simulation study is carried out using PSCAD/EMTDC.     

Application of STATCOM/BESS for wind power smoothening and hydrogen generation

This paper proposes static synchronous compensator (STATCOM) incorporated with battery energy storage system (STATCOM/BESS) to smooth the line power of wind farm consists of fixed-speed wind generators. Constant output power reference is not a good choice because there may be some cases where wind speed is very low and then sufficient power cannot be obtained. In that case, energy storage device can solve the problem but large energy capacity may be needed. This paper proposes exponential moving average (EMA) to generate the reference output power, and thus the energy capacity of BESS unit can be small. Another salient feature of this study is the generation of hydrogen by using wind energy. At the wind farm terminal, two topologies of hydrogen generators are considered to be connected and their merits and demerits are analyzed. Finally, by taking the advantage of STATCOM/BESS, simple hydrogen generator topology composed of rectifier and electrolyzer is proposed. Detailed modeling and control strategy of hydrogen generator and STATCOM/BESS topologies are discussed and a cooperative control is developed. The effectiveness of the proposed system is verified by the simulation analysis using PSCAD/EMTDC.     

Particle Swarm Optimization-based Superconducting Magnetic Energy Storage for Low-voltage Ride-through Capability Enhancement in Wind Energy Conversion System

Abstract— This article presents a novel application of the particle swarm optimization technique to optimally design all the proportional–integral controllers required to control both the real and reactive powers of the superconducting magnetic energy storage unit for enhancing the low-voltage ride-through capability of a grid-connected wind farm. The control strategy of the superconducting magnetic energy storage system is based on a sinusoidal pulse-width modulation voltage source converter and proportional–integral-controlled DC-DC converter. Control of the voltage source converter depends on the cascaded proportional–integral control scheme. All proportional–integral controllers in the superconducting magnetic energy storage system are optimally designed by the particle swarm optimization technique. The statistical response surface methodology is used to build the mathematical model of the voltage responses at the point of common coupling in terms of the proportional–integral controller parameters. The effectiveness of the proportional–integral-controlled superconducting magnetic energy storage optimized by the proposed particle swarm optimization technique is then compared to that optimized by a genetic algorithm technique, taking into consideration symmetrical and unsymmetrical fault conditions. A two-mass drive train model is used for the wind turbine generator system because of its large influence on the fault analyses. The systemic design approach is demonstrated in determining the controller parameters of the superconducting magnetic energy storage unit, and its effectiveness is validated in augmenting the low-voltage ride-through of a grid-connected wind farm.     

Comparative study on transient stability analysis of wind turbine generator system using different drive train models

A huge number of wind generators are going to be connected with the existing network in the near future. Therefore it is necessary to analyse the transient stability of power systems, including wind turbine generator systems (WTGS). It has already been reported that one-mass or lumped model of wind turbine system is insufficient to analyse the transient behaviour of WTGS. It has also been reported that for the precise transient analysis of WTGS, a six-mass drive train model is needed. The reduced order models (three-mass and two-mass) have also been adopted so far for transient behaviour analysis. But the transient stability analysis of using six-mass, three-mass and two-mass drive train models has not been reported sufficiently so far in the literature. The authors have conducted an analysis using these methods. First, a detailed transformation procedure is presented from six-mass drive train model to two-mass model, which can be used in the analysis of transient stability simulation with sufficient accuracy. It is then determined which drive train model is appropriate for transient stability analysis of grid-connected WTGS. The effects of drive train parameters (such as inertia constant, spring constant and damping constant) on stability are examined using the above mentioned types of drive train models. Moreover, different types of symmetrical and asymmetrical faults at different wind generator power levels are considered in the simulation analyses with and without considering damping constants in six-mass, three-mass and two-mass shaft models. Considering the simulation results, it can be concluded that two-mass shaft model is sufficient for the transient stability analysis of WTGS.