scholarly journals Voltage Quality and Power Factor Improvement in Smart Grids Using Controlled DG Units

Energies ◽  
2019 ◽  
Vol 12 (18) ◽  
pp. 3433 ◽  
Author(s):  
Ibrahim Ahmad ◽  
Ghaeth Fandi ◽  
Zdenek Muller ◽  
Josef Tlusty

The increased penetration of renewable energy sources in the electrical grid, due to the rapid increase of power demand and the need of diverse energy sources, has made distributed generation (DG) units an essential part of the modern electrical grid. The integration of many DG units in smart grids requires control and coordination between them, and the grid to maximize the benefits of the DG units. Smart grids and modern electronic devices require high standards of power quality, especially voltage quality. In this paper, a new methodology is presented to improve the voltage quality and power factor in smart grids. This method depends on using voltage variation and admittance values as inputs of a controller that controls the reactive power generation in all DG units. The results show that the controller is efficient in improving the voltage quality and power factor. Real data from an electrical network have been used in the simulation model in MATLAB Simulink to test the new approach.

Author(s):  
Affiq A. Ghani ◽  
Vigna K. Ramachandaramurthy ◽  
Jia Ying Yong

AbstractThe power factor of industrial facilities is typically inductive. The case study in this paper was based on a typical Malaysian 11-kV on-grid industrial system with renewable energy sources and electric vehicle charging station connected. The integration of renewable energy sources reduces energy consumption from the grid; it consecutively reduces greenhouse gas emissions. However, the integration of renewable energy sources such as solar photovoltaic operating at unity power factor results in a reduction of the industry’s power factor. According to the Malaysian Distribution Code, the power factor of a medium voltage industrial system should be more than 0.85 lagging. A long-term low power factor will reduce the related electrical equipment lifespan and increase the monthly electricity bills. A classic method to overcome this issue was by installing reactive power compensator devices, such as the synchronous condenser, static VAr compensator and static synchronous compensator. Studies had revealed that solar photovoltaic with appropriate control system design could perform short-term reactive power compensation. The control techniques used are either power factor control, active power control, reactive power control or any combination of them. However, neither the reactive power compensator devices nor the solar photovoltaic with a control system can regulate the industry’s power factor to an intended value throughout its operation. Thus, this paper presents a simple, relatively cost-effective design of a master power factor controller that is capable of regulating the industry’s power factor to an intended value throughout its operation with a single preset reference. In this research, an industry-grade system comprises an industrial load installed with a power factor-controlled capacitor bank, a power factor-controlled solar photovoltaic system, a bidirectional current-controlled electric vehicle charging system based on CHAdeMO 1.1 standard charging protocol and a master power factor controller was designed using the Matrix Laboratory/Simulink software. This paper has provided simulation results as proof that each of the designed equipment was functioning appropriately. The results also proved that the proposed master power factor controller was capable of regulating the power factor of the industrial system to above 0.85 lagging throughout its operation.


2019 ◽  
Vol 287 ◽  
pp. 08003
Author(s):  
Andrey Mirev ◽  
Yovko Rakanov ◽  
Juliana Javorova ◽  
Anton Andonov

By outlying renewable energy sources, the reactive electric power of local consumers at the same area must be carried by the grid. This loads and causes losses in the same grid. This can be avoided if the necessary reactive power is generated on the spot by the inverter. For that purpose is proposed and investigated a new modified topology for operating with variable power factor. Features of this topology are: transformerless connection to single-phase grid, symmetrical operation in both half waves and the presence of flying inductor, which eliminate the necessity from a separate boost converter, if the input voltage is smaller than the grid peak voltage. The simulation analysis is done on the model elaborated on the SIMETRIX software environment. The results show that the suggested topology can operate with variable power factor and has many additional advantages.


2021 ◽  
pp. 0309524X2110241
Author(s):  
Nindra Sekhar ◽  
Natarajan Kumaresan

To overcome the difficulties of extending the main power grid to isolated locations, this paper proposes the local installation of a combination of three renewable energy sources, namely, a wind driven DFIG, a solar PV unit, a biogas driven squirrel-cage induction generator (SCIG), and an energy storage battery system. In this configuration one bi-directional SPWM inverter at the rotor side of the DFIG controls the voltage and frequency, to maintain them constant on its stator side, which feeds the load. The PV-battery also supplies the load, through another inverter and a hysteresis controller. Appropriately adding a capacitor bank and a DSTATCOM has also been considered, to share the reactive power requirement of the system. Performance of various modes of operation of this coordinated scheme has been studied through simulation. All the results and relevant waveforms are presented and discussed to validate the successful working of the proposed system.


Author(s):  
Chethan Parthasarathy ◽  
Hossein Hafezi ◽  
Hannu Laaksonen

AbstractLithium-ion battery energy storage systems (Li-ion BESS), due to their capability in providing both active and reactive power services, act as a bridging technology for efficient implementation of active network management (ANM) schemes for land-based grid applications. Due to higher integration of intermittent renewable energy sources in the distribution system, transient instability may induce power quality issues, mainly in terms of voltage fluctuations. In such situations, ANM schemes in the power network are a possible solution to maintain operation limits defined by grid codes. However, to implement ANM schemes effectively, integration and control of highly flexible Li-ion BESS play an important role, considering their performance characteristics and economics. Hence, in this paper, an energy management system (EMS) has been developed for implementing the ANM scheme, particularly focusing on the integration design of Li-ion BESS and the controllers managing them. Developed ANM scheme has been utilized to mitigate MV network issues (i.e. voltage stability and adherence to reactive power window). The efficiency of Li-ion BESS integration methodology, performance of the EMS controllers to implement ANM scheme and the effect of such ANM schemes on integration of Li-ion BESS, i.e. control of its grid-side converter (considering operation states and characteristics of the Li-ion BESS) and their coordination with the grid side controllers have been validated by means of simulation studies in the Sundom smart grid network, Vaasa, Finland.


Cybersecurity ◽  
2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Raphael Anaadumba ◽  
Qi Liu ◽  
Bockarie Daniel Marah ◽  
Francis Mawuli Nakoty ◽  
Xiaodong Liu ◽  
...  

AbstractEnergy forecasting using Renewable energy sources (RESs) is gradually gaining weight in the research field due to the benefits it presents to the modern-day environment. Not only does energy forecasting using renewable energy sources help mitigate the greenhouse effect, it also helps to conserve energy for future use. Over the years, several methods for energy forecasting have been proposed, all of which were more concerned with the accuracy of the prediction models with little or no considerations to the operating environment. This research, however, proposes the uses of Deep Neural Network (DNN) for energy forecasting on mobile devices at the edge of the network. This ensures low latency and communication overhead for all energy forecasting operations since they are carried out at the network periphery. Nevertheless, the cloud would be used as a support for the mobile devices by providing permanent storage for the locally generated data and a platform for offloading resource-intensive computations that exceed the capabilities of the local mobile devices as well as security for them. Electrical network topology was proposed which allows seamless incorporation of multiple RESs into the distributed renewable energy source (D-RES) network. Moreover, a novel grid control algorithm that uses the forecasting model to administer a well-coordinated and effective control for renewable energy sources (RESs) in the electrical network is designed. The electrical network was simulated with two RESs and a DNN model was used to create a forecasting model for the simulated network. The model was trained using a dataset from a solar power generation company in Belgium (elis) and was experimented with a different number of layers to determine the optimum architecture for performing the forecasting operations. The performance of each architecture was evaluated using the mean square error (MSE) and the r-square.


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