Review of Power Quality Issues in Solar and Wind Energy
TL;DR: In this article, a review shows what else the issues are caused due to the solar and wind energy while connected to grid and how it can be improved, controllers, grids, power quality enhancement devices, power converters.
About: This article is published in Materials Today: Proceedings.The article was published on 2020-01-01. It has received 18 citations till now. The article focuses on the topics: Wind power & Renewable energy.
Citations
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TL;DR: In this article , a single-phase 7-level AMLI with an intelligent algorithm is proposed for renewable energy applications, which uses a single MOSFET switch with less switching stress and a single DC source.
Abstract: A super-lift mechanism has made tremendous progress in DC/DC conversion technology. In comparison to the asymmetrical form of MLI, the novel Asymmetric Multilevel Inverter (AMLI) technology proposes a minimized number of components. The Fuzzy-PI (Proportional integral) and Modified Genetic Algorithm (MGA) utilizes to minimize the harmonic content considerably using a variety of modulation index and firing angle values in open-loop and closed-loop control. This architecture for designing single-phase 7-level AMLI with an intelligent algorithm proposed for Renewable Energy (RE) applications. This circuit uses a single MOSFET switch with less switching stress and a single DC source. The effectiveness of the proposed MGA optimization eliminates the lower-order harmonics. MGA and Fuzzy-PI based Distributed Power Flow Intelligent Control (DPFIC) algorithms are applied with multilevel structures while maintaining the fundamental frequency for both MATLAB platform and hardware implementation. During this analysis, the losses is also find to investigate the influence of modulation index and output power factor on inverter efficiency. Simulations and experimental findings confirm the proposed inverter capacity to create high-quality multilayer output voltage. However, the proposed closed loop simulation circuit gives 0.47% minimum THD level, and 10.4% in experimental results.
34 citations
TL;DR: In this article, the authors present the recent progress of AI-enabled hybrid approaches for wind power forecasting emphasizing classification, structure, strength, weakness and performance analysis, and explore the various influential factors toward the implementations of AIbased hybrid wind power forecast including data preprocessing, feature selection, hyperparameters adjustment, training algorithm, activation functions and evaluation process.
Abstract: Globally, wind energy is growing rapidly and has received huge consideration to fulfill global energy requirements. An accurate wind power forecasting is crucial to achieve a stable and reliable operation of the power grid. However, the unpredictability and stochastic characteristics of wind power affect the grid planning and operation adversely. To address these concerns, a substantial amount of research has been carried out to introduce an efficient wind power forecasting approach. Artificial Intelligence (AI) approaches have demonstrated high precision, better generalization performance and improved learning capability, thus can be ideal to handle unstable, inflexible and intermittent wind power. Recently, AI-based hybrid approaches have become popular due to their high precision, strong adaptability and improved performance. Thus, the goal of this review paper is to present the recent progress of AI-enabled hybrid approaches for wind power forecasting emphasizing classification, structure, strength, weakness and performance analysis. Moreover, this review explores the various influential factors toward the implementations of AI-based hybrid wind power forecasting including data preprocessing, feature selection, hyperparameters adjustment, training algorithm, activation functions and evaluation process. Besides, various key issues, challenges and difficulties are discussed to identify the existing limitations and research gaps. Finally, the review delivers a few selective future proposals that would be valuable to the industrialists and researchers to develop an advanced AI-based hybrid approach for accurate wind power forecasting toward sustainable grid operation.
21 citations
TL;DR: A general review of the controllers used for photovoltaic systems is presented, based on the most recent papers presented in the literature, and the main contribution is the synthesis of a generalized control structure and the identification of the latest trends.
Abstract: Complex control structures are required for the operation of photovoltaic electrical energy systems. In this paper, a general review of the controllers used for photovoltaic systems is presented. This review is based on the most recent papers presented in the literature. The control architectures considered are complex hybrid systems that combine classical and modern techniques, such as artificial intelligence and statistical models. The main contribution of this paper is the synthesis of a generalized control structure and the identification of the latest trends. The main findings are summarized in the development of increasingly robust controllers for operation with improved efficiency, power quality, stability, safety, and economics.
13 citations
TL;DR: In this article , an analysis of the most common faults that appear in wind and photovoltaic generation systems is presented, and the main techniques and strategies developed for the identification of such faults are discussed in order to address the advantages, drawbacks, and trends in the field of detection and classification of specific and combined faults.
Abstract: Renewable energy-based power generation technologies are becoming more and more popular since they represent alternative solutions to the recent economic and environmental problems that modern society is facing. In this sense, the most widely spread applications for renewable energy generation are the solar photovoltaic and wind generation. Once installed, typically outside, the wind generators and photovoltaic panels suffer the environmental effects due to the weather conditions in the geographical location where they are placed. This situation, along with the normal operation of the systems, cause failures in their components, and on some occasions such problems could be difficult to identify and hence to fix. Thus, there are generated energy production stops bringing as consequence economical losses for investors. Therefore, it is important to develop strategies, schemes, and techniques that allow to perform a proper identification of faults in systems that introduce renewable generation, keeping energy production. In this work, an analysis of the most common faults that appear in wind and photovoltaic generation systems is presented. Moreover, the main techniques and strategies developed for the identification of such faults are discussed in order to address the advantages, drawbacks, and trends in the field of detection and classification of specific and combined faults. Due to the role played by wind and photovoltaic generation, this work aims to serve as a guide to properly select a monitoring strategy for a more reliable and efficient power grid. Additionally, this work will propose some prospective with views toward the existing areas of opportunity, e.g., system improvements, lacks in the fault detection, and tendency techniques that could be useful in solving them.
12 citations
References
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TL;DR: In this article, a review of microgrid drivers, real-world applications, challenges, and future prospects is presented, along with a multi-disciplinary portrait of today's micro-grid drivers.
Abstract: Microgrids are now emerging from lab benches and pilot demonstration sites into commercial markets, driven by technological improvements, falling costs, a proven track record, and growing recognition of their benefits. They are being used to improve reliability and resilience of electrical grids, to manage the addition of distributed clean energy resources like wind and solar photovoltaic (PV) generation to reduce fossil fuel emissions, and to provide electricity in areas not served by centralized electrical infrastructure. This review article (1) explains what a microgrid is, and (2) provides a multi-disciplinary portrait of today's microgrid drivers, real-world applications, challenges, and future prospects.
884 citations
TL;DR: In this paper, the authors explore the capability of using vehicle-to-grid (V2G) electric vehicles (EVs) to join distribution system voltage management, and to collaborate with online load tap changing (OLTC) transformers, voltage regulators (VRs), or shunt capacitors.
Abstract: Distributed solar generation has the potential to reach high penetration levels in distribution systems. However, its integration reshapes distribution system power flows and causes rapid-fluctuations in system statuses. The facts challenge major voltage management approaches, nowadays, such as using online load tap changing (OLTC) transformers, voltage regulators (VRs), or shunt capacitors. In this paper, we explore the capability of using vehicle-to-grid (V2G) electric vehicles (EVs) to join distribution system voltage management, and to collaborate with OLTCs to mitigate the voltage problems caused by distribution solar generations. A two-stage control method is proposed for this purpose. The first stage controls the making of rolling schedules for EV charging and OLTC tap positions, while the second controls the EVs to resist the solar generation fluctuation to maintain voltage profiles. A case system with simultaneous overvoltage/undervoltage risks is designed to test the effectiveness of the proposed method. The results demonstrate that both the over/undervoltage risks are mitigated.
158 citations
TL;DR: A microcontroller-based battery charge controller with maximum power point tracker (MPPT) is designed for harvesting the maximum power available from the PV system under given insolation and temperature conditions.
Abstract: Solar cells convert sun light into electricity, but have the major drawbacks of high initial cost, low photo-conversion efficiency and intermittency. The current-voltage characteristics of the solar cells depend on solar insolation level and temperature, which lead to the variation of the maximum power point (MPP). Herein, to improve photovoltaic (PV) system efficiency, and increase the lifetime of the battery, a microcontroller-based battery charge controller with maximum power point tracker (MPPT) is designed for harvesting the maximum power available from the PV system under given insolation and temperature conditions. Among different MPPT techniques, perturb and observe (P&O) technique gives excellent results and thus is used. This work involves the design of MPPT charge controller using DC/DC buck converter and microcontroller. A prototype MPPT charge controller is tested with a 200 W PV panel and lead acid battery. The results show that the designed MPPT controller improves the efficiency of the PV panel when compared to conventional charge controllers.
104 citations
TL;DR: In this paper, the authors demonstrate that a superconductive magnetic energy storage (SMES) system can enhance large-scale utilization of photovoltaic (PV) generation.
Abstract: The authors demonstrate that a superconductive magnetic energy storage (SMES) system can enhance large-scale utilization of photovoltaic (PV) generation. Results show that power output from a SMES system can be used to smooth out PV power fluctuations so that the combined PV/SMES output is dispatchable and free from fluctuations. Power generated from PV arrays is shown to be fully utilized under different weather conditions, and PV penetration is increased to significant levels without adversely affecting the power system. Coupled with PV generation, a SMES system is even more effective in performing diurnal load leveling. A coordinated PV/SMES operation scheme is proposed, and its demonstration under different weather conditions is discussed. >
48 citations
03 Apr 2014
TL;DR: In this article, the performance evaluation of "Perturba Observe" and "Incremental Conductance" algorithms as the most commonly utilized two maximum power point tracking (MPPT) techniques for photovoltaic systems is presented.
Abstract: This paper mainly focuses on the performance evaluation of "Perturba Observe" and "Incremental Conductance" algorithms as the most commonly utilized two Maximum Power Point Tracking (MPPT) techniques for photovoltaic systems. Matlab/SIMULINK platform is used to model and simulate the entire system. The simulation model of a PV module is constructed based on the one-diode mathematical model of a solar cell and the model is validated using the manufacturer's datasheet parameters for a commercially available PV module. A boost type DC/DC converter topology is utilized and modeled and simulation models for "PaO" and "IncCond" algorithms are constructed. According to the results, both of the algorithms have shown almost similar performances under identical test conditions. Despite its relatively high complexity, the IncCond algorithm has been slightly more efficient and has reached to the MPP in a shorter time period, while most probably the simple structure of the PaO algorithm has caused it to be the most preferred MPPT algorithm. The paper provides reliable information on the performance and characteristics of the mentioned two MPPT techniques which can be used by system designers to improve the overall efficiency and reduce the cost of PV system applications.
34 citations