Novel control strategy for hybrid renewable energy-based standalone system

Sharma, Rahul; Suhag, Sathans

doi:10.3906/elk-1604-102

Cited by 13 publications

(9 citation statements)

References 20 publications

(20 reference statements)

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“…It is a technique that continues until the local minimum of the nonlinear function is found [17][18]. The LM algorithm, which gives the fastest and most reliable results in feed forward networks, has become a standard technique for nonlinear least squares problems [19][20].…”

Section: Artificial Neural Networkmentioning

confidence: 99%

Maximum wind speed forecasting using historical data and artificial neural networks modeling

Şen¹,

Özcan²

2021

International Journal of Energy Applications and Technologies

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Estimation of the wind speed makes a very important contribution to the seamless integration of wind power plants into the grid. In this way, the maximum amount of electricity can be generated by estimating the amount of energy that can be generated from wind energy. The measurements of the wind speed in the region, where the plant is plant to be established, made before the installation of the wind power plants (WPP), takes between 6 and 18 months. In this study, it was investigated what could be done to make a foresight and estimation about the wind speed in the future for the selected region. In order to accurately determine the wind speed, it was tried to be estimated by using artificial neural networks (ANN) included in the MATLAB package program. In this study, 365 data belonging to the previous years of the region to be studied were provided and used to train the ANN of the planned study. In practice, the parameters of temperature, humidity and pressure, which are among the factors affecting wind speed, were taken into consideration. An R value of 91.20% in the training phase, 93.04% in the validation phase and 92.76% in the test phase was obtained. High accuracy values were obtained at all phases and it was shown in this study that ANN can estimate reliably without memorizing.

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Section: Artificial Neural Networkmentioning

confidence: 99%

Maximum wind speed forecasting using historical data and artificial neural networks modeling

Şen¹,

Özcan²

2021

International Journal of Energy Applications and Technologies

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“…Further, considering the slow dynamic response of BESS, the author further proposes a closed-loop control that extracts the uncompensated error component from the BESS that additionally controls the SCSS duty cycle. Hence, increasing the controllability of DC-voltage regulation under load-generation mismatch conditions even without the need for dump loads [117], nevertheless, the BESS stress is further reduced. This proposed design has been further enhanced to give a PI-fuzzy-based PFS technique [118], for effective reduction of BESS stress and hence achieve faster DC voltage restoration.…”

Section: Demand-generation Power Flow Managementmentioning

confidence: 99%

A Review on the Selected Applications of Battery-Supercapacitor Hybrid Energy Storage Systems for Microgrids

Khalid

2019

Energies

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This paper presents a comprehensive categorical review of the recent advances and past research development of the hybrid storage paradigm over the last two decades. The main intent of the study is to provide an application-focused survey where every category and sub-category herein is thoroughly and independently investigated. Implementation of energy storage systems is one of the most interestingly effective options for further progression in the field of alternative energy technology. Apart from a meticulous garnering of the energy resources regulated by the energy storage, the main concern is to optimize the characteristic integrity of the storage devices to achieve a practically techno-economic size and operation. In this paper, hybrid energy storage consisting of batteries and supercapacitors is studied. The fact that the characteristic of batteries is mostly complementary to that of supercapacitors, hybridizing these storage systems enhances their scope of application in various fields. Therefore, the objective of this paper is to present an inclusive review of these applications. Specifically, the application domain includes: (1) regulation of renewable energy sources, (2) contributions to grid regulation (voltage and frequency compensation, contribution to power system inertia), (3) energy storage enhancements (life cycle improvement, and size reduction), (4) regenerative braking in electric vehicles, (5) improvement in wireless power transfer technology. Further, this review also descriptively highlights the control strategies implemented in these domains of applications. The application-oriented review explicates the principle advantages with the hybridization of battery and supercapacitor energy storage systems that can be used as an insight for further development in the field of energy storage technology and its applications. Power Ratings (MW) 0-0.03 [12,13] 0-20 [12,13] 0-0.01 [12,13] 0.05-8 [12,13] 0.03-3 [12,13] 0-0.3 [12] 50 [13] Energy Density, Wh/L

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“…Kulaksiz et al presented a genetic algorithm (GA) method to improve the maximum power point tracing capacity of a photovoltaic system [2]. Sharma et al proposed an optimal power point tracking and control method for a hybrid renewable energy system under an independent environment [3]. Raju et al suggested the application of the improved distributed energy management system and request management of a solar microgrid using a multiagent system coordination method [4].…”

Section: Introductionmentioning

confidence: 99%

Rule extraction and performance estimation by using variable neighborhoodsearch for solar power plant in Konya

Uzun¹,

Özcan²

2020

Turk J Elec Eng & Comp Sci

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The use of renewable energy sources in the production of electricity has become inevitable in order to reduce the greenhouse gases left in the atmosphere that cause the Earth to warm up. Although countries on a national basis have implemented a number of policies to support electricity generated from renewable energy sources, investments to produce electricity without a license on a local basis are not desirable. Those who want to invest medium and small scale for the most reason expect that this work will be supported by real data. Although the electricity generated by renewable investments is generated by simulation data, these data are not realistic for such investors. In this study, the climatic conditions of the power plant of 1 MW installed in Konya and power plant production data are monitored. The artificial neural network (ANN) can achieve a high value for accuracy, but these values are sometimes complex and unclear. In the literature, a number of studies have been conducted using different methods to overcome such problems. Real-time solar power plant (SPP) data were used to determine the feasibility and success of the proposed method. The variable neighborhood search (VNS) metaheuristic method was used to acquire the optimal values belonging to input vectors, G h , which were maximized to the value of the fitness function Fs belonging to output class node s. The results obtained by the VNS method showed that the proposed method has the potential to produce the correct rules. Generally, energy investors are curious about the return on their investment. It is very important for energy providers to estimate how much electricity will be generated from existing solar power plants and accordingly determine the measures they will take to meet the electricity demand in the future. In this study, the performance estimation value obtained from the solar power plant depending on the weather conditions was obtained with 95.55% accuracy.

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Novel control strategy for hybrid renewable energy-based standalone system

Cited by 13 publications

References 20 publications

Maximum wind speed forecasting using historical data and artificial neural networks modeling

Maximum wind speed forecasting using historical data and artificial neural networks modeling

A Review on the Selected Applications of Battery-Supercapacitor Hybrid Energy Storage Systems for Microgrids

Rule extraction and performance estimation by using variable neighborhoodsearch for solar power plant in Konya

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