Power Management Strategy Based on Weather Prediction for Hybrid Stand-alone System

Dahmane, Menad; Bosche, Jérôme; El-Hajjaji, Ahmed

doi:10.1016/j.egypro.2015.12.187

Cited by 11 publications

(3 citation statements)

References 23 publications

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“…Power estimation using real-time changing atmospheric data can also be used as a reference value for other application areas. Examples of energy management studies [27], [28] for maintaining the balance between load and source or hybrid energy sources can be given. Similarly, approaches such as Artificial neural network (ANN) and ANFIS can also perform the function of integrating various energy sources into the existing system [29] and contribute to smart grid applications [30].…”

Section: Introductionmentioning

confidence: 99%

ANFIS Based Real-Time Power Reference Generator for PV Applications

Gökkuş

2022

ECJSE

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In this study, a real-time power estimation of a 250Wp solar panel is performed by using a commercial product SIS01-TC-T PV reference module and STM development board. Power estimation was carried out with Adaptive Neuro-Fuzzy Inference System (ANFIS). During the training process, the actual values of the Photo Voltaic (PV) panel with a 250Wp power were used. ANFIS training was accomplished with the hybrid learning algorithm. The power estimation process can be used as a reference power for various applications. The estimated power value can be used in real-time power monitoring for remote monitoring systems or optimum angle control applications for solar tracking mechanisms. It can also be used as a reference value for hybrid Maximum Power Point Tracking (MPPT) control applications or Proportional, Integral, and Derivative (PID) control. In addition, with this reference power value, the Pulse Width Modulation (PWM) signal required by various power electronics stages can be generated.

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Section: Introductionmentioning

confidence: 99%

ANFIS Based Real-Time Power Reference Generator for PV Applications

Gökkuş

2022

ECJSE

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“…Wind speed data are broadly used for wind energy potential analysis, as presented in [5][6][7]. Similarly, wind speed data are also used for optimal sizing of renewable energy systems [8][9][10][11], energy management systems relying on weather forecasts [12][13][14][15].…”

Section: Introductionmentioning

confidence: 99%

A Low-Cost System for Measuring Wind Speed and Direction Using Thermopile Array and Artificial Neural Network

Tzou

Ding

2021

Applied Sciences

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Recent developments in wind speed sensors have mainly focused on reducing the size and moving parts to increase reliability and stability. In this study, the development of a low-cost wind speed and direction measurement system is presented. A heat sink mounted on a self-regulating heater is used as means to interact with the wind changes and a thermopile array mounted atop of the heat sink is used to collect temperature data. The temperature data collected from the thermopile array are used to estimate corresponding wind speed and direction data using an artificial neural network. The multilayer artificial neural network is trained using 96 h data and tested on 72 h data collected in an outdoor setting. The performance of the proposed model is compared with linear regression and support vector machine. The test results verify that the proposed system can estimate wind speed and direction measurements with a high accuracy at different sampling intervals, and the artificial neural network can provide significantly a higher coefficient of determination than two other methods.

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“…1,2 Renewable hybrid systems usually are installed for reliability improvement of the customers, supplied from a weak network or electrification of rural or inaccessible areas. 3 Producing electrical energy from sunlight and wind energy, photovoltaic (PV) and wind turbine (WT) technology has gone under rapid development, among other renewable resources. As it is known, unpredictable behavior of PV/WT plants makes the employment of the support systems and storage units necessary.…”

Section: Introductionmentioning

confidence: 99%

A comparative study of PI, fuzzy‐PI, and sliding mode control strategy for battery bank SOC control in a standalone hybrid renewable system

Allahvirdizadeh

Shayanfar

Moghaddam

2019

Int Trans Electr Energ Syst

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Summary Hybrid renewable systems (HRSs) by offering green energy play an important role in supporting increasing electricity demand with regard to shrinking natural resources, global warming, and rising electric charges. Generally, higher efficiency, better power quality, improved reliability, and stability can be achieved from hybrid renewable energy systems when compared with single renewable energy systems. As a result, in this study, a hybrid system consisting renewable energy sources (PV/WT) is chosen. Besides, a backup system comprising hydrogen‐based storage system and batteries is provided because of the intermittent and undispatchable PV/WT power generation. In this paper, the power management system (PMS) includes the application of three control strategies: proportional‐integral controller (PI), fuzzy‐PI, and sliding mode control to meet design and demand objectives. The target of this paper is to investigate and compare the performance of the aforementioned control strategies considering hydrogen consumption, fuel/fuel‐cell efficiency, shorter settling time, and fewer fluctuations around the reference value. Two scenarios of constant and random loads are taken into consideration. Taking into consideration the before said criteria, the sliding mode control has a better control response in comparison with the other strategies.

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Power Management Strategy Based on Weather Prediction for Hybrid Stand-alone System

Cited by 11 publications

References 23 publications

ANFIS Based Real-Time Power Reference Generator for PV Applications

ANFIS Based Real-Time Power Reference Generator for PV Applications

A Low-Cost System for Measuring Wind Speed and Direction Using Thermopile Array and Artificial Neural Network

A comparative study of PI, fuzzy‐PI, and sliding mode control strategy for battery bank SOC control in a standalone hybrid renewable system

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