ArticleScientific reports2023
Optimization and intelligent power management control for an autonomous hybrid wind turbine photovoltaic diesel generator with batteries.
Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
12 citing papers in PubMed.
- Intelligent demand-side energy management via optimized ANFIS-gene expression programming in hybrid renewable-grid systems.Scientific reports · 2025Article
- Optimizing control and management of hybrid power system, consisting PV-wind and battery-super capacitor, using COOT algorithm.Scientific reports · 2025Article
- Effective optimal control of a wind turbine system with hybrid energy storage and hybrid MPPT approach.Scientific reports · 2024Article
- Power control of an autonomous wind energy conversion system based on a permanent magnet synchronous generator with integrated pumping storage.Scientific reports · 2024Article
- Machine learning-based energy management and power forecasting in grid-connected microgrids with multiple distributed energy sources.Scientific reports · 2024Article
- Chaotic self-adaptive sine cosine multi-objective optimization algorithm to solve microgrid optimal energy scheduling problems.Scientific reports · 2024Article
- Multi-objective energy management in a renewable and EV-integrated microgrid using an iterative map-based self-adaptive crystal structure algorithm.Scientific reports · 2024Article
- Enhancing residential energy access with optimized stand-alone hybrid solar-diesel-battery systems in Buea, Cameroon.Scientific reports · 2024Article
- Coordinated power management strategy for reliable hybridization of multi-source systems using hybrid MPPT algorithms.Scientific reports · 2024Article
- Enhancing grid-connected photovoltaic system performance with novel hybrid MPPT technique in variable atmospheric conditions.Scientific reports · 2024Article
- A new intelligently optimized model reference adaptive controller using GA and WOA-based MPPT techniques for photovoltaic systems.Scientific reports · 2024Article
- A multilayer perceptron neural network approach for optimizing solar irradiance forecasting in Central Africa with meteorological insights.Scientific reports · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
In this paper, a critical issue related to power management control in autonomous hybrid systems is presented. Specifically, challenges in optimizing the performance of energy sources and backup systems are proposed, especially under conditions of heavy loads or low renewable energy output. The problem lies in the need for an efficient control mechanism that can enhance power availability while protecting and extending the lifespan of the various power sources in the system. Furthermore, it is necessary to adapt the system's operations to variations in climatic conditions for sustained effectiveness. To address the identified problem. It is proposed the use of an intelligent power management control (IPMC) system employing fuzzy logic control (FLC). The IPMC is designed to optimize the performance of energy sources and backup systems. It aims to predict and adjust the system's operating processes based on variations in climatic conditions, providing a dynamic and adaptive control strategy. The integration of FLC is specifically emphasized for its effectiveness in balancing multiple power sources and ensuring a steady and secure operation of the system. The proposed IPMC with FLC offers several advantages over existing strategies. Firstly, it showcases enhanced power availability, particularly under challenging conditions such as heavy loads or low renewable energy output. Secondly, the system protects and extends the lifespan of the power sources, contributing to long-term sustainability. The dynamic adaptation to climatic variations adds a layer of resilience to the system, making it well-suited for diverse geographical and climatic conditions. The use of realistic data and simulations in MATLAB/Simulink, along with real-time findings from the RT-LAB simulator, indicates the reliability and practical applicability of the proposed IPMC strategy. Efficient load supply and preserved batteries further underscore the benefits of the fuzzy logic-based control strategy in achieving a well-balanced and secure system operation.
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.