Data for the Techno-Economic Assessment of Off-Grid Hybrid Renewable Energy Systems for Reliable Power Supply in Remote Regions
Description
Data for the Techno-Economic Assessment of Off-Grid Hybrid Renewable Energy Systems for Reliable Power Supply in Remote Regions This dataset includes the available and publishable data used to investigate the optimal design and performance of hybrid renewable energy systems. The study applies advanced metaheuristic optimization methods to evaluate system reliability, cost, and operational performance. The analysis focuses on off-grid applications that support Saudi Arabia’s ongoing energy transition. The dataset supports research on system configuration, component sizing, storage requirements, and economic feasibility. It also enables you to assess how different algorithms improve reliability and reduce lifecycle cost under variable climatic and load conditions. Keywords • Hybrid Renewable Energy Systems • Off-Grid Microgrids • Metaheuristic Optimization • Techno-Economic Analysis • Saudi Vision 2030 • Energy Storage Systems • Reliability Assessment • DMOA • MSA You can review the following references for more information and for data that cannot be publicly released. Journal papers: 1. Al Dawsari, Saleh Awadh, Fatih Anayi, and Michael Packianather. "Techno-economic analysis of hybrid renewable energy systems for cost reduction and reliability improvement using dwarf mongoose optimization algorithm." Energy 313 (2024): 133653. https://doi.org/10.1016/j.energy.2024.133653 2. Al Dawsari, Saleh Awadh, Fatih Anayi, and Michael Packianather. "Optimizing a hybrid off-grid photovoltaic/wind/fuel cell energy system using mantis search algorithm." Energy Conversion and Management: X (2025): 101209. https://doi.org/10.1016/j.ecmx.2025.101209 3. Al Dawsari, Saleh Awadh, Fatih Anayi, and Michael Packianather. "Novel techno-economic feasibility study of an off-grid PV/wind/diesel/battery hybrid energy system using MATLAB-HOMER link." Energy Conversion and Management: X (2025): 101386. https://doi.org/10.1016/j.ecmx.2025.101386 Conference papers: 1. Al Dawsari, Saleh Awadh, Fatih Anayi, and Michael Packianather. "Novel optimal configuration approach for off-grid microgrid with hybrid energy storage using Mantis search algorithm." In 2024 12th International Conference on Smart Grid (icSmartGrid), pp. 255-264. IEEE, 2024. https://doi.org/10.1109/icSmartGrid61824.2024.10578170 2. Al Dawsari, Saleh Awadh, Fatih Anayi, and Michael Packianather. " Optimizing a Hybrid Off-Grid Photovoltaic/Wind/Fuel Cell Energy System Using Mantis Search Algorithm." The 19th SDEWES Conference, held from 8 to 12 September 2024 in Rome, Italy
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Steps to reproduce
Data acquisition and processing • Defined the system boundary of the off-grid hybrid renewable energy system and identified the required technical and economic inputs. • Obtained solar irradiance and wind speed records from publicly accessible meteorological databases and validated them against regional Saudi datasets. • Collected component specifications for PV modules, wind turbines, batteries, inverters, and diesel generators from manufacturer datasheets and verified the values using cross-referenced catalogues. • Compiled capital cost, replacement cost, and operational cost values from published techno-economic studies and recent market reports. • Processed the raw data using MATLAB workflows. Scripts handled filtering, missing data treatment, unit conversion, and time-series alignment. • Applied a unified protocol for load profiling. Hourly load data were normalized and checked for outliers with simple statistical thresholds. • Prepared the optimization input files using standardized parameter ranges for DMOA and MSA. All settings followed previous peer-reviewed optimization studies to ensure reproducibility. • Generated simulation outputs through repeated runs to capture variability. I stored the results as structured tables that can be reproduced by executing the shared scripts. You can reproduce the dataset by following the same sources, processing steps, and software workflows.
Institutions
- Cardiff University