Mass Wind Deployment in Egypt: The Transformative Energy Hub among three continents

Wind Energy is occupying more and more space of the energy mix in most of the world. In this work, the challenges for distributed projects in communities and industrial areas are presented for Egypt and a comparison with the mass wind onshore and offshore deployment is unavoidable. In Egypt, there are plans to installed large-scale projects, but the development pace is slow. Furthermore, while the Egypt wind atlas provides ample information to properly plan and deploy wind farms, developers of distributed wind would probably have never analysed small scale sites, which may lead them to make mistakes while siting, and thus a project may end up losing money. Two use cases were selected for analysis: industrial & offshore sites and community/residential sites. It was revealed via a detailed spatial analysis that there are abundant wind resources and potential in high wind – high gain selected areas of almost 40 GW of onshore and offshore wind projects that could make Egypt a unique energy hub between Africa, Europe and the Middle East.

Renewable Energy Industry: Challenges and Development Opportunities

The development features of the renewable energy industry in solar and wind generation sectors, both characterized by their high manufacturability and equipment and components export potential and their extremely low production scale have been presented. The issues in relation to the solar and wind resources efficiency, cost reduction of solar and wind generation, electricity production technologies by increased application of the international practices have been studied.

Energy and Acoustic Environmental Effective Approach for a Wind Farm Location

The justification for the construction of a wind farm depends primarily on two factors. The first one is the availability of the area with significant windiness; the second one is the environmental conditions in the selected location. The aim of this paper was to demonstrate the need for parallel noise and energy analyses during the design of a turbine location and selection of its type on the wind farm. The noise analyses were performed according to ISO 9613-2. A detailed analysis of wind conditions in a given location is a basic activity to determine the profitability of a wind power plant foundation. The main environmental impact of WF is noise emission. The examples of wind turbines’ selection optimally utilizing wind resources in two particular locations are presented. Six wind turbines were analyzed for each location. The choice of a wind turbine for the examined location was determined by the parameters of the device, the results of annual wind measurements, and acceptable noise levels in the environment. The three devices that met the acoustic criteria and the most energy efficient ones are indicated. We describe how a proper process of selecting a type of WT for a specific location should proceed.

Geophysical constraints on the reliability of solar and wind power worldwide

If future net-zero emissions energy systems rely heavily on solar and wind resources, spatial and temporal mismatches between resource availability and electricity demand may challenge system reliability. Using 39 years of hourly reanalysis data (1980–2018), we analyze the ability of solar and wind resources to meet electricity demand in 42 countries, varying the hypothetical scale and mix of renewable generation as well as energy storage capacity. Assuming perfect transmission and annual generation equal to annual demand, but no energy storage, we find the most reliable renewable electricity systems are wind-heavy and satisfy countries’ electricity demand in 72–91% of hours (83–94% by adding 12 h of storage). Yet even in systems which meet >90% of demand, hundreds of hours of unmet demand may occur annually. Our analysis helps quantify the power, energy, and utilization rates of additional energy storage, demand management, or curtailment, as well as the benefits of regional aggregation.

Robust Optimal Dispatching of Wind Fire Energy Storage System Based on Equilibrium Optimization Algorithm

The uncertainty of wind resources is one of the main reasons for wind abandonment. Considering the uncertainty of wind power prediction, a robust optimal dispatching model is proposed for the wind fire energy storage system with advanced adiabatic compressed air energy storage (AA-CAES) technology. Herein, the operation constraints of the power plant and constraints of the reserved capacity are defined according to the operation characteristics of AA-CAES. Based on the limited scenario method, a solution framework is proposed to achieve the optimal robustness and economical operation of the system, which provides a new way for the application of the intelligent algorithm in the robust optimal dispatching. Specifically, a novel equilibrium optimization algorithm is employed to solve the optimal dispatching problem, which has good global search performance. The proposed solution is validated through simulations based on the IEEE-39 node system. The simulation results verify the effectiveness of the proposed dispatching model and the intelligent solver.

Systematic Analysis of Wind Resources for Eolic Potential in Bangladesh

Energy consumption in Bangladesh increased for economic, industrial, and digitalization growth. Reductions in conventional sources such as natural gas (54%) and coal (5.6%) are calls to enhance renewable resources. This paper aims to investigate the atmospheric variables for potential wind zones and develop a statistical power-forecasting model. The study-site is Bangladesh, focusing on eight divisions across two regions. First, the southern zone includes Dhaka (Capital), Chittagong, Barishal, and Khulna. The northern regions are Rajshahi, Rangpur, Mymensingh, and Sylhet. This investigation illustrates wind (m/s) speeds at various heights (m) and analyzes the boundary layer height (BLH) from the European Center for Medium Range Weather Forecast reanalysis 5th generation (ERA5). The data is from a period of 40 years from 1979 to 2018, assessing with a climatic base of 20 years (1979 to 2000). The climatological analysis comprises trends, time series, anomalies, and linear correlations. The results for the wind speed (BLH) indicate that the weakest (lower) and strongest (higher) regions are Sylhet and Barishal, respectively. Based on power-curve relationships, a simple power predictive model (SPPM) is developed using global wind atlas (GWA) data (sample: 1100) to estimate the power density (W/m2) and found an accuracy of 0.918 and 0.892 for Exponential (EXP) and Polynomial (PN) with mean absolute percentage errors (MAPE) of 22.92 and 21.8%, respectively. For validation, SPPM also forecasts power incorporating historical observations for Chittagong and obtains correlations of 0.970 and 0.974 for EXP and PN with a MAPE of 10.26 and 7.69% individually. Furthermore, calculations for annual energy production reveal an average megawattage of 1748 and 1070 in the southern and northern regions, with an MAPE of 15.71 and 5.85% for EXP and PN models, except Sylhet. The SPPM’s predictability can be improved with observed wind speeds and turbine types. The research wishes to apply SPPM for estimating energy in operational power plants.

Small wind turbines study and integration in a peri-urban microgrid

The use of wind resources has always gone hand in hand with high wind speeds in open fields. This paper develops the decisions to be taken for the selection, installation, and connection of small wind turbines in peri-urban environments, where wind speeds are medium or low. The guidelines are detailed throughout the document, starting with the study of the wind resource, the selection of the turbine, installation, and real-time monitoring of production for integration into a micro power grid. The installation of small wind systems in places as close as possible to the point of demand makes it possible to achieve a reduction in the cost of the electricity bill. This is thanks to the instantaneous control of generation and demand at a particular level through the installation of software, in this case, Home Assistant. The novelty of this paper is the use of this software Home Assistant to integrate of a small wind turbine in a microgrid and its control system.

A New Hybrid Algorithm for Multi-Objective Reactive Power Planning via FACTS Devices and Renewable Wind Resources

The power system planning problem considering system loss function, voltage profile function, the cost function of FACTS (flexible alternating current transmission system) devices, and stability function are investigated in this paper. With the growth of electronic technologies, FACTS devices have improved stability and more reliable planning in reactive power (RP) planning. In addition, in modern power systems, renewable resources have an inevitable effect on power system planning. Therefore, wind resources make a complicated problem of planning due to conflicting functions and non-linear constraints. This confliction is the stochastic nature of the cost, loss, and voltage functions that cannot be summarized in function. A multi-objective hybrid algorithm is proposed to solve this problem by considering the linear and non-linear constraints that combine particle swarm optimization (PSO) and the virus colony search (VCS). VCS is a new optimization method based on viruses’ search function to destroy host cells and cause the penetration of the best virus into a cell for reproduction. In the proposed model, the PSO is used to enhance local and global search. In addition, the non-dominated sort of the Pareto criterion is used to sort the data. The optimization results on different scenarios reveal that the combined method of the proposed hybrid algorithm can improve the parameters such as convergence time, index of voltage stability, and absolute magnitude of voltage deviation, and this method can reduce the total transmission line losses. In addition, the presence of wind resources has a positive effect on the mentioned issue.