A new LPF-based grid frequency estimation for the SOGI filter with improved harmonic rejection

This paper proposes a new method for the estimation of the grid voltage frequency using a low-pass filter (LPF) approach. The estimated frequency is used to tune a second order generalized integrator (SOGI) filter commonly used for grid monitoring purposes and applications requiring parameter estimation from the grid. A first-order LPF is used first for the estimation that behaves identically to the reported normalized SOGI-FLL. A second-order LPF is proposed instead to overcome this circumstance. The behavior of this approach is dynamically analyzed and a linearized model useful for design purposes is derived. The behavior of the proposed system is checked with simulations, showing that the model matches well with the real system and has a smoother transient response to step frequency perturbations and also a better rejection to harmonic distortion than previous approaches.Peer ReviewedPostprint (published version

Energy Commitment for a Power System Supplied by Multiple Energy Carriers System using Following Optimization Algorithm

In today’s world, the development and continuation of life require energy. Supplying this energy demand requires careful and scientific planning of the energy provided by a variety of products, such as oil, gas, coal, electricity, etc. A new study on the operation of energy carriers called Energy Commitment (EC) is proposed. The purpose of the EC is to set a pattern for the use of energy carriers to supply energy demand, considering technical and economic constraints. EC is a constrained optimization problem that can be solved by using optimization methods. This study suggests the Following Optimization Algorithm (FOA) to solve the EC problem to achieve technical and economic benefits. Minimizing energy supply costs for the total study period is considered as an objective function. The FOA simulates social relationships among the community members who try to improve their community by following each other. Simulation is carried out on a 10-unit energy system supplied by various types of energy carriers that includes transportation, agriculture, industrial, residential, commercial, and public sectors. The results show that the optimal energy supply for a grid with 0.15447 Millions of Barrels of Oil Equivalent (MBOE) of energy demand costs 9.0922 millions dollar for a 24-h study period. However, if the energy supply is not optimal, the costs of operating energy carriers will increase and move away from the optimal economic situation. The economic distribution of electrical demand between 10 power plants and the amount of production units per hour of the study period is determined. The EC outputs are presented, which include an appropriate pattern of energy carrier utilization, energy demand supply costs, appropriate combination of units, and power plant production. The behavior and process of achieving the answer in the convergence curve for the implementation of FOA on EC indicates the exploration and exploitation capacity of FOA. Based on the simulated results, EC provides more information than Unit Commitment (UC) and analyzes the network more efficiently and deeply.Peer ReviewedPostprint (published version

A detailed hydrothermal investigation of a helical micro double-tube heat exchanger for a wide range of helix pitch length

The present study was numerically inquired the heat transfer performance and fluid flow characteristic of a helical micro double-tube heat exchanger (HMDTHX) using the finite volume method. The tube length was considered to be constantly equal to 30 mm, and 12 different configurations were modeled by changing in turn number and pitch length (P) for Reynolds numbers of 50, 100, 150, and 200. The findings indicated that the heat transfer would enhance by applying any helix angle in the straight tube. However, it had an optimum point which varied by Reynolds number (Re). Rising Re caused overall heat transfer coefficient (OHTC), pressure drop, and pumping power augment for all cases. Increasing P in overall reduced OHTC, pressure drop, and pumping power which had different maximum points between P = 0.5 to 3. Maximum overall heat transfer coefficient (OHTC) enhancement was equal to 45% for Re = 200 and P = 2. Also, maximum effectiveness was 11.5% for P = 2 and Re = 200. Moreover, a 42% maximum increment was achieved for pressure drop, pumping power, and friction factor at Re = 200 and P = 2. Shear stress for Re = 100 to 200 showed that the values are almost the same for P = 0.5 and 1. Then by increasing P, the shear stress decreases. While, for Re = 50, a maximum is seen at P = 2. The temperature distribution was indicated that the maximum temperature of the straight tube and helical tube are the same, but the difference is in the average temperature, which was 3.2 K between straight and helical tubes. Finally, by investigating the velocity contour, it was determined that a secondary flow through the HMDTHX, affected by centrifugal force, was existed, enhancing the fluid flow turbulency and heat transfer rate

Intelligent machine learning with evolutionary algorithm based short term load forecasting in power systems

Electricity demand forecasting remains a challenging issue for power system scheduling at varying stages of energy sectors. Short Term load forecasting (STLF) plays a vital part in regulated power systems and electricity markets, which is commonly employed to predict the outcomes power failures. This paper presents an intelligent machine learning with evolutionary algorithm based STLF model, called (IMLEA-STLF) for power systems which involves different stages of operations such as data decomposition, data preprocessing, feature selection, prediction, and parameter tuning. Wavelet transform (WT) is used for the decomposition of the time series and Oppositional Artificial Fish Swarm Optimization algorithm (OAFSA) based feature selection technique to elect an optimal set of features. In order to improvise the convergence rate of AFSA, oppositional based learning (OBL) concept is integrated into it. Then, the water wave optimization (WWO) with Elman neural networks (ENN) model is employed for the predictive process. Finally, inverse WT is applied and obtained the hourly load forecasting data. To validate the effective predictive outcome of the IMLEA-STLF model, an extensive set of simulations take place on benchmark dataset. The resultant values ensured the promising results of the IMLEA-STLF model over the other compared methods

Potential of Concentrated Solar Power in the Western Region of Saudi Arabia: A GIS-Based Land Suitability Analysis and Techno-Economic Feasibility Assessment

Saudi Arabia (SA) currently relies on fossil fuels to address its escalating electricity demand and rapid industrialization, a practice that significantly contributes to climate change. This study underscores the potential of solar energy as a key renewable energy source (RES) for SA, with a specific focus on Concentrated Solar Power (CSP). CSP stands out due to its capacity to provide dispatchable electricity coupled with thermal energy storage (TES). This research introduces an integrated energy model encompassing both site suitability and techno-economic analyses tailored for utility-scale CSP technology. The investigation unfolds in two phases: site suitability analysis and techno-economic assessment, each designed to scrutinize the viability and applicability of CSP technology for power generation in SA’s western region. In the initial phase, an innovative approach, leveraging Fuzzy-Boolean Logic and Analytical Hierarchy Process (AHP) through GIS tools, is employed to identify optimal CSP plant locations. This method offers a more comprehensive and robust analysis by accounting for uncertainty and ambiguity in decision-making. Criteria are prioritized based on relative importance, contributing a novel dimension to the field. The analysis reveals that 70% of the province’s land is suitable for CSP deployment, with Makkah, Taif, Al-Khumra, and Turbah identified as the most favorable locations. In the second phase, two established CSP plants, Shams-1 and Noor III, are utilized to evaluate the technical and economic feasibility of CSP in five selected sites within the most suitable areas. The analysis unveils the lowest levelized cost of electricity (LCOE) for utility-scale CSP plants in Makkah province, standing at 9.58 ¢/kWh for parabolic trough (PT) technology and 9.17 ¢/kWh for solar power tower (SPT) technology. Sensitivity analysis of TES indicates that CSP plants with 8 hours of storage exhibit the optimal configuration, producing electricity with the lowest LCOE and the highest capacity factor (CF). This comprehensive study establishes CSP as a viable and promising renewable energy (RE) technology for SA. The proposed site selection methodology facilitates the identification of suitable locations for CSP plants, while the techno-economic analysis demonstrates that CSP plants equipped with TES are both cost-effective and reliable

Power calculation algorithm for single-phase droop-operated inverters considering nonlinear loads

The average active and reactive powers, Pav and Qav, are crucial parameters that have to be calculated when sharing common loads between parallelized droop-operated single-phase inverters. However, low-pass filters (LPF) with very low cut-off frequency should be used to minimize the distortion impact in the amplitude and frequency references provided by the droop equations. This forces the control to operate at a very low dynamic velocity, degrading the stability of the parallelized system. For this reason, different solutions had been proposed to increase the droop operation velocity in literature, but with the consideration of only sharing linear loads. The issues derived from the sharing of nonlinear loads had not been properly considered. This paper proposes a method to calculate Pav and Qav using second order generalized integrators (SOGI) that increase the velocity of the droop control algorithm considering nonlinear loads as the design worst case scenario. Then it is employed a double SOGI (DSOGI) approach to filter the current non-sinusoidal waveform and provide the fundamental component, which results in a faster transient response and improves the system's stability. The proposed calculation method shows to be faster than other approaches when considering nonlinear loads. Simulations are provided to validate the proposal.Peer Reviewe

An automated algorithm for stability analysis of hybrid dynamical systems

There are many hybrid dynamical systems encountered in nature and in engineering, that have a large number of subsystems and a large number of switching conditions for transitions between subsystems. Bifurcation analysis of such systems poses a problem, because the detection of periodic orbits and the computation of their Floquet multipliers become difficult in such systems. In this paper we propose an algorithm to solve this problem. It is based on the computation of the fundamental solution matrix over a complete period–where the orbit may contain transitions through a large number of subsystems. The fundamental solution matrix is composed of the exponential matrices for evolution through the subsystems (considered linear time invariant in this paper) and the saltation matrices for the transitions through switching conditions. This matrix is then used to compose a Newton-Raphson search algorithm to converge on the periodic orbit. The algorithm–which has no restriction of the complexity of the system–locates the periodic orbit (stable or unstable), and at the same time computes its Floquet multipliers. The program is written in a sufficiently general way, so that it can be applied to any hybrid dynamical system