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Climatic phenomena, particularly hydrological droughts, have led to significant changes in reservoir operation strategies. Multipurpose reservoir operations are essential for effectively managing stored water resources for various activities like electricity generation and agricultural irrigation. Despite considerable efforts to support decision making for each economic activity, there remains a weak integration across these sectors in joint analyses. To address this, an integrated approach combining a model of a large power system and a model at the basin scale is proposed to analyze the operation of both power and agricultural systems. This approach allows evaluation of the operating policies of a multipurpose reservoir and its performance at both the local and regional scales under different hydrological scenarios. A modification is implemented whereby the priority of water extraction to agricultural users is increased. Its effects are assessed for different hydrological trajectories in a case study in the Laja Lake basin in southern Chile, the biggest Chilean basin with a capacity of up to 5,500 Hm3. The Laja Lake, a multipurpose reservoir with substantial hydroelectric generation capacity and extensive agricultural areas plays a crucial role in the operation of the national power system. Based on an analysis of 2025, it is demonstrated that hydrological changes directly impact electrical and agricultural performance. Drought conditions increase thermal generation, costs, emission intensity, and water deficits. Furthermore, the policy modification reveals tradeoffs between the power sector's emissions and agricultural water deficits. For drier scenarios, increasing agricultural extraction priority results in low additional operational costs and emissions from the power system, which supports adopting a policy aligned with netzero objectives. [ABSTRACT FROM AUTHOR]

Copyright of Przegląd Elektrotechniczny is the property of Przeglad Elektrotechniczny and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Unreliable resources in conventional power systems have created new challenges for the users of these systems. These sources of production, including wind and solar sources, with a significant share in the power generation of many power systems, cause problems in the safe and stable operation of power systems due to uncertainty. Therefore, it is very important to provide a method or model for safe and stable operation of power systems. The main innovation of this paper is to present a new SCUC model to maximize the flexibility of the system along with reducing the operating cost in the form of a security constrained multi-level robust optimization problem in the presence of wind uncertainty sources. Also, a set of demand response programs and rapid response hybrid cycle units are used as sources of flexibility. Accordingly, the tolerable range of uncertainty and system slope reservation is developed with a low-cost combination and with the commitment to flexible covering resources. The desired optimization problem has been solved with the help of the NCCG algorithm and MILP method. The efficiency and reliability of this proposed model have been simulated and evaluated in IEEE 6-bus and 118-bus standard power systems, and the simulation results confirm the technical and economic efficiency of this model. [ABSTRACT FROM AUTHOR]

The systems of policies impacting climate change mitigation are complex. Yet, to date, we have limited conceptual and empirical knowledge on the dynamics within these. We address this gap by employing a systems lens to untangle the interactions between the policies affecting climate change mitigation in the electricity generation space. We conceptualise climate policyscapes for electricity generation as systems populated with policies whose means impact decarbonisation in the electricity generation space. The impacts under analysis include both support and obstruction of climate change mitigation. We analyse the evolution of the UK climate policyscape from 1956 to 2022. Methodologically, we combine qualitative content analysis and network analysis. We populate the policyscapes with pieces of legislation in the electricity generation space and employ qualitative content analysis to identify the policy means affecting climate change mitigation. Our network analysis of the 2022 climate policyscape reveals that policies hindering climate mitigation remain largely present, which renders the climate policyscape incoherent. We show that policies supporting mitigation are more likely to behave as a group than policies hindering climate mitigation. Climate policies tend to be adopted as packages, whilst fossil policies remain a steady process throughout the history of the UK climate policyscape. [ABSTRACT FROM AUTHOR]

Summary: Due to the energy crisis and environmental concerns, wind power has seen a considerable increase in use over the past 10 years as a source of renewable energy. Since wind is intermittent and variable, it is obvious that as penetration levels rise, the influence of wind power generation on the electric power system must be considered. Wind power forecasting is essential because large‐scale wind power integration will make it more difficult to plan, operate, and control the power system. An accurate forecast is an efficient way to deal with the operational problems brought on by wind variability. To better utilize wind energy resources, it is essential to increase prediction accuracy. Frequently, the noise in the dataset causes the ramp events to be misclassified or overestimated. The main emphasis of this study is the pre‐processing of wind power data that produces precise time‐series data while reducing noise or artifact content and maintaining the swing feature of the original data. For this task, the data augmentation approach is proposed, where the augmented data (synthetic data) will be added up with the training data, in such a way as to make the strategy useful for real‐time applications. As the next step, the significant features, such as higher‐order statistical features and lower‐order statistical features are extracted. The extracted features act as the input to the recurrent neural network (RNN) classifier, the weights of which are tuned using the proposed honey badger crow (HBCro) optimization algorithm. The proposed HBCro optimization algorithm acts as the major contribution of the proposed model, and it is modeled with the integration of the concepts of the crow search optimization (CSO) algorithm and the honey badger optimization algorithm (HBA). The proposed system is simulated in MATLAB and the effectiveness of the proposed method is validated by comparison with other conventional methods in terms of Error measures. Furthermore, the developed HBCro‐based RNN obtained efficient performance in terms of MSE, MAE, RMSE, RMPSE, MAPE, MARE, MSRE, and RMSRE of 0.1578, 0.0442, 0.2102, 123.238, 124.72, 0.9944, 1.1799, and 1.0732, respectively. [ABSTRACT FROM AUTHOR]

This study introduces the Bi-Level Source-Grid-Load Synergistic Optimization (BL_SGLSO) model, which effectively balances the competing objectives of water conservation and carbon emission reduction in the power industry. The model aims to establish a clean and low-carbon electric power system by harmoniously reconciling these two critical goals. Through the application of bi-level programming, the BL_SGLSO model adeptly manages the preferences and conflicts of decision makers at various levels while capturing regional interactions and the intricacies of electricity transmission. Key findings reveal that non-fossil energy conversion technologies are poised to become the dominant force in electricity generation, accounting for an impressive 89.34% share by 2050. To mitigate the spatial mismatch between power load and resource allocation, the development of new transmission pathways and the expansion of the "power transmission from west to east" initiative are paramount. Furthermore, the implementation of a carbon-reducing power system offers significant potential for conserving water resources and alleviating water stress. These insights provide invaluable guidance for decision makers seeking to optimize multi-regional electric power systems for both water efficiency and low-carbon outcomes while simultaneously promoting the adoption of renewable energy sources and fostering synergistic development across regions. [ABSTRACT FROM AUTHOR]

Load forecasting is a key aspect of power system design, operation, and maintenance. To obtain an accurate forecast model which is very vital for the development of any power sector capacity expansion plan be it on generation, transmission and distribution, regression (0.0139) and mean square error (0.99791) were used as criteria for selecting the optimal model for load forecasting. The higher the value of regression, the better the value of the accuracy of the load forecast. In the same vein, the lower the value of the mean square error, the better the accuracy of the load forecast. The load forecast using Backpropagation artificial neural network (BPANN) obtained load forecast in the year 2035 to be 85998MW. This forecast is necessary to provide an increase in generation capacity to meet 85836.99MW of load by 2035. Taking 2021 as base year, the total load demand, which comprises the industrial, commercial, and residential customers were estimated and used to forecast the total load requirements of the customers in year 2035. The ten experimental results obtained by creating ten different topologies of BPANN validated the choice of 30 hidden layer neurons for use in the load forecasting. [ABSTRACT FROM AUTHOR]

Understanding the water requirement of electricity generation is critical to the development of both electricity and water systems, while the water consumption of the whole electric power system remains unrevealed. Here, we examine the water consumption driven by electricity generation, transmission, and consumption in China, finding that 14 billion m3 of freshwater is consumed by electricity generation in 2019 and that 2.5 billion m3 of freshwater was virtually transferred via electricity transmission. Nationally, the freshwater consumption per unit of electricity generation was 1.9 m3/MWh. Based on the state-of-the-art electricity transmission data, we find that 59% of the transported electric power was from water-scarce provinces and 0.7 billion m3 of freshwater was lost due to the electricity loss in transmission lines in China. It is essential to link water resources with the whole electric power system (production, transmission, and consumption) rather than only part of the power system as in previous research. [ABSTRACT FROM AUTHOR]

In a modern and technological world that has a great demand for energy, a versatile energy market, and a renewed electric infrastructure capable of expanding the electric power system under the premise of universal access to electricity, that seeks to minimize the effects of climate change, and that requires an improvement in its reliability, security, and resilience, microgrids are born as one of the systems that have the potential to supply each of these requirements in order to guarantee an adequate decarbonization, decentralization, digitalization, diversification, and democratization of the future grid. However, the integration of microgrids into the electric power system will generate impacts that are currently under study. This paper identifies and analyzes the technical impacts in the electric power system due to the implementation of microgrids, based on what has been recognized in the literature, so that those who have purposes of installation, creation, innovation, and research of microgrids, such as grid operators, technology providers, companies, and researchers, can establish criteria and indicators through which the feasibility of projects involving microgrids can be determined. The concept, importance, and characteristics of microgrids are given, along with a technical justification of the impacts. In addition, technical impacts on some study cases of real microgrids around the globe are identified. Finally, an analysis of the identified technical impacts is offered, and conclusions are drawn. [ABSTRACT FROM AUTHOR]

This work presents a multi-parameter optical fiber monitoring solution applied to an underground power distribution network. The monitoring system demonstrated herein uses Fiber Bragg Grating (FBG) sensors to measure multiple parameters, such as the distributed temperature of the power cable, external temperature and current of the transformers, liquid level, and intrusion in the underground manholes. To monitor partial discharges of cable connections, we used sensors that detect radio frequency signals. The system was characterized in the laboratory and tested in underground distribution networks. We present here the technical details of the laboratory characterization, system installation, and the results of 6 months of network monitoring. The data obtained for temperature sensors in the field tests show a thermal behavior depending on the day/night cycle and the season. The temperature levels measured on the conductors indicated that in high-temperature periods, the maximum current specified for the conductor must be reduced, according to the applied Brazilian standards. The other sensors detected other important events in the distribution network. All the sensors demonstrated their functionality and robustness in the distribution network, and the monitored data will allow the electric power system to have a safe operation, with optimized capacity and operating within tolerated electrical and thermal limits. [ABSTRACT FROM AUTHOR]

The Golden Jackal Optimization algorithm (GJO) is used in this study to address the problem of optimal placement and sizing of single and multiple distributed generators (DGs) on the IEEE123 test system. The proposed approach attempts to minimize the total power loss of the system while respecting the voltage and power limits. The GJO algorithm is a new meta-heuristic algorithm inspired by the behavior of the golden jackal in the wild. The GJO algorithm is used to find the ideal location and sizing of DGs, and the results are compared with those obtained by other meta-heuristic techniques. According to the simulation results, the GJO method outperforms other metaheuristic algorithms in terms of problem-solving, while satisfying all constraints of the system. The proposed approach also demonstrates the effectiveness of the GJO algorithm in the solution of complex optimization problems in power systems. [ABSTRACT FROM AUTHOR]

This paper presents a method for refining the forecast schedule of renewable energy sources (RES) generation by its intraday adjustment and investigates the measures for reserving RES with unstable generation in electric power systems (EPSs). Owing to the dependence of electricity generation by solar and wind power plants (PV and WPPs, respectively) on natural conditions, problems arise with their contribution to the process of balancing the power system. Therefore, the EPS is obliged to keep a power reserve to compensate for deviations in RES from the planned generation amount. A system-wide reserve (mainly the shunting capacity of thermal and hydroelectric power plants) is used first, followed by other means of power reserve: electrochemical, hydrogen, or biogas plants. To analyze the technical and economic efficiency of certain backup means, mathematical models based on the theory of similarity and the criterion method were developed. This method is preferred because it provides the ability to compare different methods of backing up RES generation with each other, assess their proportionality, and determine the sensitivity of costs to the capacity of backup methods with minimal available initial information. Criterion models have been formed that allow us to build dependencies of the costs of backup means for unstable RES generation on the capacity of the backup means. It is shown that, according to the results of the analysis of various methods and means of RES backup, hydrogen technologies are relatively the most effective. The results of the analysis in relative units can be clarified if the current and near-term price indicators are known. [ABSTRACT FROM AUTHOR]

The 12th article proposes a hybrid technique by combining an evolutionary optimization technique, namely the modified invasive weed optimization with the conventional perturb and observe algorithm to enhance the search performance for the MPPT output of a PV system. It reports that the controller tuning parameter values calculated by an ant-lion optimization technique provide better performance than those calculated by whale optimization, gray wolf optimization, and particle swarm optimization. Solutions of the optimization problem obtained using an oppositional grasshopper optimization algorithm and several other algorithms including teaching learning-based optimization are compared. [Extracted from the article]

This article proposes a simple method to calculate a current vector trajectory for the enhanced operation of the electric power generation system based on a synchronous reluctance machine (SynRM). Owing to magnetic saturation and cross magnetization, the performance and the torque capability of a SynRM vary according to the position and the value of the stator current. State-of-the-art control methods usually assume parameters with constant values, especially the inductance, neglecting saturation, leading to possible uncertainty in the machine operation. Therefore, a current vector trajectory to operate this type of machine, as a generator, in an extended speed range, with enhanced performance and considering magnetic saturation is proposed. A straightforward algorithm based on the inductance characteristic of the machine is used to calculate the trajectory of the stator current vector. This trajectory is evaluated via the numerical simulation of an experimentally validated finite-element model of a SynRM. The results show that the proposed current vector trajectory can improve the torque capability to 5% concerning the estimated trajectory without considering saturation. Experimental results are also provided to demonstrate the enhanced operation of the generator. [ABSTRACT FROM AUTHOR]

Reliable short-term load forecasting is vital for the planning and operation of electric power systems. Short-term load forecasting is a critical component used in purchasing and generating electric power, dispatching, and load switching, which is essential for balancing supply and demand and mitigating the risk of power shortages. This is becoming even more critical given the transition to carbon-neutral technologies in the energy sector. Specifically, since renewable sources are inherently uncertain, a distributed energy system with renewable generation units is more heavily dependent on accurate load forecasts for demand-response management than traditional energy sectors. Despite extensive literature on forecasting electricity demand, most studies focus on predicting the total demand solely based on the previous-step observations of aggregate demand. With advances in smart-metering technology and the availability of high-resolution consumption data, harnessing fine-resolution smart-meter data in load forecasting has attracted increasing attention. Studies using smart-meter data mainly involve a "bottom-up" approach that develops separate forecast models at sub-aggregate levels and aggregates the forecasts to estimate the total demand. While this approach is conducive to incorporating fine-resolution data for load forecasting, it has several shortcomings that can result in sub-optimal forecasts. However, these shortcomings are hardly acknowledged in the load forecasting literature. This work demonstrates how limitations imposed by such a bottom-up load forecasting approach can lead to misleading results, which could hamper efficient load management within a carbon-neutral grid. [ABSTRACT FROM AUTHOR]

Currently, power electronics and AC machine drive systems are employed in numerous areas, such as in industrial processes, consumer electronics, electric vehicles (EVs), renewable-energy-source (RES)-based distributed generation (DG) systems, and electric power generation systems. As RESs such as wind and solar are attracting relatively more attention due to environmental issues caused by fossil fuel use, various RESs have been integrated into the utility grid (UG) as DG systems. As a result, the concept of a microgrid (MG), which constructs an electrical power system with DGs, energy storage systems (ESSs), and loads, has emerged. Recently, the DG-based MG has been regarded as a promising and flexible technology for those involved in constructing electric power systems. This article presents future technology and recent developments in applied power electronics. In this Special Issue, "The Recent Development of Power Electronics and AC Machine Drive Systems", four papers were published highlighting recent developments in this field. In addition, other topics beyond the coverage of the published articles are highlighted by a guest editor to address other trends and future topics related to the Special Issue. Through an in-depth investigation of recent development trends, this article seeks to encourage related studies in power electronics. [ABSTRACT FROM AUTHOR]

Global electricity generation by renewable energy sources and the electrification of the transportation system are gaining more importance to mitigate climate change. The dc system plays a significant role in these developments. To protect dc systems, dc circuit breakers with advanced technology are required that are fast and reliable. Various solid-state dc circuit breakers, such as $Z$ -source and $T$ -source circuit breakers, have been presented in the literature to meet the dc system demand; however, these topologies suffer from limitations such as high conduction loss, complexity in design, no physical isolation, and presence of negative current flow in load during reclosing. To overcome the aforementioned limitations, a bidirectional solid-state dc circuit breaker (BD-SSCB) that detects the overload or short-circuit faults and responds instantaneously to mitigate the fault current has been proposed in this article. The controllable shutoff function is much needed in applications where sudden load change occurs continuously during the normal operation, such as varying acceleration of an electric vehicle. The proposed BD-SSCB is validated using spice simulations and hardware experiments with varying system parameters for a system rating of 400 V/10 A. [ABSTRACT FROM AUTHOR]

As wind energy increases its share of total electricity generation and its integration into the power system becomes more challenging, accurately representing the spatio-temporal variability in wind data becomes crucial.Wind fluctuations impact power and energy systems, e.g. energy system planning, vulnerability to storm shutdowns, and available voltage stability support. To analyse such fluctuations and their spatio-temporal dependencies, time series of wind speeds at an hourly or higher frequency are needed. We provide a comprehensive evaluation of the global and mesoscale-model-derived wind time series against observations by using a set of metrics that we present as requirements for wind energy integration studies. We also perform a sensitivity analysis to find the best model setup of the Weather Research and Forecasting (WRF) model, focusing on evaluating the wind speed fluctuation metrics. The results show that using higher spatial resolution in the WRF model simulations improves the representation of temporal fluctuations; however, higher-spatial-resolution simulations often lower the correlations of wind time series with measurements. Thus, we recommend finer-spatial-resolution simulations for modelling power ramp or voltage stability studies but ERA5 rather than mesoscale simulations for studies where correlations with measurements are essential. We also show that the nesting strategy is an important consideration, and a smoother transition from the forcing data to the nested domains improves the correlations with measurements. All mesoscale model simulations overestimate the value of the spatial correlations in wind speed as estimated from observations. Still, the spatial correlations and the wind speed distributions are insensitive to the mesoscale model configuration tested in this study. Regarding these two metrics, mesoscale model simulations present more favourable results than ERA5. [ABSTRACT FROM AUTHOR]

The secondary energy on board has been gradually replaced by electrical power in more electric aircraft, effectively improving the fuel economy, reliability and maintainability of the aircraft, and has become an important direction of the aviation technology. As the core of the secondary energy system on board, the power system plays a key supporting role in the development of more electric aircraft. The innovative development of the power system and related technologies are the necessary basis to realize the improvement and global optimization of the aircraft comprehensive performance. Based on the concepts and characteristics of more electric aircraft, this paper analyzes and compares the electric power system architecture of three typical more electric aircraft, summarizes the key technologies supporting the development of more electric aircraft electric power system, and discusses the development trend of high voltage, direct current and intelligent more electric aircraft electric power system in the future. [ABSTRACT FROM AUTHOR]

This paper develops and analyzes four energy scenarios for Colombia that consider the El Niño phenomenon and the inclusion of renewable energies in the energy generation matrix for the period 2020–2035. A comparative analysis is presented between the results of the different scenarios proposed. The most relevant finding is the use of the reserve margin as an indicator of system reliability. A scenario which included 7214 MW of large-scale non-conventional renewable energy, 10,000 MW of distributed generation, and 12,240 MW of hydroelectric power was assumed, with a reserve margin of over 50%. Additionally, it was found that for the scenarios in which a generation capacity with non-conventional renewable energies of less than 10,000 MW in 2034 was assumed, the reserve margin of the system in the seasons of the El Niño phenomenon will be less than historical records of the system. Alternatively, it was found that the scenarios in which the inclusion of at least 9600 MW of the electric power generation capacity of non-conventional renewable energies proposed by 2034 offer benefits in the reduction in greenhouse gas (GHG) emissions, which contributes to the achievement of the emission reduction objectives of the Paris Agreement. [ABSTRACT FROM AUTHOR]

The fuel cell-based electric power generation system is playing a major role in the present electrical power distribution system. The fuel cell gives a nonlinear V-I curve. As a result, the extraction of fuel cell power is very difficult. To extract the peak power of the fuel cell, a Maximum Power Point Tracking (MPPT) technique is used. In this work, an Improved Beta-based Fuzzy Logic Controller (IBeta-FLC) is proposed to track the MPP with high speed. The proposed MPPT technique is compared with other hybrid MPPT techniques in terms of maximum power extraction, settling time, oscillations across MPP, tracking speed, and efficiency. The Proton Exchange Membrane Fuel Cell (PEMFC) stack gives high output current, and low output voltage. As a result, the overall system conduction losses are improved. So, in this work, a new Single Switch Universal Input-voltage Boost Converter (SSUIBC) is introduced to step-up the fuel cell output voltage. The features of the proposed boost converter are high voltage gain, less complexity in design, wide output operation, and less voltage stress across the switch. The proposed PEMFC fed boost converter system performance is evaluated successfully by using a MATLAB/Simulink window. In addition, the utilized boost converter is investigated experimentally by using an external DC-source. [ABSTRACT FROM AUTHOR]

Copyright of Ingenius, Revista Ciencia y Tecnología is the property of Universidad Politecnica Salesiana and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

With the use of hybrid renewable sources for example solar and wind turbines, an autonomous electric power generation system based on self-sufficient electric power generation is built in order to promote a smart and ecologically friendly environment. The three-phase inverter that links this scattered generating unit to the grid is in charge of ensuring that it is properly connected to the grid. While the energy produced by the hybrid unit is being utilized, it is also being stored in the batteries so that it may be used to transport power when other sources of power are not available, such as when the grid is down. This stand-alone power conversion and storage system is being built with the aid of power electronic converters and controllers, among other components, in order to ensure balanced power flow operation. To produce PWM pulses for the generator side converter, a PI controller is utilized. On the PV side, an improved PI controller is used to drive the SEPIC converter, which increases the transient responsiveness of the converter while it is being controlled by the controller. In order to communicate with the grid, the generated electricity is routed via a three-phase inverter that is controlled according to the DQ theory. The challenges connected with poor power quality are substantially resolved by the converters that have been presented. For simplicity of use, an automated control function has been introduced; in addition, an interactive MATLAB model of the system is being developed for minor and medium-scale microgrid applications; also, a prototype is being created to verify the simulation results. [ABSTRACT FROM AUTHOR]

Increasing the presence of non-conventional clean energy sources in Electrical Power Systems (EPS) is a global strategic goal. Particularly, photovoltaic systems are attractive due to their versatility, low maintenance cost, easy installation, noiselessness, etc. However, the integration of photovoltaic systems into EPS increases the necessary regulation actions performed by system generators due to stochastic fluctuations of solar radiation, especially on cloudy days. Even using complex models that consider many variables, solar irradiation and its corresponding photovoltaic power generation are difficult variables to forecast with accuracy in cloudy day scenarios. To address this problem, Energy Storage Systems (BESS) have been proposed as a solution to mitigate the variability of photovoltaic generation, which reduce the need to use traditional spinning reserves and provide auxiliary grid services. The BESS selection required to mitigate photovoltaic generation is directly related to the worst-case daily variability of photovoltaic generation in the short term. This paper proposes a practical estimation of daily perspective photo voltage solar generation curve in Electrical Power Systems. [ABSTRACT FROM AUTHOR]

The intermittent nature of wind generation makes essential the development of new tools to support the security assessment of electrical power systems (EPS) with this type of alternative energy source. In this context, the static security region (SSR) is a powerful tool that allows the steady-state security assessment of a EPS through visual inspections. The nomograms enable to carry out a fast analysis of the possible generation scenarios that a system can assume without violating its security limits. Therefore, the mains objective of this paper is to include a new security limit in the SSR, to complement the security assessment. This new limit is associated with intermittent generation sources, such as wind farms. For that purpose, an algorithm for the automatic construction of SSR is presented, where this new security limit was incorporated. The proposed methodology is applied to the well-known New England test system. The results presented validate and indicate the effectiveness of the proposed technique. [ABSTRACT FROM AUTHOR]

In recent years, the methods of controlling electrical machines have been witnessing increasing development to reduce torque and electric current fluctuations in electrical power generation systems from renewable sources such as wind energy. The generation of electric power from wind plants imposes the need for an efficient and more robust method in order to obtain fewer ripples in active and reactive power. In this work, a new fractional-order proportional-integral (FOPI) controller and intelligent PWM (IPWM) technique are proposed to control an existing asynchronous generator (AG) in variable-speed multi-rotor wind turbines (VSMRWTs). This proposed method depends on combining or using two methods, namely nonlinear area and fractional calculus, to obtain a more robust method and to reduce current and torque ripples. In the framework of this study, the electric power generation system consists of a 1.5 MW AG and VSMRWTs. The AG is controlled using a simpler and easily accomplished method called direct vector control, based on FOPI controllers and the IPWM technique (DVC-FOPI-IPWM). The maximum power point tracking (MPPT) method is used to generate the maximum energy from the VSMRWTs. The proposed DVC-FOPI-IPWM technique is modeled in the Matlab/Simulink platform to obtain good quality current and active power. Simulation results show that the proposed strategy reduces the ripples of torque, current, and active power compared to the classical technique. Moreover, the reduction ratio is about 85%, 99%, and 93.33% for the current, active power, and torque, respectively. [ABSTRACT FROM AUTHOR]