Wind Generation Research Articles

Exploration of Alternatives to Reduce the Gap in Access to Electricity in Rural Communities—Las Nubes Village Case (Barranquilla, Colombia)

The global crisis associated with COVID-19 and the Russia-Ukraine conflict has affected progress towards the Sustainable Development Goals (SDGs). Projections for SDG7 (Ensure access to affordable, reliable, sustainable, and modern energy for all) indicate a slowdown in the pace of electrification. Thus, the problem of poverty will persist in many regions as long as access to electricity remains difficult. This work analyzes some solutions to the lack of electricity supply in a rural community using organic waste from its economic activity and the integration of other available renewable sources to make electricity affordable and reliable. A model that minimizes the levelized cost of energy and restricts the proportion of annual energy not supplied to less than 5% of the community’s annual demand optimizes the performance of off-grid and on-grid systems. These systems have in common the production of electricity from biogas produced from swine manure, supplemented with wind and solar generation. Batteries and diesel generators support the operation of off-grid systems. As expected, the grid-connected system presented the best performance; however, the result reaffirms the need for governments to ensure the policy and infrastructure conditions that facilitate the grid connection of vulnerable communities to achieve SDG7.

Integration of wind and solar energies with battery energy storage systems into 36-zone Great Britain power system for frequency regulation studies

Variable-speed wind generators (VSWGs) and solar Photovoltaic (PV) units are being broadly employed as the main renewable energy sources in large-scale transmission power networks. However, they can cause system stability challenges following power imbalances since they provide no inertial and governor responses. In this study, generic dynamic models are developed for VSWGs, PVs and battery energy storages systems (BESSs) which include inertia emulator and droop-based frequency control schemes. These models are suitable for transmission systems stability studies and are integrated into 36-zone Great Britain (GB) power system in DIgSILENT PowerFactory. It is a very useful benchmark for academic research and industrial sectors to undertake feasibility studies for renewable energy integration into GB power system. However, it is not an exact equivalent of the real GB power system. The dynamic time-domain simulations and modal analysis are provided and justified to investigate how PV, Wind and BESS units affect the system frequency response. A sensitivity analysis is also carried out against several factors to demonstrate the dynamic performance of the test system incorporating the generic models for VSWGs, PVs and BESSs. These are associated with units’ frequency response and system frequency changes under renewable energies’ penetration levels of 20 %, 25 %, 50 %, 60 % and 75 % of system demand.

Enhanced Multiobjective Optimization Algorithm for Intelligent Grid Management of Renewable Energy Sources

Optimal scheduling of microgrids (MGs) is a crucial component of smart grid optimization, playing a vital role in minimizing energy consumption and environmental degradation. However, existing methods tend to consider only a single optimization and do not consider the multiobjective optimization problem of MGs in a comprehensive and integrated way. This study proposes a comprehensive multiobjective optimal scheduling methodology for renewable energy MGs, incorporating demand-side management (DSM) considerations. Initially, a DSM multiobjective optimization model is formulated, focusing on the load shifting of controllable devices within the MG to refine the electricity consumption structure. This model contemplates the renewable energy consumption of the MG, customer electricity purchase costs, and load smoothness. Subsequently, a multiobjective optimization model for grid-connected MGs, encompassing wind and photovoltaic power generation, is constructed with the dual objectives of economic and environmental optimization for the MG. Ultimately, a multimodal multiobjective optimization algorithm, amalgamating a local convergence index and an environment selection strategy, is proposed to solve the model. The experimental results show that compared with other methods, the proposed method in this paper can reduce the integrated cost by 32.6% and 38.9% in summer and 19.4% and 40.2% in winter. This stands out as a unique contribution in the field of MG optimization, as it integrates DSM considerations into a multiobjective optimization model. This methodology achieves a balance between minimizing energy consumption and environmental degradation while also enhancing economic efficiency.

The DC-side active filter with dual-buck full-bridge inverter for wind generators

The DC-side active filter with dual-buck full-bridge inverter for wind generators

Research on improving low-frequency oscillation characteristics of wind power grid-connected power system with doubly-fed wind generator based on virtual impedance power system stabilizer

Research on improving low-frequency oscillation characteristics of wind power grid-connected power system with doubly-fed wind generator based on virtual impedance power system stabilizer

EMT Model of 20-MW Wind Generator for Real-time Simulation of HVDC Networks

As modern trends demand efficient methods to massively and promptly exploit clean energy, there is an urgent need of solutions that can help the ambition of accelerating the development and integration of larger scale energy systems with the capacity to extract, store, and utilize huge amounts of renewable energy sources. In view of this, the rated power output of the wind generation technology is expected to significantly increase in the near future to enable multi-gigawatt roll outs, e.g. the European plans for Offshore infrastructure development in the North-Sea. Besides, gigantic energy systems shall transmit the power to onshore interconnected systems via HVDC transmission. This paper introduces an EMT model of a 20 MW wind generation system with the conventional back-to-back converter replaced by a combination of an AC to DC converter and a DC to DC converter. While the need of such systems is acknowledged in the literature, the design and performance analysis of high power implementation of such systems have not been addressed yet. The proposed system operates at a voltage level of 100 kV, which can directly transfer power through HVDC interconnection. The designed control aspects are outlined and the resulting dynamic response obtained from realtime digital simulation (RTDS) are discussed. The presented wind generator concept can help in reducing the size of a planned energy system by requiring lesser system components. Also, the system efficiency can be enhanced by decreasing the number of power conversion stages.

МАТЕМАТИЧЕСКОЕ И КОМПЬЮТЕРНОЕ МОДЕЛИРОВАНИЕ ПРЕОБРАЗОВАТЕЛЯ ДЛЯ МАЛОЙ ВЕТРОУСТАНОВКИ

Relevance The importance of using non-traditional energy sources is evidenced by the decision to provide subsidies from the federal budget for state support for technological connection of generating facilities operating on the basis of the use of renewable energy sources (RES). As part of the state policy aimed at improving energy efficiency and developing the use of renewable energy sources, mechanisms are provided to support the stimulation of electric energy production by generating facilities operating on the basis of the use of renewable energy sources. Aim of research In this paper, the development and research of a power converter for wind energy that meets the requirements of highly efficient alternative energy sources is carried out. The developed converter can be used by models. The article is devoted to the analysis of the weaknesses of traditional power converters and the development of solutions to improve their efficiency and reliability. Research methods This work consists in creating a computer model for the wind energy system in the Matlab/Simulink program. The model is focused on the characteristics of a specific wind turbine and includes elements for converting and controlling electricity, such as a generator, rectifier and inverter, as well as a component that simulates the physical operation of a windmill. The selected components make it possible to accurately simulate both the electrical and mechanical parts of the wind power system. Results The authors consider the possibility of developing a power converter for wind energy that meets the requirements of highly efficient alternative energy sources. Mathematical and computer modeling of a converter for a small wind turbine has been performed. The novelty of the work consists in the development of a model in the Simulink program of the Matlab converter software package for a small wind turbine, taking into account the parameters of a WH8-10000W type wind generator and consisting of a virtual PMGM, a rectifier, a pulse inverting stabilizer, an inverter, which were taken from the Specialized Power Systems library, as well as a system simulating the mechanical part of a wind generator. This article presents the results of the calculation and selection of the elements of the electrical schematic diagram of the developed and investigated converter of a small wind turbine. Based on the results of a study performed using computer simulation of a converter for a small wind turbine with a power source from a wind generator, graphs of converter currents and voltages were constructed and analyzed. Acknowledgments: The research was carried out using a grant from the President of the Russian Federation in 2022-2024 for young scientists and graduate students carrying out promising scientific research and development in priority areas of modernization of the Russian economy. Grant recipient is Regina Tagirovna Khazieva. The priority direction of modernization of the Russian economy (direction of competition No. SP-2022 of the Grant Council of the President of the Russian Federation) is «Energy Efficiency and Energy Saving, Including Issues of Developing New Types of Fuel». Research topic: «Development and Research of a Filter Compensating Device to Improve the Quality of Electricity».

Enhancing decentralized frequency regulation approach in mixed source of generation diversified with wind and PV integration deploying artificial gorilla troops algorithm

Nowadays, the penetration of renewable energy sources, mainly wind and solar photovoltaic systems, into the existing power systems, destabilizes the grid, especially in the aspect of frequency regulation. AGC is one of the most important tasks in this mixed-generation environment to maintain the balance between the generated and consumed electricity, thus keeping the system frequency at an acceptable level. Therefore, AGC needs to be optimized for the noisy and volatile output of RESs. AGTA is a recent optimization method developed based on the social foraging behavior of gorillas, being a sophisticated way of exploration and exploitation. Therefore, the method is implemented in AGC. By mimicking the social behaviour and foraging strategy, the group gives rise to a new technique for enhancing the efficiency and response of the AGC system in light of wind and PV energy generation variation. A two-area power system model has been formulated characterized by the existence of wind and PV generation in addition to the conventional sources of the power system. This model is meant to simulate diverse situations to give an idea as regards the capability of the new algorithm to enhance grid stability and adaptability. The simulated results show that the proposed AGTA significantly surpasses other conventional optimization methods for AGC and results in an effective frequency control strategy. it confirms the potential of the AGTA from a new perspective in providing a feasible option for decentralized frequency regulation in a multi-generation landscape.

On the issue of applying the dynamic thermal rating in electric power distribution system

The article considers separate studies and review articles on dynamic thermal rating system in power transmission lines and electrical equipment. Available researches of foreign authors are mainly devoted to forecasting algorithms, model-ing methodologies and implementation of dynamic thermal rating in order to increase the capacity of power transmis-sion lines. It is shown that for the tasks of planning and management of the electric power system in Russia, the need to study and coordinate domestic and foreign developments on the assessment of the capacity of power transmission lines and power distribution is currently relevant. The expansion of residential areas increases the load on electric distribution network due to the shift of maximum power consumption. The currently dynamically changing conditions of electricity consumption direct attention to the development of new technological concepts and the applicability of the existing approaches to assessing the capacity of electricity transmission lines to distribution networks. Available research on dynamic thermal rating in electric distribution networks has focused much attention on both the potential problems and benefits of its implementation in the integration of distributed generation based on the renewable energy sources, in particular wind generation. The ambiguous impact of dynamic thermal rating systems on the reliability of the electric distribution network and the need for their reasonable use, as well as a significant lack of research in relation to cable distribution networks and consistency in assessing their capacity depending on the cable insulation material are being not-ed. Few studies have verified the adaptation of the state-of-the-art approach of dynamic thermal rating of overhead transmission lines to cable lines for predicting parameters corresponding to operational objectives. The research results can be useful in the development and modernization of metering systems, in which new functions of power loss moni-toring and automated determination of distribution network reliability indicators are implemented, which will allow, within the framework of “smart grids”, to ensure the required level of reliability of power supply to consumers.

A Novel Sliding Mode Control Strategy for Remote Area Power Supply Management

This paper introduces a comprehensive Energy Management Strategy (EMS) control for a Remote Area Power Supply (RAPS) system, that includes a wind generation subsystem, a battery bank, and a variable local load. The primary objectives of the EMS control are to meet the load power demand, adapt to wind fluctuations, and extend the battery bank’s lifespan. To achieve these objectives, the EMS controller determines the operation modes of the wind generation and battery bank. The study includes a detailed design of a Sliding Mode Controller (SMC) for the boost converter associated with wind power generation. This study offers valuable insights into controlling standalone wind-dominated systems in remote areas, offering solutions to enhance stability by reducing voltage ripple and improving performance through optimizing settling time. Simulations confirm the effectiveness of the proposed technique in managing load and wind variations, outperforming conventional PI controllers.

Enhanced Randomized Harris Hawk Optimization of PI controller for power flow control in the microgrid with the PV-wind-battery system

Microgrids, characterized by their ability to work individually or in combination with the main power system, play a pivotal role in addressing the growing demand for reliable and sustainable energy solutions. This work concentrates on the integration of sustainable energy sources, specifically photovoltaic (PV), and wind generation and a battery storage system within a microgrid framework. Additionally, a power flow control strategy is implemented to enhance the dynamic behaviour and stability of the microgrid. The proportional-integral (PI) controller is a fundamental component in regulating the microgrid’s power flow, ensuring optimal performance under varying operating conditions. However, tuning the PI controller parameters is a difficult task because of the dynamic and nonlinear nature of renewable energy sources. In this work, the application of the Enhanced Randomized Harris Hawk Optimization (ERHHO) to fine-tune the PI controller is proposed, using the algorithm’s ability to mimic the hunting behaviour of hawks in finding optimal solutions. The PV-Wind-Battery microgrid system is modelled, and the proposed algorithm is employed to optimize the PI controller parameters for efficient energy management. The ERHHO algorithm’s exploration-exploitation balance is harnessed to navigate the complex solution space and converge to optimal PI controller settings, thereby enhancing the microgrid’s stability and performance. The study evaluates the effectiveness of the proposed ERHHO-based PI controller tuning through comprehensive simulations. Performance metrics such as transient response, overshoot, settling time, and steady-state error are analysed to validate the robustness and efficiency of the proposed method. Compared to its nearest optimization algorithm, with the proposed algorithm rise time is reduced by 50%, overshoot is reduced by 75%, settling time is reduced by 66%, and finally, a percentage of reduction of steady-state error is 45%. The outcomes of this research contribute to the advancement of microgrid control strategies, offering a novel approach to PI controller tuning in the context of diverse renewable energy sources. The integration of the Harris Hawk Optimization algorithm provides a promising avenue for enhancing the operational efficiency and reliability of microgrids, paving the way for sustainable and resilient energy systems in the aspect of growing energy landscapes.

Power flow analysis in a distributed network for a smart grid system

<span>This article presents the implementation of a hybrid renewable energy-based smart grid in a distributed system. Photovoltaic (PV) and wind generation are variable and time-dependent, yet they are very efficient and correlated, making them perfect for a two-source hybrid system. To maximize the generated power, using the maximum power point tracker (MPPT) technique, the incremental conductance (IC) algorithm is employed. The proportional integral (PI)-based MPPT controller is chosen to improve the efficiency of conventional MPPT controllers. A battery system is implemented as an energy management system (EMS) to aid in transferring or managing the high load throughout peak and off-peak hours. The proposed system uses an optimization technique called genetic algorithm (GA) to control the inverter voltage. The GA-tuned PI controller performs efficiently and has less harmonic distortion than the traditional sinusoidal pulse width modulation (SPWM) control method. The designed system uses real-time measurable parameters as inputs and is simulated in Matlabtool. The system generates 42 kW of solar power and 250 kW of wind power; the total harmonic distortion (THD) value is 5% less than the SPWM technique. For future work, flexible alternating current transmission system (FACTS) devices can improve the power quality and lower the oscillations.</span>

Renewable Energy Sources constrained Generation Scheduling of Thermal Units in a Regulated Power Industry

Renewable energy production technologies use resources directly from the environment to generate electric power. These energy sources such as sunshine, wind, tides and biomass are some of the more popular gifts from the nature. The renewable energy resources emit nothing into atmosphere or never produce green house gas or pollute the environment at all. Even if the renewable energy sources are safe to the atmosphere, these resources meet out smaller percent of power requirement internationally This paper a population based optimization algorithm of Corona Virus Herd Immunity Optimizer (CVHIO) is proposed to solve the renewable energy constrained generation scheduling problem. The objective function of the problem is to minimize the total operating cost of hybrid system with satisfying standard operating constrains of thermal, wind and solar power plants. Initially the variables of the problem are effectively optimized using CVHIO algorithm. . Numerical example with IEE 39 bus test system (ten thermal twenty four hour) with an equivalent Solar and Wind generators are considered to prove the performance of CVHIO approach.

Retrofit Planning and Flexible Operation of Coal-Fired Units Using Stochastic Dual Dynamic Integer Programming

The continuous growth of wind power requires greater power system operational flexibility owing to the variability and uncertainty of wind power generation. Retrofitting existing coal-fired units is a demonstrated cost-effective method for improving system flexibility. This study proposes a decision support tool that provides optimal investment decisions to enhance power system operational flexibility. A novel flexibility retrofit planning (FRP) model is proposed in which the embedded operational problem is a stochastic mixed-integer nonlinear programming (SMINLP) unit commitment problem. In the operational unit commitment model, novel mixed-integer nonlinear formulations are proposed to represent the coal-fired unit attribute (minimum power output, startup and shutdown times, and maximum ramp rate) modifications after retrofitting. A new solution method based on the Benders decomposition (BD) and stochastic dual dynamic integer programming (SDDIP) algorithms is proposed to solve the proposed FRP model. The modified IEEE 39-bus, 57-bus, and 118-bus test systems were used to verify the effectiveness of the proposed model and solution method. The results demonstrate that the proposed FRP model can balance the retrofitting and operational costs to minimize the total cost and accommodate more wind generation. The proposed solution method is computationally efficient for solving FRP models.

Application of DC/AC converters in self-contained power supply systems based on wind generators in the conditions of the Arctic Shelf

Application of DC/AC converters in self-contained power supply systems based on wind generators in the conditions of the Arctic Shelf

МОДЕЛИРОВАНИЕ И АНАЛИЗ РЕЖИМОВ РАБОТЫ ЭЛЕКТРОЭНЕРГЕТИЧЕСКИХ СИСТЕМ С ВЫСОКОЙ ДОЛЕЙ ВОЗОБНОВЛЯЕМЫХ ИСТОЧНИКОВ ЭНЕРГИИ

The article examines the features of operation of electric power systems (EPS) with a high share of renewable energy sources (RES), such as solar and wind generation. The problems associated with the integration of RES into the power system, including issues of dynamic stability and reliability, are considered. Modeling of various scenarios of EPS operation with a high level of RES integration was carried out, which allows us to assess the impact of these factors on the stability of the system and propose measures to improve its reliability. The results obtained can be used to develop strategies for effective management of power systems in the context of an increasing share of RES.

Turning toward a smart region by implementing a hybrid power system

Distributed generation (DG) especially energy acquired from renewable energy sources (RES) plays a significant role in modern power sector due to high carbon emissions around the globe. Its emerging potential is feasible by implementing microgrids as they are beneficial for networks in terms of increasing flexibility and stability, providing frequency and voltage support, power factor compensation etc. This makes the investment into microgrid incorporating RESs attractive, while at the same time reducing overall investment in the grid. Higher cost and stochastic nature of intermittent RES are complications for the implementation and operation of such solutions. This paper will analyse economic feasibility of hybrid power system (HPS) implementation consisting of a wind generator (WG), a photovoltaic system (PVS), gas combined heat and power plant (CHP) and storage batteries. Each of the elements is optimized according to power demand and RES’s potential. Technical analysis of the grid integration, parallel operation of the system and the grid is analysed with an example of a real medium-voltage distribution network operating in Bosnia and Herzegovina by using quasi-dynamic load flow simulation of one-week time-period. Finally, different operating mechanisms and strategies will be proposed, following the minimal power form the grid premise to satisfy maximum usability of RES’s potential. It is shown that implementing such HPS would be beneficial in terms of both economy and, ecology, as well as in reducing energy losses. Besides, it will reduce power supplying costs and energy losses, as well as and secure better exploitation and utilization of natural renewable energy sources. These technologies positively affect power network by decreasing the risk of network-components overloading, better exploiting the power-generation facilities based on renewable resources and positively impacting voltage profiles. Similar places, situated on remote locations, may use this analysis as an example to follow, to reduce their costs of electricity, acquire more reliable and sustainable power supply, and embrace green future.

An Effective Spinning Reserve Allocation Method Considering Operational Reliability With Multi-Uncertainties

Spinning reserve (SR) is a crucial resource for ensuring power system reliability by lowering operational risk. The operational risk is contingent on the unpredictability of renewable energy as well as the replacement rate of electrical devices in relation to operating conditions. Previous research on SR allocation ignoring the condition-dependent outage replacement rate (CDORR) of electrical equipment may have allocated insufficient SR capacity that cannot adjust for unanticipated power imbalances. In addition, the introduction of CDORR and various multi-uncertainty scenarios into existing SR allocation models may incur a significant computational cost. This work presents an efficient SR allocation model that takes operational reliability under multi-uncertainties into account (e.g., wind output randomness, load fluctuations, generator and transmission contingencies with CDORR). Analytical expected energy not served (EENS) formulations based on the sensitivity method are derived to estimate the operational risk under multi-uncertainties, thereby obviating the need for iterations in large uncertainty scenarios. We present an improved relaxation method based on the McCormick envelope to further enhance the model's tractability. The proposed tangent plane cut collection strategy improves the computational efficiency by reducing the redundant envelope region. Results demonstrate that the proposed method benefits the economy by considering operational reliability and accelerates computational speed with reasonable accuracy.

Comparative Analysis of Low Voltage Ride Through Techniques of DFIG Connected to Grid using AI Techniques

The requirement for clean and eco-friendly energy initiated the production of renewable energy. Wind energy promises attractive features such as bulk power production and reduced maintenance cost. Advancement of technologies in the field of wind turbines and generators made the gates open for attractive investments. Adjustable-speed wind turbines tied to Doubly Fed Induction Generators (DFIG) became the most excellent choice of power utilities due to their low-cost power converters and four-quadrant control of useful and wattless powers. The ability to extract a high amount of power for a specified wind speed is a major advantage of DFIG which attracted Power system Operators (PSOs). Low voltage ride-through and wattless Spower support to the grid are estimated and compared using conventional PI controllers, Artificial Neural Network (ANN), and Random Forest Optimization (RFO) algorithm.

Moringa oleifera Seeds Potential as Biofuel via Thermal Conversion Method Based on Morphological and Chemical Content Evaluation

The 26th UN Climate Change Conference of the Parties (COP26), last held in Glasgow, Scotland, in November 2021, encouraged countries to keep global warming below 1.5 degrees Celsius. On the other hand, fossil fuels are still dominant as a primary source for power generation. In order to keep the temperature target viable, clean and renewable fuel is needed immediately. Biomass is a promising alternative for future energy sources, which has several advantages compared to wind and solar power generators. Atmospheric carbon dioxide is absorbed by biomass for its growth, making it a carbon-neutral fuel. Moringa oleifera (MO) has big potential compared to other lignocellulosic biomass based on its growth resilience in a wide range of climates. MO seeds contain highly valuable chemical products in the form of lipids and carbohydrates that can be converted into fuel using pyrolysis. Morphology and surface chemical content testing using SEM-EDX show that the average MO seed particle has spherical geometry, which is desirable because it has the smallest contact area compared to other shapes. Chemical analysis concludes that MO seeds have 73 and 23 wt.% carbon and oxygen, respectively. Trace inorganic elements are also present, such as Mg, Al, P, S, K, and Ca, which can be beneficial for the thermal conversion process because they are able to provide a catalyst effect and can be further utilized as fertilizer.