Wind Turbine Plant Research Articles

Design and Simulation of Smart Grid Based on Solar Photovoltaic and Wind Turbine Plants

Design and Simulation of Smart Grid Based on Solar Photovoltaic and Wind Turbine Plants

Offshore Wind Energy Validation Experiment Hierarchy

This paper provides a summary of planning work for experiments that will be necessary to address the long-term model validation needs required to meet offshore wind energy deployment goals. Conceptual experiments are identified and laid out in a validation hierarchy for both wind turbine and wind plant applications. Instrumentation needs that will be required for the offshore validation experiments to be impactful are then listed. The document concludes with a nominal vision for how these experiments can be accomplished.

Optimal energy management system for grid-connected hybrid power plant and battery integrated into multilevel configuration

A novel optimal energy management system (EMS) using a nonlinear constrained multivariable function to optimize the operation of battery energy storages (BESs) used in a hybrid power plant with wind turbine (WT) and photovoltaic (PV) power plants is proposed in this work. The hybrid power plant uses a configuration based on a battery-stored impedance-based cascaded multilevel inverter to integrate renewable energy sources (PV power plants and WT) and BESs into the grid. The new optimal EMS seeks for satisfying the demanded power while dispatching power between BESs to optimize their efficiency. A grid-connected configuration is implemented to assess the efficiency of the suggested supervisory control under changes in renewable energy (changes in wind speed and irradiation), and in a varying active and reactive powers’ request. The BES efficiency obtained from the suggested EMS is set side by side to the BES efficiency got from a conventional EMS and a model predictive control (MPC), both working based on the state-of-charge (SOC) of the BES and balancing power EMS. The results from MATLAB simulation and the experimental results with the real-time OPAL-RT simulator (OP4510, OPAL-RT) and dSPACE MicroLabBox show the effectiveness of the suggested approach and the improvement in long-term BES efficiency.

EXAMINATION OF THE RELATIONSHIP BETWEEN THE LOCATION OF WIND PLANTS AND THE EARTHQUAKE RISK: CASE STUDY TÜRKİYE

The significance of renewable energy resources has become increasingly prominent in light of the global population growth and the inadequacy of existing energy sources. Among these resources, wind energy stands out as a highly efficient option for sustainable power generation worldwide. Türkiye, with its capacity to accommodate both onshore and offshore wind turbines, has emerged as an attractive hub in this field. Given Türkiye's favourable geographical location, wind energy holds great potential in the country. Consequently, there has been a steady rise in the number of wind power plants established for electricity generation in Türkiye, along with an increase in their installed power capacity. However, the regions hosting these wind power plants face dynamic challenges, such as the risk of earthquakes, which can jeopardize their continuous operation. This study focuses on providing a comprehensive analysis of the causes of wind turbine damage, offering statistical insights into this subject. Additionally, the study discusses the various factors influencing the selection of suitable locations for wind turbine power plants, while also exploring relevant international laws and regulations. To initiate the research, an initial step involves creating a map illustrating the existing wind turbine plant locations. The study also presents statistical data regarding the distribution of wind turbine plants in earthquake-prone regions. Subsequently, by considering the earthquake map established in Türkiye's 2018 earthquake regulation, an assessment of earthquake risks is conducted based on the existing wind turbine power plant locations. As a result, new locations characterized by low earthquake risk and high wind efficiency are proposed for future wind power plant projects.

Harnessing solar and wind power for sustainable seawater desalination: A multi-criteria geospatial suitability analysis

Water and energy sustainability are major concerns of the world's nations at present. This research introduces a geographical decision-making model for strategically selecting optimal locations for seawater reverse-osmosis desalination plants (SWRODPs). Furthermore, it assesses the best electrification approach, considering onshore wind turbine (WT) or solar photovoltaic (PV) power plants. A representative case-study of the Egyptian Red Sea Coast Region (ERSCR) is considered to validate the proposed model. The study delineates nineteen assessment criteria for building an informed selection of SWRODPs' potential locations. Seven experts with at least ten years of expertise in desalination and renewable technologies were selected to obtain accurate assessment criteria that imitate the real-life selection process. The group best-worth method (GBWM) was employed to ascertain optimal weights for the geospatial model criteria. The findings indicate that a mere 6.11 % of the total land area is deemed suitable, with the remaining 93.89 % classified as restricted. The suitable area is divided into different suitability classes in which about 65.85 % of the suitable area is found good for establishing the SWRODPs, while about 23.65 % of suitable land is found of moderate suitability. Besides, about 9.21 % and 0.03 % of suitable lands are considered very good and excellent suitability for implementing SWRODPs' projects. Moreover, the analysis pinpointed 8 % of the ERSCR (∼12,810 km2) as a highly suitable area for PV installation, predominantly within Qusir, Ras Sidr, Hurghada, and Ataqa districts. Concurrently, a scant 0.15 % (∼244 km2) is optimal for WT in the Qusir district. Further, the results offer proposals to the authorities and energy investors with about 50,200 km2 and 39,858 km2 of the ERSCR suitable for establishing SWRODPs powered by PV and WT, respectively. Overall, the research findings are anticipated to bolster the UN's sustainable development goals 6 and 7 and align with Egypt's Vision 2030.

Технології електрогенерації та теплопостачання для підвищення енергетичної незалежності окремих територіальних громад

Russian attacks on Ukraine's energy system, which led to the blackout of entire cities and the termination of district heating, highlighted the risks and disadvantages of relying on large-scale district energy supply for communities. In this context, it is important to consider the development of the energy supply of communities in the direction of their energy independence. The purpose of the article is to form a list of electricity generation and heat supply technologies for increasing the energy independence of individual territorial communities, which are appropriate for implementation in Ukraine. The article considers the criteria for the analysis and selection of technologies for distributed power generation and heat supply. An analytical overview of the following power generation and heat supply technologies is presented: solar and wind power plants, gas piston and gas turbine plants, generators, batteries, co- and trigeneration plants, biofuel power plants and heat-generating boilers, heat pumps and electric boilers, and their grouping is performed according to the established criteria. All the considered technologies contribute to reducing the external supply of communities with energy resources and reducing losses during the transmission and distribution of electricity. Technologies that use renewable energy sources and local fuels are appropriate for implementation in communities in accordance with the availability of sufficient amounts of resources. Still, in most cases, they are not able to fully provide communities with electrical and thermal energy due to their insufficient quantity and high cost of equipment, such as batteries and heat pumps. Decisions regarding the implementation of a specific technology of distributed generation should be made after a thorough analysis of the conditions and possibilities of the energy supply of each individual community. This article is aimed at discussing the options of increasing energy independence and ensuring the reliability of the energy supply of territorial communities in Ukraine. Keywords: distributed generation, power generation, heat supply, renewable energy sources, cogeneration, biofuels, heat pumps.

Towards the implementation of Positive Energy Districts in industrial districts: an Italian case study

Owing to the opportunity to provide an annual positive energy balance and net-zero carbon emissions, Positive Energy Districts aim at fostering the energy transition of urban city centres. To fully support the decarbonization of cities, it may be interesting to extend their implementation to other energy intensive districts, such as cities’ industrial areas. In this regard, this paper addresses the opportunity to apply the Positive Energy District concept within the industrial area of a city in the South of Italy. A mixed-use building, the industrial wastewater treatment plant and an office building have been involved as users and equipped with a 250 kW wind turbine and multiple photovoltaic plants installed on the roof of the buildings, in parking areas and in an unused land, for a total peak power equal to 466 kW. The renewable-based plants’ generation has been simulated in HOMER Pro® software, on a quarter-hour basis, and an energy and environmental analysis have been performed using users’ real electric load profiles. The proposed configuration allows to save 55% of primary energy and carbon dioxide emissions compared to the baseline case where users’ electric energy demand is fully met by the power grid. In particular, the primary energy saving is equal to 1 GWh/y and the carbon dioxide emissions reduction is equal to 150 tCO2/y.

Machine Learning–Adjusted WRF Forecasts to Support Wind Energy Needs in Black Start Operations

Abstract The push for increased capacity of renewable sources of electricity has led to the growth of wind-power generation, with a need for accurate forecasts of winds at hub height. Forecasts for these levels were uncommon until recently, and that, combined with the nocturnal collapse of the well-mixed boundary layer and daytime growth of the boundary layer through the levels important for energy generation, has contributed to errors in numerical modeling of wind generation resources. The present study explores several machine learning algorithms to both forecast and correct standard WRF Model forecasts of winds and temperature at hub height within wind turbine plants over several different time periods that are critical for the anticipation of potential blackouts and aiding in black start operations on the power grid. It was found that mean square error for day-2 wind forecasts from the WRF Model can be improved by over 90% with the use of a multioutput neural network, and that 60-min forecasts of WRF error, which can then be used to adjust forecasts, can be made with an LSTM with great accuracy. Nowcasting of temperature and wind speed over a 10-min period using an LSTM produced very low error and especially skillful forecasts of maximum and minimum values over the turbine plant area.

Thermo-ecological analysis of the power system based on renewable energy sources integrated with energy storage system

Energy systems based on Variable Renewable Energy (VRE) such as solar energy (PV, PV/T) and wind energy (wind turbine) are intermittent by weather and climate conditions. This poses challenges for managing to obtain a stable energy supply. Microgrids based on VRE must accommodate the variability using, for example, energy storage. The second options for adjustment are backup generators or sources with firm capacity cooperating with VRE. The article presents an analysis of individual RES sources PV, PV/T system, wind turbine and biogas plant indicating the advantages of individual components and the possibility of their cooperation in a microgrid. The analysis for the assumed climatic conditions (location: Katowice, Poland) showed the benefits of the combination in the energy mix sources based on solar radiation and wind energy. The analysis also covers the use of the energy stored (based on electrolyser, hydrogen store and fuel cell) and presents the possibilities of using energy storage technology in various options of the energy mix. The most advantageous was a mixed system based on renewable energy sources using solar irradiation and wind energy with the stabilizing participation of a biogas plant - in this case, the capacity of the energy storage was fully used. In the further part of the article an exergo-ecological analysis using the TEC concept (thermo-ecological cost) is presented. TEC indicators for different versions of the energy mix were presented, analysing the systems in terms of natural resource management. The thermo-ecological analysis showed that the best energy mixes in terms of assessing the efficiency of natural resource management are systems that use the advantages of each component, supporting by energy storage.

Assessment and Enhancement of Uncertain Renewable Energy Hosting Capacity With/out Voltage Control Devices in Distribution Grids

Nowadays, with excessive integration of renewable energy sources (RESs), the distribution systems face several challenges due to exceeding the hosting capacity limit (HCL) of RESs. This article proposes a bi-stage approach to maximize the HCL considering RESs and load uncertainties. The first stage develops a multiobjective framework to adjust the system voltage profiles in a specific manner to avoid exceeding the voltage boundaries with high penetration of RESs. In the second stage, two processes are employed to maximize the HCL as the main objective function. In the first one, the photovoltaic (PV) and wind turbine (WT) plants are optimally allocated, while in the second process, a combination of three voltage control devices is proposed. A correlated multidimension probability uncertainty model is used to emulate the uncertainty of PV, WT, and load demand. Manta Ray foraging optimization (MRFO) algorithm is proposed to solve single-objective and multiobjective frameworks in the bi-stage approach considering the performance limits. The proposed approach is tested and validated on medium- and large-scale distribution systems. The effectiveness of the proposed MRFO is approved compared with two optimization algorithms. The proposed approach achieves up to 77.8% RESs integration from the total load demand for the tested systems.

Integrated Energy Management System for Microgrid based on Renewable Energy Sources

An effective energy management strategy is crucial to ensure highest system reliability, stability, operation efficiency and cost-effective operation of renewable energy sources based standalone microgrid. This paper presents an efficient energy management system for microgrid incorporated with Photovoltaic system, PMSG based wind turbine and energy storages including battery, fuel cell-Electrolyzer. Implemented hybrid modified invasive weed optimization with perturbed and observed method for PV systems to harvest maximum energy during partial shading condition. A sliding mode controller is implemented for boost converter to work as maximum power point tracker for wind turbine. Three solar plants and three wind farms are considered in this paper to establish 1 MW microgrid. Each wind farm is established with multiple wind turbines and similarly each solar plant having multiple PV modules. Each wind turbine and solar plant has their own inverter to synchronize at point of common coupling (PCC). Effective controllers are proposed to supply quality power at PCC under linear status and nonlinear status of single and three phase loads. Small size battery is considered to work under transient time and electrolyzer-fuel cell set will be working under steady state condition to reduce the cost of the system. TS-Fuzzy based controllers are designed for all the converters and implemented hardware-in-loop on a Real Time Simulator (RTS) by using OPAL RT technology/modules. The results unveiled that the RTS precisely emulate the dynamics of the microgrid with proposed controllers.

An open source Modelica implementation of the IEC 61400-27-1 type 4 wind turbine model for power system stability assessment

This paper presents a Modelica open-source implementation of the IEC 61400-27-1:2020 wind turbine and wind power plant models and proposes a modified version in which the high level control remains unchanged while an inner current loop is added together with a more detailed representation of the phase-locked loop. Accordingly, the dynamics of the output filter are also introduced within the generator system, which is now modeled as a current-controlled voltage source instead of a current injector inspired by recent work on grid forming controls. The original wind turbine model has been successfully validated, using both OpenModelica and Dyna ω o, a hybrid Modelica/C++ suite of simulation tools, with respect to Eurostag results considering the 2015 Neplan test case. In addition, satisfying performances of the modified generator and control systems were obtained. Finally, the wind power plant models were integrated into the IEEE 14 bus system by replacing one of the synchronous generators. • A Modelica implementation of IEC 61400-27-1:2020 wind turbine and power plant has been proposed. • A version with a current loop and a more detailed phase-locked loop is proposed. • The dynamics of the output filter are also introduced within the generator system. • The models have been successfully validated, using both OpenModelica and Dyna ω o. • Satisfying performances of the modified generator and control systems were obtained.

Data-Driven and Model-Based Control Techniques for a Wind Turbine Benchmark Model

Abstract: Wind turbine plants are complex dynamic and uncertain processes driven by stochastic inputs and disturbances, as well as different loads represented by gyroscopic, centrifugal, and gravitational forces. Moreover, as their aerodynamic models are nonlinear, both modelling and control become challenging problems. On one hand, high–fidelity simulators should contain different parameters and variables in order to accurately describe the main dynamic system behaviour. Therefore, the development of modelling and control for wind turbine systems should consider these complexity aspects. On the other hand, these control solutions have to include the main wind turbine dynamic characteristics without becoming too complicated. The main point of this paper is thus to provide two practical examples of development of robust control strategies when applied to a simulated wind turbine plant. Extended simulations with the wind turbine benchhmark model and the Monte–Carlo tool represent the instruments for assessing the robustness and reliability aspects of the developed control methodologies when the model–reality mismatch and measurement errors are also considered. Advantages and drawbacks of these regulation methods are also highlighted with respect to different control strategies via proper performance metrics.

Short-term scheduling of hybrid thermal, pumped-storage, and wind plants using firefly optimization algorithm

This paper presents a novel method based on an enhanced firefly algorithm (EFA) to solve scheduling hybrid thermal, pumped-storage, and wind plants. Since the scheduling problem is inherently discrete, basic EFA and binary encoding/decoding techniques are used in the proposed EFA approach. Optimal power values of thermal and pumped-storage units are determined separately in the presence of uncertainty caused by wind speed. The proposed method is applied to a real plant, including four pumped-storage units, 34 thermal units with different characteristics, and one wind turbine plant. In addition, dynamic constraints of upstream and downstream sources and constraints regarding thermal and wind units are also considered for finding the optimal solution. In addition, the proposed EFA is successfully applied to a real plant, and the results are compared with those of the three available methods. The results show that the proposed method has converted to a more optimal cost than the other methods.

Cooperative Operation Model of Wind Turbine and Carbon Capture Power Plant Considering Benefit Distribution

Increasing systematic carbon sinks and clean energy generation proportion are the main ways to reduce the carbon emission of power system. In order to promote wind power accommodation and reduce system carbon emissions, a cooperative operation model of wind turbine and carbon capture power plant (CCPP) is constructed. Then, the model is equivalently transformed into two sub-problems. One is the operation optimization sub-problem of cooperative alliance with the goal of maximizing the alliance benefit. The other is the benefit distribution sub-problem with the goal of fair distributing cooperative benefit. To protect participants’ privacy, the alternating direction method of multipliers (ADMM) is used to realize the distributed solution of the two sub-problems. Finally, the effectiveness of the proposed model is verified by an example, and the sensitivity analysis of the alliance benefit and system carbon emission is carried out with carbon price and carbon capture cost as the sensitivity factors. The example results show that: (1) By providing up and down regulation services to wind turbines, CCPP can obtain ancillary service income and help to reduce the declaration deviation of wind turbines, which can realize multi-win-win situation. (2) Carbon price affects both thermal power units and carbon capture equipment. So, compared with carbon costs, the carbon emissions and the alliance benefit are both more sensitive to carbon price. The model of the paper is constructed under the deviation punishment mechanism, and subsequent research can be expanded in combination with a more detailed imbalance settlement mechanism.

Implementation of Modified Multi-Objective Particle Swarm Optimization to multi-machine power system stability

This paper addresses a coordinated wind turbine equipped with a doubly fed induction generator, photovoltaic plant, and a fractional lead-lag stabilizer to enhance the low-frequency oscillation (LFO) in response to their effects on the power system under load conditions. To achieve better stability in the power system, the DFIG wind turbine and PV plant are equipped with a power oscillation damper (POD) in a practical form by single-input signal output. Although power system stabilizers (PSSs) are the first choice offered for multimachine power system stability, they cannot guarantee power system stability with different types of power plants and their interconnections. To get the high-speed response and the least steady-state error, the fractional-order lead-lag stabilizer is suggested. To save the initial price of equipping all generators with the stabilizer, only the best locations are selected using a probabilistic method formulated in the frequency domain. The optimal tuning of FL-L and POD variables is formulated by the optimization problem, and the developed version of particle swarm optimization is used to solve it. Finally, the suggested coordinated controller is implemented in the MATLAB tool. Moreover, the suggested controller is compared to other available controllers by several indices. The simulation results show that the proposed controller can provide acceptable performance in low frequency oscillation in large scale power systems. According to the simulation results, the damping ratio was modified from 0.1343 to 0.5773. It leads to a reduction in the settlement time from 3.65 s to 2.14 s. Also, the proposed modified optimization algorithm makes a faster and better global and local search compared to other optimization algorithms.

Hardware–In–The–Loop Assessment of Robust Fuzzy Control Solutions for Hydroelectric and Wind Turbine Models

The interest towards renewable energy resources is increasing, and in particular it concerns wind and hydro powers, where the key point regards their efficient conversion into electric energy. To this end, control techniques can be used to meet this purpose, especially the ones relying on fuzzy models, due to their capabilities to manage nonlinear dynamic processes working in different conditions, and affected by faults, measurement errors, uncertainty and disturbances. The design methods addressed in this paper were already developed and validated for wind turbine plants, and important results can be achieved from their appropriate design and application to hydroelectric plants. This is the key issue of the paper, which recalls some considerations on the proposed solutions, as well as their validation to these energy conversion systems. Note that works available in the related literature that consider both wind and hydraulic energy conversion systems investigate a limited number of common issues, thus leading to little exchange opportunities and reduced common research aspects. Another important point addressed in the paper is that the proposed control design solutions are able to take into account the different working conditions of these power plants. Moreover, faults, uncertainty, disturbance and model-reality mismatch effects are also considered when analyzing the reliability and robustness features of the derived control schemes. To this end, proper hardware-in-the-loop tools are considered to verify and validate the developed control schemes in more realistic environments.

A Unique Control Strategy and Power Management in Wind/Solar Renewable Energy Power System to Improve the Power Quality of Grid System

Hybrid energy generation which includes both wind and solar energy has grown exponentially in latest years, and this will continue. Power quality problems such as voltage-swells, voltage-sags, harmonic components, power factor, and inadequate voltage control are caused by intermittent various exposures and the incorporation of wind-turbine and Photo-voltaic power generating systems with the grid. A Static Compensator (STATCOM) is employed to enhance power-quality. The power quality enhancement method for grid-connected wind-turbine and photo voltaic power plants employing STATCOM is introduced in this paper. The framework of the proposed methodology describes in order to improve the transient voltage stability of the large-scale wind / solar hybrid system, the STATCOM reactive power compensation device is connected to the grid. The compensator is offered to further improve output parameters such as voltage THD, current THD and active power.

Optimization of Wind Energy Battery Storage Microgrid by Division Algorithm Considering Cumulative Exergy Demand for Power-Water Cogeneration

This study investigates the use of division algorithms to optimize the size of a desalination system integrated with a microgrid based on a wind turbine plant and the battery storage to supply freshwater based on cost, reliability, and energy losses. Cumulative exergy demand is used to identify and minimize the energy losses in the optimized system. Division algorithms are used to overcome the drawback of low convergence speed encountered by the well-known method genetic algorithm. The findings indicated that there is a positive relationship between cost, cumulative exergy, and reliability. More specifically, when the loss of power supply probability is 10%, compared to when it is 0%, the total cumulative exergy demand and total life cycle cost are reduced by 34.76% when the battery is full and 45.44% when the battery is empty and there is a 44.43% decrease in total life cycle cost, respectively. However, the more reliable system, the less exergy is lost during the production of 1 m3 freshwater by desalination integrated into wind turbine plant.

A Novel Nonsingular Terminal Sliding Mode Control-Based Double Interval Type-2 Fuzzy Systems: Real-Time Implementation

Extensive use of wind turbine (WT) systems brings remarkable challenges to the stability and safety of the power systems. Due to the difficulty and complexity of modeling such large plants, the model-independent strategies are preferred for the control of the WT plants which eliminates the need to model identification. This current work proposes a novel model-independent control methodology in the rotor side converter (RSC) part to ameliorate low voltage ride through (LVRT) ability especially for the doubly-fed induction generator (DFIG) WT. A novel model-independent nonsingular terminal sliding mode control (MINTSMC) was developed based on the principle of the ultra-local pattern. In the suggested controller, the MINTSMC scheme was designed to stabilize the RSC of the DFIG, and a sliding-mode supervisor was adopted to determine the unknown dynamics of the proposed system. An auxiliary dual input interval type 2 fuzzy logic control (DIT2-FLC) was established in a model-independent control structure to remove the estimation error of the sliding mode observer. Real-time examinations have been carried out using a Real-Time Model in Loop (RT-MiL) for validating the applicability of the proposed model-independent control in a real-time platform. To evaluate the usefulness and supremacy of the MINTSMC based DIT2-FLC, the real-time outcomes are compared with outcomes of RSC regulated conventional PI controller and MINTSMC controller.