Farm Power Research Articles

A comprehensive review on applications of multicriteria decision‐making methods in power and energy systems

Energy has been considered as one of the essential needs of mankind along with air, water, and food and witnessed evolution of civilization since evidence of human life. Managing energy resources is one of the challenging problems being capital intensive. Addressing this involves critical thinking and decision making with all possible aspects, technically known as set of primary and secondary criteria. There exist a number of literature sources addressing applications of multicriteria decision-making (MCDM) in different energy-related areas. Some are focusing on energy policy making, few are explaining site selection of solar PV, wind farm, and hydro power plants, and a few are describing applications in load management. Moreover, a few literature in this field elaborates various MCDM methods and their applications. In this article, an extensive and exhaustive study is carried out incorporating almost all possible applications of MCDM in renewable energy area. Various energy-intensive applications are mapped with MCDM methods along with governing sensitive parameters. Hence, this study facilitates practicing engineers, decision-makers, academician, and researchers to identify areas and MCDM techniques researched over the past decade in energy sector for planning, managing, selecting renewable resources, etc.

Mesoscale simulations of a real onshore wind power base in complex terrain: Wind farm wake behavior and power production

Sustainable development of wind power is challenging due to the difficulty in detecting farm-to-farm wake. In this work, the wind farm wake and power production of Zhangbei wind power base under various wind and topography are studied using the mesoscale weather research and forecasting model coupled with a wind farm parameterization. The results show that the farm wake is closely related to wind and topography. The maximum wind deficit that occurs in the medium prevailing wind at isolated and mountainous regions are 2.5 m/s and 0.5 m/s, respectively. The farm wake recovers downstream 20–35 km or more in isolated wind farms and about 6 km or less in mountainous wind farms, which can be neglected vertically higher than twice and fourfold diameters above the hub height. Moreover, the wind farms fully utilize the terrain acceleration outperform those located in the lower areas at the windward of the hill. The uncoordinated wind farm region with the minimum average normalized power of 0.47 is detected, which is attributed to the dense layout and no reasonable buffer zone along with the prevailing wind. It is imperative to perceive these and provide potential solutions to promote the sustainable development of wind power.

Методика синхронизации подачи энергии от ветрогенераторного парка

Wind turbines and wind farms can be connected to the major electricity distribution system. This paper presents the research results on synchronization of wind farm power supply into the utility grid depending on parameters of the grid at the moment. Measurement time gets synchronized with the external time signal delivered from a navigating system like GLONASS. This can help eliminate antiphase operation of individual wind turbines. Connection diagrams and the whole methodology presented in this paper aim to make wind farm power supply into the grid more effective and loss-eliminating.

Floating Offshore Vertical Axis Wind Turbines: Opportunities, Challenges and Way Forward

The offshore wind sector is expanding to deep water locations through floating platforms. This poses challenges to horizontal axis wind turbines (HAWTs) due to the ever growing size of blades and floating support structures. As such, maintaining the structural integrity and reducing the levelised cost of energy (LCoE) of floating HAWTs seems increasingly difficult. An alternative to these challenges could be found in floating offshore vertical axis wind turbines (VAWTs). It is known that VAWTs have certain advantages over HAWTs, and in fact, some small-scale developers have successfully commercialised their onshore prototypes. In contrast, it remains unknown whether VAWTs can offer an advantage for deep water floating offshore wind farms. Therefore, here we present a multi-criteria review of different aspects of VAWTs to address this question. It is found that wind farm power density and reliability could be decisive factors to make VAWTs a feasible alternative for deep water floating arrays. Finally, we propose a way forward based on the findings of this review.

Coordinated optimal control of active power of wind farms considering wake effect

In a large-scale wind farm, under the influence of the wake effect, the single-machine maximum power extraction control strategy would not be able to function at the ideal optimal value. It is important to study the coordinated operation strategy of the wind farm under the wake effect to improve the output power of wind farms and improve the economic benefit. In this paper, a practical wake model called the PARK model is used and a wake superposition model based on energy balance is derived. Based on these models, an optimization problem is formulated to maximize the output power of the wind farm considering the wake effect. Taking the Horns Rev offshore wind farm as an example, the stochastic points method, particle swarm optimization, and the pattern search algorithm are implemented and compared with the single-machine maximum power extraction algorithm. Test results show that the particle swarm optimization and the pattern search algorithm have better performance. The output power of the wind farm increases by about 10 percent. The particle swarm optimization requires less computation while the pattern search algorithm obtains better and more practical results. Finally, the pattern search algorithm is used to improve economic benefits under different wind conditions.

A new wind power forecasting algorithm based on long short‐term memory neural network

Wind power is one of the most large-scale new energy sources. But wind power instability will affect power grid safety, which is in a great need for wind power forecasting algorithms. To accurately predict wind power and reduce power grid fluctuations, it proposes a new wind power forecasting (WPF) algorithm based on long short-term memory (LSTM) neural network using wind farm real operation data. First, the wind farm power data are de-averaged and divided into two different sets in order to meet the requirements of the algorithm. Then, structure of the LSTM neural network is designed and hyper-parameters are adjusted to improve accuracy of forecasting. Finally, the definite LSTM neural network is used for forecasting the power data in time series to derive the power forecasting value, which is reduced and evaluated according to the original size. The results show that compared with other forecasting methods, in short-term WPF at different time scales, this algorithm has smaller errors in power forecasting results, which is also suitable for long-term WPF.

A scenario-based optimal dispatch for joint operation of wind farms and combined heat and power plants considering energy flexibilities in heating networks

A scenario-based optimal dispatch is proposed for joint operation of a wind farm and combined heat and power (CHP) plant considering energy flexibilities in heating networks. First, the heating network is modelled, and energy flexibility is used to improve the flexible adjustment ability of the CHP plant. Then, considering the uncertainty of wind power, a scenario-based optimal dispatch model for wind farms and CHP plants with heating networks is proposed to maximize the revenue expectation of the joint operation. The simulation results show that the joint operation revenue is improved compared with that of independent operation. Considering the energy flexibilities in heating networks, the CHP plant in the joint system can compensate for the fluctuations in wind power output, promote the integration and consumption of wind power, and reduce the penalty cost caused by the uncertainty of wind power.

A new three-dimensional wake model for the real wind farm layout optimization

The utilization of wind energy has attracted extensive attentions in the last few decades around the world, providing a sustainable and clean source to generate electricity. It is a common phenomenon of wake interference among wind turbines and hence the optimization of wind farm layout is of great importance to improve the wind turbine yields. More specifically, the accuracy of the three-dimensional wake model is critical to the optiamal design of a real wind farm layout considering the combinatorial effect of wind turbine interaction and topography. In this paper, a novel learning-based three-dimensional wake model is proposed and subsequently validated by comparison to the high-fidelity wake simulation results. Moreover, due to the fact that the inevitable deviation of actual wind scenario from the anticipated one can greatly jeopardize the wind farm optimization outcome, the inaccuracy of wind condition prediction using the existing meteorologic data with limited-time measurement is incorporated into the optimization study. Different scenarios including short-, medium-, and long-term wind data are studied specifically with the wind speed/direction prediction errors of [Formula: see text] 0.25 m/s, [Formula: see text] 5.62 [Formula: see text], [Formula: see text] 0.08 m/s, [Formula: see text] 1.75 [Formula: see text] and [Formula: see text] 0.025 m/s, [Formula: see text] 0.56 [Formula: see text], respectively. An advanced objective function which simultaneously maximizes the power output and minimizes the power variance is employed for the optimization study. Through comparison, it is found that the optimized wind farm layout yields over 210 kW more total power output on average than the existed wind farm layout, which verifies the effectiveness of the wind farm layout optimization tool. The results show that as the measurement time for predicting the wind condition gets longer, the total wind farm power output average increases while the error of power output prediction decreases. For the wind farm with 20 wind turbines installed, the individual power output is above 500 kW with an error of 90 kW under the short-term wind [Formula: see text] 0.25 m/s, [Formula: see text] 5.62 [Formula: see text], while it is above 530 kW with an error of 10 kW under the long-term wind [Formula: see text] 0.025 m/s, [Formula: see text] 0.56 [Formula: see text].

Optimal power assessment of energy storage devices using nonlinear autoregressive network with extended Kalman filter for electric power farm tiller applications

ABSTRACT Precise state-of-health (SOH) estimation is extremely challenging in lithium-ion based cells due to the nonlinear behavior of its operating parameters. This pertains to complex estimation and prediction characteristics of power and energy demands in hybrid electric vehicles (HEVs) and electric vehicles (EVs), particularly variations in the operating temperature. In this paper, agricultural electric power tiller application battery pack cells are utilized for the study analysis. Extended Kalman filter algorithm (EKF) analysis was carried out for the experimental cell voltage estimation. The estimated voltage applied as the input to the nonlinear autoregressive network (NARX) modeled to analyze actual versus predicted charge/discharge powers. These estimation studies were carried out for lithium-ion nickel manganese cobalt chemistry 18650 cells. Aging analysis was carried out for four study cells through electrochemical impedance spectroscopy (EIS) to measure the impedance growth with different SOC conditions under a constant temperature of 318 K. In addition, incremental capacity analysis (ICA) peak points studies were carried out with regression analysis performed to evaluate the change in capacity. Resistance characterization analysis with two different temperature conditions 308 K and 318 K was performed to evaluate the change in resistance for the four study cells.

Modified Beetle Annealing Search (BAS) Optimization Strategy for Maxing Wind Farm Power through an Adaptive Wake Digraph Clustering Approach

Owing to scale-up and complex wake effects, the centralized control that processes the command from turbines may be unsuitable, as it incurs high communication overhead and computational complexity for a large offshore wind farm (OWF). This paper proposes a novel decentralized non-convex optimization strategy for maxing power conversion of a large OWF based on a modified beetle antennae search (BAS) algorithm. First, an adaptive threshold algorithm which to establish a pruned wake direction graph while preserving the most critical wake propagation relationship among wind turbines are presented. The adaptive graph constraints were used to create wake sub-digraphs that split the wind farm into nearly uncoupled clustering communication subsets. On this basis, a Monte Carlo-based beetle annealing search (MC-BAS) nonlinear optimization strategy was secondly designed to adjust the yaw angles and axial factors for the maximum power conversion of each turbine subgroup. Finally, the simulation results demonstrated that a similar gain could be achieved as a centralized control method at power conversion and reduces the computational cost, allowing it to solve the nonlinear problem and real-time operations of the OWF.

Seed metering device evaluation by Grease Belt Method

Soybean [Glycine max. (L.) Merr.] serve as one of the most valuable crop in the world; not only for oil purpose italso feed for livestock and aquaculture. A simple laboratory grease belt method for soybean planter was developed fortesting and calibrating the seed metering mechanism. The study was conducted in the year 2017, in the Departmentof Farm Machinery and Power Engineering, Allahabad. The main frame consists of variable speed drive, and greasecoated belt that are fitted with necessary provisions. The second frame consists of seed hopper and seed metering unit.The field and laboratory methods have been developed and used for evaluation of planter performance, each methodhaving its own advantages and shortcomings. In the present study, grease belt was used for laboratory evaluation ofwheel type seed-metering device and investigated the feeding quality, missing index, seed rate, and uniformity ofseeds in the row at various speed of grease belt. The results from grease belt methods were in good agreement andanalysis of variances showed that seed-metering device with 18 cells in 50 rpm performed better than seed-meteringdevice with 32 cells and in other speeds. Calibration of the manually operated seed-cum-fertilizer soybean planterhas been done in the laboratory. During calibration of planter, it found that there was less missing of soybean due tocircular shape of seed. Due to full hopper the pressure was high at the bottom and due to this force on seed of soybeaneasily reaches at the metering device.

Layout and power generation estimation of 50 MW wind turbine in Dayingpo

In the feasibility study of wind power generation project, wind turbine selection, layout and power generation estimation of wind farm are the core contents. According to the analysis needs of Dayingpo project, this paper first introduces the geographical location and wind energy resources of Lan county Dayingpo 50MW wind power generation project. Based on the above work, the optional fans are selected. As a result, WTG1-2200 and​ WTG2-2500 are selected for layout. According to the actual terrain and wind energy resources of Dayingpo, a total of 22 fans are arranged, including 17 WTG 1-2200 and 5 WTG 2-2500. According to the above contents, the annual on grid power reduction coefficient of the wind farm, the annual on grid power of the wind farm, and the single unit power generation results of WTG1-2200 and WTG2-2500 are estimated in detail, respectively. Finally, according to the actual terrain and fan layout scheme, the suggestions for the next practical project are proposed.

Ergonomical Assessment on Hand Operated Chaff Cutter by Rural Women Workers

A study was conducted to ease the fodder cutting operations a commercially available hand chaff cutter (Sokhiya Agricultural Industries, Jaipur, India) during 2019–20 in the Department of Farm Machinery and Power Engineering at College of Agricultural Engineering, Sangareddy, Telangana, India. The assessment was done using with 3 different age group female workers who regularly feed to the animals to assess its suitability for workers of the southern region of India. The parameters used for the Ergonomical evaluation include machine operation at different forces are heart rate, pulse rate, oxygen consumption rate, and energy expenditure rate. The average heart rate for female subjects of P1, P2 and P3 was recorded before the operation is 79, 76 and 81 beats min-1 and after the operation is 109, 108 and 113 beats min-1 for various fodders. The average pulse rate for female subjects of P1, P2, and P3 was recorded before the operation is 62, 68, and 63 beats min-1 and after the operation is 80, 80, and 82 beats min-1 for various fodders. The average oxygen consumption rate and energy expenditure rate of female subjects of P1, P2 and P3 were found to be 0.61, 0.59 and 0.66 liter min-1, and 12.68, 12.36 and 13.74 KJ min-1 respectively after operation of chaff cutter. The physiological parameters are heart rate, pulse rate, oxygen consumption rate, and energy consumption rate increased more rapidly for all age group female workers after operation of chaff cutter with 3 various fodders.

Enhancement of photovoltaic power farms using a new power prediction approach

Solar energy power prediction is a vital process for designing and operating solar power plants to evaluate the system performance and reduce the cost of grid management as it decreases the grid imbalance for a more stable grid. This study introduces a new power prediction approach to enhance the power prediction quality by combining different solar models. The study investigates the performance of 4.5 MWp solar field located at the California Polytechnic State University at San Luis Obispo, California, United States to validate this new approach. The system is real-time monitored for 1 year to study its performance. A representative identical model for the actual farm is then designed and built on a solar performance modeling software to validate the software. The actual energy generation of the field is compared with the predicted energy. The model is optimized by selecting different transposition and decomposition models to achieve the most accurate energy prediction. After that, the model is used in a computational framework to predict the energy injected into the grid for photovoltaic solar farms in Egypt based on the new approach methodology. Egypt is considered a solar belt country. Following the validation, a pilot model is used to predict energy generation for the selected locations in Egypt. Egypt's case study is then used as a pilot project to optimize some design parameters to study its effect and the suitability of the power generation in Egypt's weather. The results show that the relative error using the new approach for the whole year when using the proposed approach of combining the solar models is 2.9%. The performance ratio of the actual farm is 79% for the whole year, and the total energy produced is 10.92 GWh/year. The power prediction for the Egyptian sites concludes that 14 GWh/year energy potential can be achieved from the Red Sea location from the suggested model and the most suitable modules are polycrystalline. Furthermore, predicting a 13% increase in power generation due to using tracking technology compared with the usage of polycrystalline with fixed mounts.

Ethno-veterinary Practices For Livestock Owners: A Study in Pithoragadh District of Uttarakhand

Background: Livestock plays a vital role in the farmer’s life. They provide farm power, rural transport, manure, fuel, milk and meat. It provides income and employment to the small farmers. Thus, livestock has major role in rural economy. In Uttarakhand, medical facilities are very less in number. Due to unavailability of modern health facilities, poverty, connectivity with urban centre, awareness, etc. people in hilly and rural areas are still depend on traditional medicines for their health care. Some of the communities are using wild plant parts for healthcare. The indigenous knowledge of the veterinary health care system acquired by traditional herbal healers and elderly learned farmers and is orally transformed from one generation to other. Methods: Thus, a study was conducted to document the medicinally important plants used in treatment of cattle diseases by rural people living in Pithoragadh District of Uttarakhand. Interview Schedule, Participatory Rural Appraisal, Group Discussion techniques were used to identify plants and their medicinal information. Out of 219 villages under tehsil Munsyari, total five villages viz; total three villages viz; Alam, Arkhet, Baidu Mahar were selected purposively. Participatory Rural Appraisal, Group Discussion techniques were used to document the medicinal plants. Result: The investigator recorded 30 plants species to have ethnoveterinary value. These medicinal plants are highly valuable and appropriate for animal health care and management. People are dependent upon food, fruits, fodder, and medicinal plants for their healthcare. Hilly people use these traditionally available medicinal plants for animal health and believe that these are easily available, less expensive and have no side effects as compare to modern medicine. Present scenario as deforestation, tourism affects medicinal plants. Thus, conservation of these species is necessary. Proper policies should be needed to conserve the forests and medicinal plants. Attention should be made on scientific validation and proper exploitation and utilization of these medicinally important plants in animal health care.

Decentralised optimisation for large offshore wind farms using a sparsified wake directed graph

Considering the wake effects, developing an efficient wake-based graph clustering algorithm is essential for the decentralised coordinated online control of large offshore wind farms. In this study, the idea of graph sparse is introduced into the algorithm, in which the sparsified wake-directed graph is generated while preserving the original wake-directed graph critical wake coupling relationship between turbines. The key is to construct the original wake-directed graph by quantifying wake intensity and applying the graph sparseness constraints algorithm to achieve an ultra-sparse wake subgraph. Based on the sparsified wake-directed graph and wake intensity weighting matrix, the wind farm is split into almost uncoupled cluster subsets to establish decentralised sparse communication architectures. By doing so, a decentralised sequential quadratic programming optimisation strategy is proposed to solve a nonconvex optimisation problem, in which the thrust load problem is converted into a power controlling optimisation problem, and the thrust load distribution is balanced using the power margin. Simulation results reveal that the proposed scheme can maximise wind farm power production while minimising thrust loads in various turbulence intensities, making it functional for real-time operations on a large-scale wind farm.

An Anti-Fluctuation Compensator Design and Its Control Strategy for Wind Farm System

Large-scale wind farms in commercial operations have demonstrated growing influence on the stability of an electricity network and the power quality thereof. Variations in the output power of large-scale wind farms cause voltage fluctuations in the corresponding electrical networks. To achieve low-voltage ride-through capability in a doubly fed induction generator (DFIG) during a fault event, this study proposes a real-time reactive power control strategy for effective DFIG application and a static synchronous compensator (STATCOM) for reactive power compensation. Mathematic models were developed for the DFIG and STATCOM, followed by the development of an indirect control scheme for the STATCOM based on decoupling dual-loop current control. Moreover, a real-world case study on a commercial wind farm comprising 23 DFIGs was conducted. The voltage regulation performance of the proposed reactive power control scheme against a fault event was also simulated. The simulation results revealed that enhanced fault ride-through capability and prompt recovery of the output voltage provided by a wind turbine generator could be achieved using the DFIG along with the STATCOM in the event of a three-phase short-circuit fault.

PMSM Wind Farm Aggregation Algorithm Based on Power Equivalence Principle

With the continuing increase of offshore wind farm power scale, it is urgent to propose a simplified wind farm model, which aggregates the entire wind farm into single or several aggregated wind turbine generators (WTGs), aiming to save computing resources and improve simulation speed. A novel aggregation algorithm that considers the power loss of offshore submarine cable is proposed, which is different from the traditional wind farm modeling method that adopts amplifying transformer as aggregation medium. Moreover, multi machine aggregation (MMA) algorithm is furtherly proposed to improve the aggregation accuracy. Simulation results verify that the proposed aggregation method can present the dynamic characteristics of wind farm with high accuracy, and can be popularized for other types of wind farm.

Utilization and Linkage of Oceanic Energy in Natuna Island: A Review

Rachmayani, R.; Ningsih, N.S.; Ardiansyah, I.; Yani, L.F.; Rizal, A.M.; Kartadikaria, A.R.; Sari, N.T, and Park, H., 2021. Utilization and linkage of oceanic energy in Natuna Island: A review. In: Lee, J.L.; Suh, K.-S.; Lee, B.; Shin, S., and Lee, J. (eds.), Crisis and Integrated Management for Coastal and Marine Safety. Journal of Coastal Research, Special Issue No. 114, pp. 599–603. Coconut Creek (Florida), ISSN 0749-0208. Natuna Regency is known as the northernmost regency in the Karimata Strait with its abundant captured fisheries up to 104.879,81 tons, oil up to 3.138.143 barrels and natural gas up to 34.772.019 MMBTU in 2019, respectively. Moreover, Natuna is famous for aquaculture fisheries of Napoleon (Cheilinus undulatus) with allowed-export capacity up to 30,000 kg. However, resource development in Natuna is often constrained by poor infrastructure such as limited fish unloading berths and natural gas pipelines, obscure electricity, and inadequate energy resources. Thus, the utilization of resources in Natuna has not been maximized. Currently, Natuna has been partially improved on distribution services through the sea toll and the establishment of the Integrated Marine and Fisheries Centre (SKPT) of the Lampa Strait. To carry out the challenge and manifest the resources in Natuna, researches on marine renewable energy in Natuna have been conducted and revealed significant wave height up to ∼1.5 m, ocean current velocity per year ranged from 0.255 to 0.340 m/s, and thermal gradient's Carnot efficiency up to 0.67. Despite these lacking numbers on ocean currents, waves, and thermal gradients for renewable energy development, this study exhibits that the Natuna region has a great energy potential from wind farm and solar power plant development. There are four recommended sites namely Pulau Tiga, Sabang Mawang, Sedanau Island, and SKPT Natuna as places to develop hybrid renewable energy development from pumped hydro storage system, wind farm, and/or solar power plant. The renewable energy development at these locations will support smart city concept in Natuna.

Mechanical and Tribological Behaviour of Hybrid Multi Fibre Reinforced Nylon 6-6 Nanocomposites

The investigation on the effect of adding silane modified chopped E-glass fibre and Aluminium metal wire-mesh into nano silica toughened nylon 6-6 thermoplastic composites on mechanical, drop load impact, fatigue and tribological behaviour is studied in this paper. The primary aim of this research work is to develop a hybrid Nylon 6-6 nanocomposites having high stiffness, toughness and wear resistance. The chopped glass fibre and Al wire-mesh was surface treated with the help of 3-Aminopropyletrimethoxylane (silane) and acid etching. The tensile results revealed that additions of glass fibre and Al mesh into nano - silica toughened nylon 6-6 composite gives improved tensile and flexural strength. Similarly, the Izod impact strength of Al-mesh reinforced nano silica (1vol.%) toughened nylon 6-6 gives superior energy absorption up to 6 Joules/cm. The drop load impact penetration of composite N3 (59% - Nylon 66, 20% - E-glass fibre, 20% - Al wire mesh and 1 % - nano silica) shows very limited penetration than other composites. Highest fatigue life of 16391 cycles was observed for the composite designated N3, which contains 1 vol.% of nano silica, whereas the composite containing 2 vol.% of nano silica gives very lower specific wear rate and Co-efficient of friction. The developed composite which has better modulus, stiffness, wear resistance and fatigue life could be possibly used in automobile power transmission gears, domestic equipment and farm related machineries.