Grid Of Stations Research Articles

IoT-Based Healthcare Support System for Alzheimer’s Patients

In the last decade, the Internet of Things (IoT) has become a new technology that aims to facilitate life and help people in all aspects of their lives. This technology is used for smart homes, smart grid stations, smart agriculture, health systems, transport services, smart cities, etc. The number of sensors and IoT devices along with applications is used for monitoring the health condition of patients. These devices will monitor the movement of targeted patients at home or out of their homes. Based on their behavior and movement, the treatment will be provided to Alzheimer’s patients. The data will be collected from multiple sensors installed at patient’s homes and smartwatches for checking their blood pressure level and temperature, which is too important in the current Corona Virus Disease (COVID-19) pandemic for these types of patients. On the other hand, due to the diminishing mobility of people around the world, increasing environmental pollution and stress which is caused by modern machine life and various brain and neurological diseases including Alzheimer’s, Parkinson, etc. are widespread among people all over the world. The different types of communication protocols such as Message Queue Telemetry Transport (MQTT) and WebSocket (with authentication and autoclosing of connection) for sensors and the smartwatch have been used. The secure backend admin panel is used for tracing the location of doctors, patients, and ambulance. These protocols are implemented with security to protect the privacy of patients also.

Availability assessment of voltage source converter HVDC grids using optimal power flow‐based remedial actions

This study proposes a methodology for assessing the availability of voltage source converter high-voltage direct current (HVDC) grids based on the enumeration methodology of contingency analysis with N − 2 criteria and makes contributions in the computation of remedial actions and the definition and computation of reliability indices applied for HVDC grids. Thus, this study proposes the computation of remedial actions based on an optimal power flow, looking to maintain power exchanges between HVDC and high-voltage alternating current grids, when a contingency occurs on the HVDC grid and converter stations or HVDC lines are out of their operating limits. On the other hand, an HVDC grid has the function of injecting and extracting power from AC interconnected zones, and then traditionally used nodal reliability indices must be modified to indices that reflect the performance of the HVDC network to fulfil its function of interconnection of systems. This study defines two sets of availability indices applicable to HVDC grids: (i) loss of power and energy extracted from the DC grid to the AC zones and (ii) loss of power and energy injected to AC zones from the DC grid. The proposed methodology is applied to perform the availability assessment of the CIGRE B4 DC grid test system and the results are presented.

Analysis of the Influence of Distributed Photovoltaic Power Station Grid Connection on Distribution Network Relay Protection

With the improvement of China’s economic level and the continuous development of the power industry, the current photovoltaic power supply has been welcomed by more and more users as a new type of energy in the power field. For the power generation field, it can promote the power resources Production and development. Since the implementation of the distributed photovoltaic power plant grid connection in my country, it has also had a large impact on the relay protection of the distribution network. This article has analyzed this.

Resource Scheduling and Energy Cooperation in HetNet with Cross-Layer Interference Constraints

Facing more and more severe global warming problems, renewable energy, as an alternative to traditional fossil fuels, is attracting more and more attentions due to its capability of reducing carbon emission. This paper considers two-tier HetNets with orthogonal frequency division multiple access (OFDMA), where the macro base station (MBS) is powered by power grid and small base stations (SBSs) have hybrid energy supplies. Through smart grid, SBSs can share their renewable energy with each other. We consider the problem of cross-layer interference caused by spectrum reuse, the burst of user data, and the randomness of renewable energy arrivals. Through energy cooperation, this paper investigates maximizing the time-average energy efficiency of SBSs. Based on user data queue and SBS energy queue, the optimal problem is decoupled into two subproblems by Lyapunov optimization: resource allocation subproblem and energy scheduling and energy cooperation subproblem. By solving two subproblems, the online solution to the optimization problem is obtained. Through theoretical analysis and simulations, both user data queues and energy queues have an upper bound, the network is stable, and the proposed algorithm performs better than the basic algorithm without energy cooperation.

Comparative study of two new energy control systems based on PEMFC for a hybrid tramway in Ecuador

This article presents a comparison of two alternative systems to supply the traction power of a tramway in Cuenca–Ecuador. Each system studies the effective combination of supercapacitors, lithium ion batteries and proton exchange membrane fuel cells (SC/LIB/PEMFC) on board. The first system uses renewable sources (PV/HKT/GB/Grid) supplying the on-board systems through the existing grid and hydrogen charging stations. While the second system uses only grid power from a single point of charge, leaving the tramway without any external connection point throughout their journey. The energy and economic analyses are based on the capacity of each system to supply the load and the resources used.The results show that the new proposed control systems, by means of the analysed configurations made up of different control states, are always capable of perfectly supplying the power required by the tramway throughout their journey. However, when using energy from renewable sources, hydrogen consumption decreases by 4.27% with respect to the grid on each round trip, with a lower net present cost. Furthermore, in the first proposed system, the depth of discharge in SC and LIB is greater.

Research on Development Technology of AC / DC Hybrid Distribution Network Construction in Smart Grid

At present, the flexible interconnection of flexible power grids based on flexible DC and the combination of AC and DC distribution networks in smart grids will bring great changes and challenges to the operation of traditional power distribution systems. The AC / DC hybrid distribution network can better accept distributed power and DC loads, alleviate the contradiction between limited corridors and high load density in urban power grid stations, and provide dynamic reactive power support at the load centre, which can effectively improve the urban distribution system. Power quality, reliability and operating efficiency. This article summarizes and analyses key technical issues such as the topology, optimization planning, dispatch control, and economic evaluation of AC-DC hybrid distribution networks. Finally, the application prospects of AC-DC hybrid distribution networks are prospected.

A Strategic and Significant Method for the Optimal Placement of Phasor Measurement Unit for Power System Network

Currently the new state of power system relies on a precise monitoring of electrical quantities such as voltage and current phasors. Occasionally, its operation gets disturbed because of the flicking in load and generation which may result in the interruption of power supply or may cause catastrophic failure. The advanced technology of phasor measurement unit (PMU) is introduced in the late 1990s to measure the behavior of power system more symmetrically, accurately, and precisely. However, the implementation of this device at every busbar in a grid station is not an easy task because of its expensive installation and manufacturing cost. As a result, an optimum placement of PMU is much needed in this case. Therefore, this paper proposes a new symmetry approach of multiple objectives for the optimum placement of PMU problem (OPPP) in order to minimize the installed number of PMUs and maximize the measurement redundancy of the network. To overcome the drawbacks of traditional techniques in the proposed work a reduction and exclusion of pure transit node technique is used in the placement set. In which only the strategic, significant, and the most desirable buses are selected without considering zero injection buses (ZIBs). The fundamental novelty of the proposed work considers most importantly the reduction technique of ZIBs from the optimum PMU locations, as far as the prior approaches concern almost every algorithm have taken ZIBs as their optimal placement sets. Furthermore, a PMUs channel limits and an alternative symmetry location for the PMUs placement are considered when there is an outage or PMUs failure may occur. The performance of the proposed method is verified on different IEEE-standard such as: IEEE-9, IEEE-14, IEEE-24, IEEE-30, IEEE-57, IEEE-118, and a New England-39 bus system. The success of the proposed work was compared with the existing techniques’ outcomes from the literature.

Intelligent Charging Management of Electric Vehicles Considering Dynamic User Behavior and Renewable Energy: A Stochastic Game Approach

Uncoordinated charging of a rapidly growing number of electric vehicles (EVs) and the uncertainty associated with renewable energy resources may constitute a critical issue for the electric mobility (E-Mobility) in the transportation system especially during peak hours. To overcome this dire scenario, we introduce a stochastic game to study the complex interactions between the power grid and charging stations. In this context, existing studies have not taken into account the dynamics of customers’ preference on charging parameters. In reality, however, the choice of the charging parameters may vary over time, as the customers may change their charging preferences. We model this behavior of customers with another stochastic game. Moreover, we define a quality of service (QoS) index to reflect how the charging process influences customers’ choices on charging parameters. We also develop an online algorithm to reach the Nash equilibria for both stochastic games. Then, we utilize real data from the California Independent System Operator (CAISO) to evaluate the performance of our proposed algorithms. The results reveal that the electricity cost with the proposed method can result in a saving of about 20% compared to the benchmark method, while also yielding a higher QoS in terms of charging and waiting time. Our results can be employed as guidelines for charging service providers to make efficient decisions under uncertainty relative to power generation of renewable energy.

Implementation of Distributed Generation with Solar Plants in a 132 kV Grid Station at Layyah Using ETAP

Decentralized power generation efficaciously merges technological advances in a rapidly changing face of power networks introducing new power system components, advanced control, renewable sources, elegant communication, and web technology paving the way for the so called smart grids. Distributed generation technology lies at the intersection point of power systems, power electronics, control engineering, renewable energy, and communication systems which are not mutually exclusive subjects. Key features of renewable integration in a distribution network include loss minimization, voltage stability, power quality improvement, and low-cost consumption resulting from abundant natural resources such as solar or wind energy. In this research work, a case study has been carried out at a 132 kV grid station of Layyah, Pakistan, which has active losses, reactive losses, low power factor, low voltage on the demand side, and overloaded transformers and distribution lines. As a result, power outage issue is frequent on the consumer side. To overcome this issue, a simulation of load flow of this system is performed using the Newton-Raphson method due to its less computational time, fewer iterations, fast convergence, and independence from slack bus selection. It finds the harsh condition in which there were 23 overloaded transformers, 38 overloaded distribution lines, poor voltage profile, and low power factor at the demand side. There is a deficit of 24 MW in the whole system along with 4.58 MW active and 12.30 MVAR reactive power losses. To remove power deficiency, distributed generation using solar plants is introduced to an 11 kV distribution system with a total of 24 units with each unit having a capacity of 1 MW. Consequently, active and reactive power losses are reduced to 0.548 MW and 0.834 MVAR, respectively. Furthermore, the voltage profile improves, the power factor enhances, and the line losses reduce to a great extent. Finally, overloaded transformers and distribution lines also return to normal working conditions.

Renewable Electricity Production and Sustainability of the National and Regional Power Systems of Kazakhstan

The government of Kazakhstan is following many other national governments in promoting the development of renewable energy generation through adjustment of the policy environment and investment incentives. The government has started to invest in the construction of wind-, solar- and hydro-energy producing stations, some of which already operate in different regions of Kazakhstan. This paper aims to address the local challenges of the transition to renewable electric energy generation in the Almaty region of Kazakhstan. The authors examine regional challenges associated with introducing renewable energy production, with a focus on the energy market, the regional grid and energy management practices. The findings show that the development of renewable energy in the Almaty region is complicated by the absence of decentralized consumption options, the unreadiness of the regional grid and traditional power stations to accept renewable energy and the centralized old-fashioned management of the energy system. Instead of the expected increase of cheap energy for the private sector, there is an increasing technological and financial burden on traditional energy producers. The findings of the study raise serious research questions for further exploration: what is the real cost of clean energy production for regions of Kazakhstan, and why does public investment in support of renewable energy production not consider the implications of increasing the efficiency of traditional energy production and modernizing regional energy grids?

Evaluation of ERA-Interim Air Temperature Data over the Qilian Mountains of China

In this study, 2 m air temperature data from 24 meteorological stations in the Qilian Mountains (QLM) are examined to evaluate ERA-Interim reanalysis temperature data derived from the European Centre for Medium-Range Weather Forecasts (ECMWF) for the period of 1979–2017. ERA-Interim generally captures the monthly, seasonal, and annual variation very well. High daily correlations ranging from 0.956 to 0.996 indicate that ERA-Interim captures the daily temperature observations very well. However, an average root-mean-square error (RMSE) of ±2.7°C of all stations reveals that ERA-Interim should not be directly applied at individual sites. The biases are mainly attributed to the altitude differences between ERA-Interim grid points and stations. The positive trend (0.457°C/decade) is significant over the Qilian Mountains based on the 1979–2017 observations. ERA-Interim captures the warming trend very well with an increase rate of 0.384°C/decade. The observations and ERA-Interim both show the largest positive trends in summer with the values of 0.552°C/decade and 0.481°C/decade, respectively. We conclude that in general ERA-Interim captures the trend very well for observed 2 m air temperatures and ERA-Interim is generally reliable for climate change research over the Qilian Mountains.

Short-Term Load Forecasting Using Modified Sequence-to-Sequence Deep Learning Framework

The future of smart grids promises unprecedented flexibility in energy management. Therefore, it is crucial to accurately predict the energy load demand of individual power grid stations and overall levels. In this paper, a Sequence to Sequence learning method based on long short-term memory neural network (Seq2Seq) forecast model is proposed to predict the load of the community microgrid. In particular, this paper studies the effectiveness of Seq2Seq in community microgrid load forecasting, avoiding overfitting through weight attenuation regularization, and reducing the impact of interference and noise on training data. The proposed method is implemented on the base load data set of multi-user. The results of Seq2Seq were compared with the results of two well-known methods, one is traditional LSTM and the other is Support Vector Machine (SVM) on the same datasets. Experimental results show that compared with SVM and traditional LSTM, Seq2Seq has better learning effect. Finally, we calculate the performance index. When using load data to train and test the model, it was noted that compared with traditional LSTM and SVM, the root mean square error (RMSE) of Seq2Seq was decreased by 44.07% and 64.06%, respectively. Our research offers a decent reference for the application of deep learning in the field of energy management.

Mechanisms of sediment trapping in coastal embayments off the Shandong Peninsula in summer—A case study in Weihai Bay

This paper investigates sediment trapping in coastal embayments during summer seasons based on observation data obtained from two instrumented tripods that were placed at the mouth of Weihai Bay on north coast of Shandong Peninsula, China, over a 15-day period between 5 and August 20, 2018. The data consisted of time series of water depths, current profiles, wave parameters, near-bed flow velocities, turbidity, water salinity and temperature. Distributions of suspended sediment concentration (SSC) and water temperature in the bay and adjacent sea areas were also investigated at 87 grid stations from July 31 to August 4, 2018. From these data the bed shear stresses, residual currents and suspended sediment fluxes (SSF) were calculated. The results indicated that the variability in the SSC at the northern mouth was mainly controlled by local sediment resuspension while at the southern mouth horizontal advection due to the SSC gradient was the dominant mechanism. To identify the main drivers of the sediment transport, the SSF was analyzed using the decomposition method. The seaward advective transport due to residual flow and landward tidal pumping effect dominated the total near-bed sediment transport at the northern and southern mouths, respectively. Therefore, trapping processes occurred mainly through the southern mouth. The suspended sediment fluxes (SSF) during neap and spring tides at the southern mouth were 0.053 and 0.321 g m−2 s−1, respectively, while during moderate wave conditions (Hs > 0.8 m), the SSF was two times larger than the spring tide. In summer, the fine-grained sediments trapped in the bay were mainly derived from resuspension off the eastern tip of the Shandong Peninsula and thus is indirectly from the Yellow River. During such sediment transport and trapping processes, upwelling and winds can also play important roles.

Performance analysis of machine learning classifiers for non-technical loss detection

Power companies are responsible for producing and transferring the required amount of electricity from grid stations to individual households. Many countries suffer huge losses in billions of dollars due to non-technical loss (NTL) in power supply companies. To deal with NTL, many machine learning classifiers have been employed in recent time. However, few has been studied about the performance evaluation metrics that are used in NTL detection to evaluate how good or bad the classifier is in predicting the non-technical loss. This paper first uses three classifiers: random forest, K-nearest neighbors and linear support vector machine to predict the occurrence of NTL in a real dataset of an electric supply company containing approximately 80,000 monthly consumption records. Then, it computes 14 performance evaluation metrics across the three classifiers and identify the key scientific relationships between them. These relationships provide insights into deciding which classifier can be more useful under given scenarios for NTL detection. This work can be proved to be a baseline not only for the NTL detection in power industry but also for the selection of appropriate performance evaluation metrics for NTL detection.

Black Rats eradicated from Big Green Island in Bass Strait, Tasmania

Big Green Island is a 129-ha Nature Reserve and part of the Furneaux Group of islands in Bass Strait, southeastern Australia. Beginning in April 2016, Black Rats Rattus rattus were targeted for eradication using poisoning with 50 ppm brodifacoum wax blocks via a 25 x 25 m grid of bait stations (16 stations per ha) checked daily for a four-week period followed by three one-week visits over an eight-week period. After six weeks, rodent chew-cards were deployed exposing pockets of rat activity on the island. Island-wide monitoring led to the capture of six rats, the last known rat being killed in November 2016. Monitoring for signs of rats proceeded for a further two years and the island was declared rat-free in November 2018. The project encompassed partnerships between government agencies, industry and non-government organisations, and involved a significant volunteer contribution.

Towards Energy Efficient Smart Grids Using Bio-Inspired Scheduling Techniques

Electric power grids are lagging in flexibility and time-response. A smart grid is an improved version of electrical grids that leverages Internet of Things (IoT) based devices to improve the overall infrastructure from the grid stations to intelligent appliances. It provides better understanding of supply and demand and overall flow of data depending based upon the requirements. Modern approach towards Smart grid envisions to provide electricity consumers with the opportunity to manage their respective power usage. Population increase has played a major role in the adoption of smart grid as a lot of electrical energy is consumed in the residential sector and a lot of architectures have been proposed for better flow of information from the smart meter to connectors and devices for improved customer participation. Customer needs have been very important in the smart grid. However, the customers have never been provided with the ease of choosing their own kind of benefits from the smart grid. In this work, we propose an enhanced architecture working effectively for multiple users based on their requirements. The users would be able to choose their type of scheduling techniques based on their requirements. These requirements may include cost reduction and increasing user comfort for better consumption of electricity and reliable systems. These requirements can be achieved using different Bio inspired computing based scheduling algorithms. Furthermore, in this work, we provide a comparison of these bio inspired scheduling techniques, i.e., Enhanced Differential Evolution, Bacterial Foraging Algorithm and Grey Wolf Optimization integrated in smart grid architecture for providing better consumption of electricity and achieving reliable systems. These algorithms mainly aim to schedule load, minimize electricity bills and maximize the user comfort depending on user demand.

Sustainable protection coordination in presence of distributed generation with distributed network

The distributed generation (DG) is getting extensively integrated in existing power distribution system because of the massive development in green energy technologies and their economical, technical, and environment benefits. However, apart from beneficial aspects, DGs also have various and complex technical limitations, major of which are loss of protection coordination among protection devices which can lead to malfunctioning of protection devices, blind protection, fuse blowing, and permanent outage of power supply due to temporary faults. In this paper, a novel curve fitting technique is designed to restore much influenced recloser-fuse coordination using the directional properties of midline recloser for upstream and downstream protection devices coordination. It also works on fuse-saving scheme. Using Electrical Transient Analysis Program (ETAP) Software, the proposed methodology is implemented on a real 11 kV Rajewala radial distribution feeder starting from 132 kV Eimnabad grid station, district Gujranwala, Pakistan. Present here are some key results. Different case studies are carried out and results validate the effectiveness of the proposed methodology, and the coordination among protection devices is sustained even after DGs integration in the system.

Loss Minimization With Optimal Power Dispatch in Multi-Frequency HVac Power Systems

Low-frequency high-voltage ac transmission scheme has recently been proposed as an alternative approach for bulk power transmission. This paper proposes a multi-period optimal power flow (OPF) for a multi-frequency HVac transmission system that interconnects both conventional 50/60-Hz and low-frequency grids using back-to-back converters with a centralized control scheme. The OPF objective is to minimize system losses by determining the optimal dispatch for generators, shunt capacitors, and converters. The OPF constraints include the operational constraints of all HVac grid and converter stations. The resulting mixed-integer nonlinear programing problem is solved using a proposed framework based on the predictor-corrector primal-dual interior-point method. The proposed OPF formulation and solution approach are verified using a multi-frequency HVac transmission system that is modified from the IEEE 57-bus system. The results with the optimal dispatch from the proposed method during a simulated day show a significant loss reduction and an improved voltage regulation compared to those when an arbitrary dispatch is chosen.

Analysis risk of dynamic stability of power network with multiple small motor groups equivalent to each other

The BPA data of the regional power grid is usually only used for the detailed modeling of the 110kV grid connected substation, and the 35kV and the following grid station generally use the equivalent parameters of the equivalent capacity of the unit, and then be incorporated into the 110kV power grid for simulation analysis. In order to analyze the accuracy of power system stability simulation after equivalence, a detailed model of the grid connected small hydropower units with 35kV and the following is built. The results show that, using a plurality of small hydropower units group area grid equivalence, dynamic stability analysis of differences, there are regional power grid internal oscillation mode equivalent and cannot reflect the regional oscillation modes in small turbine.

Common reflection point mapping of the mantle transition zone using recorded and 3-D synthetic ScS reverberations

SUMMARY The method of ScS reverberation migration is based on a ‘common reflection point’ analysis of multiple ScS reflections in the mantle transition zone (MTZ). We examine whether ray-theoretical traveltimes, slownesses and reflection points are sufficiently accurate for estimating the thickness H of the MTZ, defined by the distance between the 410- and 660-km phase transitions. First, we analyse ScS reverberations generated by 35 earthquakes and recorded at hundreds of seismic stations from the combined Arrays in China, Hi-NET in Japan and the Global Seismic Network. This analysis suggests that H varies by about 30 km and therefore that dynamic processes have modified the large-scale structure of the MTZ in eastern Asia and the western Pacific region. Second, we apply the same procedure to spectral-element synthetics for PREM and two 3-D models. One 3-D model incorporates degree-20 topography on the 410 and 660 discontinuities, otherwise preserving the PREM velocity model. The other model incorporates the degree-20 velocity heterogeneity of S20RTS and leaves the 410 and 660 flat. To optimize reflection point coverage, our synthetics were computed assuming a homogeneous grid of stations using 16 events, four of which are fictional. The resolved image using PREM synthetics resembles the PREM structure and indicates that the migration approach is correct. However, ScS reverberations are not as strongly sensitive to H as predicted ray-theoretically because the migration of synthetics for a model with degree-20 topography on the 410 and 660: H varies by less than 5 km in the resolved image but 10 km in the original model. In addition, the relatively strong influence of whole-mantle shear-velocity heterogeneity is evident from the migration of synthetics for the S20RTS velocity model and the broad sensitivity kernels of ScS reverberations at a period of 15 s. A ray-theoretical approach to modelling long-period ScS traveltimes appears inaccurate, at least for continental-scale regions with relatively sparse earthquake coverage. Additional modelling and comparisons with SS precursor and receiver function results should rely on 3-D waveform simulations for a variety of structures and ultimately the implementation of full wave theory.