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1
Dong, Lihu, Danqing Song, and Zhuo Chen. "Small-signal modeling and stability analysis of grid-connected offshore wind power based on virtual synchronous generator control." Journal of Physics: Conference Series 2087, no. 1 (November 1, 2021): 012055. http://dx.doi.org/10.1088/1742-6596/2087/1/012055.
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Abstract With the increasing installed capacity of offshore wind power, the grid-connected of offshore wind power technology based on virtual synchronous generators (VSG) control can simulate the inertia and damping characteristics of synchronous generator, which is helpful to improve the networking ability and inertial supportability of grid-connected inverter. However, VSG control also inevitably causes system oscillation, endangers the safe and stable operation of the power grid. Hence, the main circuit and control circuit of offshore wind power grid connection are firstly modeled, and the small-signal model of offshore wind power grid-connected inverter based on VSG control is obtained. Then the correctness of the model is verified by Matlab/Simulink software. Finally, the root trajectory method is used to identify the effects of VSG control parameters and line parameters on the system stability. The results show that VSG control has a significant influence on the stability of the grid-connected system, and reasonable design parameters are needed to ensure the safe and stable operation of the power grid.
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Nurtiyanto, Woro Agus, Perani Rosyani, Lili Solihin, and Wiji Prayogo. "Analisis Efisiensi Inverter pada Grid-Connected 50 KWp Unpam Viktor." Journal of Computer System and Informatics (JoSYC) 3, no. 4 (September 3, 2022): 348–55. http://dx.doi.org/10.47065/josyc.v3i4.2134.
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The efficiency of grid-tied inverters in converting electrical energy sourced from solar power plants. The purpose of this study is to find out how efficient the Grid-tied inverter is based on the results of field tests, and it is useful as a reference to determine the performance of an inverter connected to the utility grid. Quantitative research methods with direct measurement techniques use the Seaward PV meter measuring instrument and the IsolarCloud monitoring application and control panel to determine the output power absorbed by the load with the research location in the inverter room on the 7th floor of the Pamulang Viktor University campus. The results show that the highest efficiency is achieved with a value of 98.4% where it can be said that the inverter can convert almost all of the energy produced by solar cells, with an average short circuit current (Isc) 16% greater than the maximum current (Imp) and open circuit voltage (Voc) is 21% greater than the maximum power voltage. The results of the analysis also show that the increase in current has no significant effect on the efficiency of the inverter.
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SIddaraj, Siddaraj, Udaykumar R. Yaragatti, and Nagendrappa Harischandrappa. "Coordinated PSO-ANFIS-Based 2 MPPT Control of Microgrid with Solar Photovoltaic and Battery Energy Storage System." Journal of Sensor and Actuator Networks 12, no. 3 (May 27, 2023): 45. http://dx.doi.org/10.3390/jsan12030045.
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The microgrid is a group of smaller renewable energy sources (REs), which act in a coordinated manner to provide the required amount of active power and additional services when required. This article proposes coordinated power management for a microgrid with the integration of solar PV plants with maximum power point tracking (MPPT) to enhance power generation and conversion using a hybrid MPPT method based on particle swarm optimization-adaptive neuro-fuzzy inference system (PSO-ANFIS) to acquire rapid and maximum PV power along with battery energy storage control to maintain the stable voltage and frequency (V-f) of an isolated microgrid. In addition, it is proposed to provide active and reactive power (P-Q) regulation for the grid connected. The approach used provides more regulation due to the least root mean square error (RMSE), which improves photovoltaic (PV) potential extraction. The comparison results of the PSO-ANFIS and P&O controllers of the MPPT and the controller of the energy storage devices combined with the V-f (or P-Q) controller of the inverter all show effective coordination between the control systems. This is the most important need for contemporary microgrids, considering the potential of changing irradiance in the grid following mode, the grid forming mode under an island scenario, and back-to-grid synchronization. With the test model, the islanded and grid-islanded-grid connected modes are investigated separately. The results demonstrate conclusively that the proposed strategies are effective. To run the simulations, MATLAB and SimPowerSystems are utilized.
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Chen, Ke, Hongkai Wang, Zhangchi Ying, Chengxin Zhang, and Jiaqi Wang. "Online cleaning method of power grid energy anomaly data based on improved random forest." Journal of Physics: Conference Series 2108, no. 1 (November 1, 2021): 012067. http://dx.doi.org/10.1088/1742-6596/2108/1/012067.
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Abstract Aiming at the problem of high root mean square error of traditional power grid energy anomaly data online cleaning, a power grid energy anomaly data online cleaning method based on improved random forest is designed. Firstly, an outlier data recognition model of isolated forest is designed to identify outliers in the data. Secondly, an improved random forest regression model is established to improve the adaptability of random forest to mixed abnormal data, and the data trend is fitted and predicted. Finally, the improved random forest data cleaning method is used to compensate the missing data after removing the mixed abnormal data, so as to clean the abnormal energy data of the power grid. The experimental results show that when the amount of power grid energy anomaly data increases, the cleaning root mean square error of the experimental group is significantly lower than that of the control group. The method in this paper solves the problem of high root-mean-square error in the online cleaning of abnormal data of traditional grid energy.
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Nazir, Zunaira, and Math H. J. Bollen. "Graphical Ways to Visualize Operational Risk Results for Transmission System Contingencies." Electricity 3, no. 3 (September 7, 2022): 442–62. http://dx.doi.org/10.3390/electricity3030023.
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The increased complexity of the transmission grid can endanger the operational security of the grid. Operational risk assessment, a stochastic tool, helps to enhance security. Contingency analysis and its impact quantification are the main constituents of operational risk assessment. In this study, different graphical methods are proposed to visualize operational risk contingency-based detailed results: heat-map and risk-based contingency chart. Through the heat-map, the system operator can determine which contingencies contribute most to the operational risk and would therefore be the most threatening contingencies for operational security of the grid. The “risk-based contingency chart” allows the system operator to analyze contingency cases from the probability and impact aspect in one chart. Both tools may be used in the control room for improved operational planning. In this study of contingency analysis and various types of network studies of severity factor quantification, the IEEE 39-Bus sample network is used in Power-Factory to analyze the contingencies behavior under different operational scenarios.
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Das, Partha Sarati, and Kyeong-Hwa Kim. "Open-Switch Fault-Tolerant Control of a Grid-Side Converter in a Wind Power Generation System." International Journal of Power Electronics and Drive Systems (IJPEDS) 6, no. 2 (June 1, 2015): 293. http://dx.doi.org/10.11591/ijpeds.v6.i2.pp293-304.
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A fault-tolerant technique of a grid-side converter (GSC) is a very important task because the unbalanced grid power endangers the overall system. Since the GSC is very sensitive to grid disturbance, the complete system needs to be stopped suddenly once an open-switch fault occurs. To improve the reliability of system, the continuous operation should be guaranteed. In this paper, a redundant topology based fault-tolerant algorithm is proposed for a GSC in a wind power generation system. The proposed scheme consists of the fault detection and fault-tolerant algorithms. The fault detection algorithm employs the durations of positive and negaitive cycles of three-phase grid currents as well as normalized root mean square (RMS) currents. Once a fault is detected, the corresponding faulty phase is identified and isolated to enable the fault-tolerant operation. The faulty phase is replaced by redundant one rapidly to recover the original shape of the grid currents, which ensures the continuity in operation. In contrast with the conventional methods, the proposed fault detection and fault-tolerant algorithms work effectively even in the presence of the open faults in multiple switches in the GSC. Simulation results verify the effectiveness of the proposed fault diagnosis and fault-tolerant control algorithms.
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Hu, Linlin, and Long Fu. "Primary frequency modulation of microgrid based on consistent droop control method." Journal of Physics: Conference Series 2387, no. 1 (November 1, 2022): 012017. http://dx.doi.org/10.1088/1742-6596/2387/1/012017.
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Abstract The rapid development of new energy sources gradually challenges the frequency stability of power systems. This article focuses on how to realize the frequency modulation control of the power grid under the fluctuation of the power grid. In order to improve the frequency stability of the microgrid system, based on the traditional droop control and consensus algorithm research, this paper proposes a microgrid primary frequency modulation based on the consistency droop control method. This control strategy improves the consistency of the progressive correction term to realize the control of the output of the energy storage unit, and improves the traditional droop controller to quickly restore the stability of the primary frequency. The root locus method verifies the effectiveness and feasibility of the control strategy. The simulation experiment verifies the frequency modulation ability of the proposed control strategy, which not only has a faster adjustment speed and response ability, but also has a strong anti-interference ability.
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Ebigenibo Genuine Saturday. "Nigerian Power Sector: A new structure required for effective and adequate power generation, transmission and distribution." Global Journal of Engineering and Technology Advances 1, no. 1 (April 30, 2021): 06–018. http://dx.doi.org/10.30574/gjeta.2021.7.1.0035.
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In this paper, the structure of the Nigerian power sector is examined, the problems in the structure are identified and a new structure is proposed for effective power generation, transmission and distribution. Besides the problems usually canvassed, the current structure is defective from the perspective of the ownership of the power infrastructures, passive involvement of state governments and undue influence of the federal government. The reforms in the sector were driven by the Electric Power Sector Reform Act (EPSRA) of 2005, leading to the creation of Power Holding Company of Nigeria (PHCN) to take both the assets and the liabilities of the then National Electric Power Authority (NEPA), and the subsequent unbundling of PHCN to 18 successor companies – 6 power generating companies, one power transmission company and 11 power distribution companies. The new structure proposed in this work gives room for every state government to own power plants and distribute power in the various states. They can equally buy power from independent power producers. Power plants owned by the federal government in the present structure are to continue sending power to the national grid and made available to states with insufficient power generation in the new structure. Independent power producers can also send power to the national grid. The federal government will continue managing power transmission in the new structure. Each state government will own at least two power distribution companies in partnership with private organizations who will equally have a stake in the ownership of the power generating plants. The tariff of grid-connected power will be higher, encouraging states to go into active power generation. The new structure will enable the federal government to do away with rural electrification programme and other power generation options regulated by the Nigerian Electricity Regulatory Commission which should be under the control of various state governments. New laws are needed in the place of the EPSRA to achieve the new structure. The federal government will make money from the proposed structure instead of spending huge sums of money in the present structure.
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Qin, Yongxin, Bingchao Qin, Tao Hong, Xiao Zhang, Dongyang Wang, Dongrui Liu, Zi-Yuan Wang, et al. "Grid-plainification enables medium-temperature PbSe thermoelectrics to cool better than Bi 2 Te 3." Science 383, no. 6688 (March 15, 2024): 1204–9. http://dx.doi.org/10.1126/science.adk9589.
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Thermoelectric cooling technology has important applications for processes such as precise temperature control in intelligent electronics. The bismuth telluride (Bi 2 Te 3 )–based coolers currently in use are limited by the scarcity of Te and less-than-ideal cooling capability. We demonstrate how removing lattice vacancies through a grid-design strategy switched PbSe from being useful as a medium-temperature power generator to a thermoelectric cooler. At room temperature, the seven-pair device based on n-type PbSe and p-type SnSe produced a maximum cooling temperature difference of ~73 kelvin, with a single-leg power generation efficiency approaching 11.2%. We attribute our results to a power factor of >52 microwatts per centimeter per square kelvin, which was achieved by boosting carrier mobility. Our demonstration suggests a path for commercial applications of thermoelectric cooling based on Earth-abundant Te-free selenide-based compounds.
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Ani, Vincent Anayochukwu. "Simulation and Optimization of Photovoltaic/Diesel Hybrid System for Off-Grid Banking Industry." International Journal of Energy Optimization and Engineering 3, no. 2 (April 2014): 17–37. http://dx.doi.org/10.4018/ijeoe.2014040102.
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Power supply is one of the major problems of the banking industry of many emerging economies, such as Nigeria, particularly as the banks strive to modernize and offer quality services, such as electronic banking. This paper proposed a PV/Diesel hybrid power generation system suitable for banking. The study is based on simulation and optimization of hybrid system of a bank located in two different locations [Nsukka (Enugu State – which covers the southern part of the nation) and Kaura (Kaduna State – covering the northern part of the nation)]. The Hybrid Optimization Model for Electric Renewables (HOMER) software was used for the design of the proposed stand-alone PV/Diesel power system. A control system for the Hybrid PV-Diesel Energy System with Battery Storage was developed to coordinate when power should be generated by PV panels and when it should be generated by diesel generator. From the simulation results, 46% decrease in each pollutant is noticed in Nsukka for a 46% renewable penetration into the existing diesel only power system; while in Kaura, 55% decrease in each pollutant is noticed for a 55% renewable penetration into the existing diesel only power system. This shows that the more % of renewable penetration into the diesel only system, the more decrease in pollutant emission. The results also show that the two locations (Nsukka and Kaura) have the same excess electricity of 45kWh/yr showing that the system is optimally sized. This excess electricity of power supply is guaranteed in the location simulated in order to give room for future Bank expansion. This may also be applied to other regions of the country.
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Rahman, Shahinur, Shuhui Li, Himadry Shekhar Das, Xingang Fu, Hoyun Won, and Yang-Ki Hong. "Exploring Dynamic P-Q Capability and Abnormal Operations Associated with PMSG Wind Turbines." Energies 16, no. 10 (May 16, 2023): 4116. http://dx.doi.org/10.3390/en16104116.
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With the proliferation of large-scale grid-connected wind farms, subsynchronous oscillation (SSO) incidents associated with Type-4 wind turbines (WTs) with a permanent magnet synchronous generator (PMSG) have occurred frequently. These incidents have caused severe reliability risks to the power grid. Conventionally, P-Q capability charts are utilized to ensure the safety operating region of a synchronous generator. However, a PMSG WT exhibits completely different and dynamic P-Q capability characteristics due to the difference in energy conversion technique and several critical factors related to the WT power converters. This paper presents a comprehensive dynamic P-Q capability study of a PMSG WT with sufficient and accurate considerations of the WT control and operation in the dq reference frame, its power converter constraints, and grid dynamics. Models of a PMSG WT are first developed based on its control principle in the dq reference frame. Then, algorithms for obtaining the P-Q capability charts of the WT are developed with the considerations of complete WT constraints in different aspects. The study analyzes the root cause of many abnormal operations of grid-connected PMSG WTs, reported in the literature, from the dynamic P-Q capability perspectives. The proposed study is verified via an electromagnetic transient (EMT) model of a grid-connected Type-4 WT.
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Elbouchikhi, Elhoussin, Muhammad Fahad Zia, Mohamed Benbouzid, and Soumia El Hani. "Overview of Signal Processing and Machine Learning for Smart Grid Condition Monitoring." Electronics 10, no. 21 (November 8, 2021): 2725. http://dx.doi.org/10.3390/electronics10212725.
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Nowadays, the main grid is facing several challenges related to the integration of renewable energy resources, deployment of grid-level energy storage devices, deployment of new usages such as the electric vehicle, massive usage of power electronic devices at different electric grid stages and the inter-connection with microgrids and prosumers. To deal with these challenges, the concept of a smart, fault-tolerant, and self-healing power grid has emerged in the last few decades to move towards a more resilient and efficient global electrical network. The smart grid concept implies a bi-directional flow of power and information between all key energy players and requires smart information technologies, smart sensors, and low-latency communication devices. Moreover, with the increasing constraints, the power grid is subjected to several disturbances, which can evolve to a fault and, in some rare circumstances, to catastrophic failure. These disturbances include wiring issues, grounding, switching transients, load variations, and harmonics generation. These aspects justify the need for real-time condition monitoring of the power grid and its subsystems and the implementation of predictive maintenance tools. Hence, researchers in industry and academia are developing and implementing power systems monitoring approaches allowing pervasive and effective communication, fault diagnosis, disturbance classification and root cause identification. Specifically, a focus is placed on power quality monitoring using advanced signal processing and machine learning approaches for disturbances characterization. Even though this review paper is not exhaustive, it can be considered as a valuable guide for researchers and engineers who are interested in signal processing approaches and machine learning techniques for power system monitoring and grid-disturbance classification purposes.
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Khan, M. Ryyan, Intekhab Alam, and M. Rezwan Khan. "Inverter-Less Integration of Roof-Top Solar PV with Grid Connected Industrial Drives." Energies 16, no. 4 (February 20, 2023): 2060. http://dx.doi.org/10.3390/en16042060.
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Green energy from Solar PV is getting increased attention in the industries due to the falling price of solar panels in the world market. A grid-tied inverter is one of the major components in such a system, where the DC energy from PV is converted to AC and synchronized with the grid to obtain power sharing between the PV and the grid for the industrial drives. In this paper, a DC link has been proposed instead of an AC link for interconnection between the solar PV system and the grid to run those industrial drives. In most modern industrial applications, induction motors are driven by VVVF (Variable Voltage and Variable Frequency) inverters to achieve efficient speed control. The inverters commonly have a rectifier section at the front end that rectifies the input AC to DC and the DC is then used in PWM mode to generate the required voltage and frequency for the induction motor operating under variable speed and load conditions. Such an inverter can use both AC or DC as the input so long the supply voltage has the right value for the inverter to operate. In our proposition, we eliminate the grid-tied inverter and use a DC link, created from the rectified AC and the regular Solar PV, to obtain the power-sharing between the PV output and the grid. Using the DC link output directly to energize the VVVF inverter has an impact on the performance of the inverter. In the proposed system, the solar PV array is designed in such a way that the grid remains as the supplementary power source only to supplement any shortfall in the PV output due to variable sunshine conditions. The control circuit used in this novel technique is inexpensive, efficient, and simple in design when compared to the grid-tied inverters. The proposed system has been implemented at Niagara Textiles in Gazipur, Bangladesh. The experimental/practical results are presented to validate the basic concept. Around a 20% reduction in the cost of energy has been reported in this paper, with a more than 90% efficient system. This will definitely make solar PV energy more competitive with regular energy and attractive to industries for its simplicity.
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Zhong, Caomao, Zhi Zhang, Anan Zhu, and Benxin Liang. "An Adaptive Virtual Impedance Method for Grid-Connected Current Quality Improvement of a Single-Phase Virtual Synchronous Generator under Distorted Grid Voltage." Sensors 23, no. 15 (August 1, 2023): 6857. http://dx.doi.org/10.3390/s23156857.
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The proportion of distributed generation systems in power grids is increasing, leading to the gradual emergence of weak grid characteristics. Moreover, using voltage-sourced grid-connected inverters can enhance the stability of a weak grid. However, due to the presence of background harmonics in weak grids, the grid voltage can cause significant distortions in the grid-connected current, which adversely affects the quality of the grid-connected current. This paper begins by briefly introducing the principle of the virtual synchronous generator (VSG). Then, the output current of the voltage source inverter is analyzed to elucidate the mechanism of harmonic current generation. Considering the distortion in the grid-connected current of the voltage source grid-connected inverter caused by background harmonics in the grid voltage, a harmonic current suppression strategy based on an adaptive virtual harmonic resistor is proposed. The proposed strategy employs a signal separation module based on multiple second-order generalized integrators connected through a cross-feedback network. This module effectively separates the fundamental and harmonic currents from the grid-connected current, extracts the amplitudes of the fundamental and harmonic currents through coordinate transformation, and adaptively adjusts the virtual harmonic resistance magnitude through the negative feedback control of the harmonic content (the ratio of the harmonic current amplitude to the fundamental current amplitude). These measures are used to enhance the quality of the grid-connected current. Additionally, the stability of the system is analyzed using the root locus of the open-loop transfer function. Finally, the effectiveness of the proposed method is validated through a combination of MATLAB/Simulink simulations and experimental results.
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Bartolucci, Lorenzo, Stefano Cordiner, Vincenzo Mulone, and Marina Santarelli. "Ancillary Services Provided by Hybrid Residential Renewable Energy Systems through Thermal and Electrochemical Storage Systems." Energies 12, no. 12 (June 24, 2019): 2429. http://dx.doi.org/10.3390/en12122429.
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Energy Management System (EMS) optimal strategies have shown great potential to match the fluctuating energy production from renewables with an electric demand profile, which opens the way to a deeper penetration of renewable energy sources (RES) into the electric system. At a single building level, however, handling of different energy sources to fulfill both thermal and electric requirements is still a challenging task. The present work describes the potential of an EMS based on Model Predictive Control (MPC) strategies to both maximize the RES exploitation and serve as an ancillary service for the grid when a Heat Pump (HP) coupled with a Thermal Energy Storage (TES) is used in a residential Hybrid Renewable Energy System (HRES). Cost savings up to 30% as well as a reduction of the purchased energy unbalance with the grid (about 15%–20% depending on the season) have been achieved. Moreover, the thermal energy storage leads to a more efficient and reliable use of the Heat Pump by generally decreasing the load factor smoothing the power output. The proposed control strategy allows to have a more stable room temperature, with evident benefits also in terms of thermal comfort.
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Thangarathinam, P., N. Suganya, T. Praddeep, and S. Vignesh. "Synchrophasor Technology for Cyber Security in Smart Grid." International Journal of Students' Research in Technology & Management 3, no. 7 (October 29, 2015): 436. http://dx.doi.org/10.18510/ijsrtm.2015.378.
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Smart grid is controlled by an authority personnel who uses LAN or the internet to control it. By knowing this information any one from outside can control the smart grid using LAN or the internet. This process of hacking the smart grid control is known as aurora attack. The Aurora attack may pose a risk to rotating machinery operating under certain conditions on the electrical grid. The Aurora attack involves opening and closing one or more circuit breakers, resulting in an out-of-synchronism condition that may damage rotating equipment connected to the power grid.This paper focuses on the Aurora attack on a synchronous generator and the existing technology available to mitigate the attack. The root cause of the vulnerability is breakdown in security. The first level prevents the attack with sound security practices. The second level protects the equipment in the event that the security level is compromised. The equipment can be protected using wide-area synchronized phasor measurement and protection system and security considerations.
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Zhu, Jiamin, Sikan Chen, and Zhijian Jin. "Progress on Second-Generation High-Temperature Superconductor Tape Targeting Resistive Fault Current Limiter Application." Electronics 11, no. 3 (January 18, 2022): 297. http://dx.doi.org/10.3390/electronics11030297.
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The resistive superconducting fault current limiter is well known for its simple structure and outstanding current-limiting effect, and it is broadly applied in power grid systems. The second-generation high-temperature superconductor (HTS) tape, of higher structural strength and greater room-temperature resistance, is well suited for application in resistive superconducting fault current limiters. The quenching caused by overcurrent in the HTS tape is a complexed coupling effect of several physical factors. The tape structure and properties directly impact the ultimate HTS tape’s quench performance. In this study, various SS316-laminated HTS tapes, of different critical currents, room-temperature resistances, and masses, were prepared. The pulse impact parameters of the various tape samples were measured using the RLC high-current impact test platform. By analyzing the resultant data, a quantitative assessment methodology to measure a tape’s tolerance toward impact was developed. The dependence of the HTS tape’s tolerance toward impact on its critical current, room-temperature resistance, and mass was studied. This provides numerical guidance on HTS material selection for resistive superconducting fault current limiters.
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Gbémou, Shab, Julien Eynard, Stéphane Thil, Emmanuel Guillot, and Stéphane Grieu. "A Comparative Study of Machine Learning-Based Methods for Global Horizontal Irradiance Forecasting." Energies 14, no. 11 (May 29, 2021): 3192. http://dx.doi.org/10.3390/en14113192.
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The proliferation of photovoltaic (PV) power generation in power distribution grids induces increasing safety and service quality concerns for grid operators. The inherent variability, essentially due to meteorological conditions, of PV power generation affects the power grid reliability. In order to develop efficient monitoring and control schemes for distribution grids, reliable forecasting of the solar resource at several time horizons that are related to regulation, scheduling, dispatching, and unit commitment, is necessary. PV power generation forecasting can result from forecasting global horizontal irradiance (GHI), which is the total amount of shortwave radiation received from above by a surface horizontal to the ground. A comparative study of machine learning methods is given in this paper, with a focus on the most widely used: Gaussian process regression (GPR), support vector regression (SVR), and artificial neural networks (ANN). Two years of GHI data with a time step of 10 min are used to train the models and forecast GHI at varying time horizons, ranging from 10 min to 4 h. Persistence on the clear-sky index, also known as scaled persistence model, is included in this paper as a reference model. Three criteria are used for in-depth performance estimation: normalized root mean square error (nRMSE), dynamic mean absolute error (DMAE) and coverage width-based criterion (CWC). Results confirm that machine learning-based methods outperform the scaled persistence model. The best-performing machine learning-based methods included in this comparative study are the long short-term memory (LSTM) neural network and the GPR model using a rational quadratic kernel with automatic relevance determination.
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Jung, A.-Hyun, Dong-Hyun Lee, Jin-Young Kim, Chang Ki Kim, Hyun-Goo Kim, and Yung-Seop Lee. "Regional Photovoltaic Power Forecasting Using Vector Autoregression Model in South Korea." Energies 15, no. 21 (October 23, 2022): 7853. http://dx.doi.org/10.3390/en15217853.
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Renewable energy forecasting is a key for efficient resource use in terms of power generation and safe grid control. In this study, we investigated a short-term statistical forecasting model with 1 to 3 h horizons using photovoltaic operation data from 215 power plants throughout South Korea. A vector autoregression (VAR) model-based regional photovoltaic power forecasting system is proposed for seven clusters of power plants in South Korea. This method showed better predictability than the autoregressive integrated moving average (ARIMA) model. The normalized root-mean-square errors of hourly photovoltaic generation predictions obtained from VAR (ARIMA) were 8.5–10.9% (9.8–13.0%) and 18.5–22.8% (21.3–26.3%) for 1 h and 3 h horizon, respectively, at 215 power plants. The coefficient of determination, R2 was higher for VAR, at 4–5%, than ARIMA. The VAR model had greater accuracy than ARIMA. This will be useful for economical and efficient grid management.
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Molla, Emiyamrew Minaye, and Cheng-Chien Kuo. "Voltage Quality Enhancement of Grid-Integrated PV System Using Battery-Based Dynamic Voltage Restorer." Energies 13, no. 21 (November 2, 2020): 5742. http://dx.doi.org/10.3390/en13215742.
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The advancement of power electronic-based sensitive loads drives the power utilities’ devotion to power quality issues. The voltage disturbance could be happening due to fault conditions, switching of loads, energizing of transformers, or integration of highly intermittent energy sources such as PV systems. This research work attempts to enhance the voltage fluctuation of a sensitive load connected to a grid-integrated PV system using a battery-based dynamic voltage restorer (DVR). The proposed battery energy storage-based DVR has two separate controlling stages that are implemented at the DC–DC buck/boost converter of the battery and voltage source converter (VSC) system. Charging and discharging of the battery is operated based on the state-of-charge (SOC) value of the battery and the measured root mean square (RMS) voltage at the point of common coupling (PCC). The VSC of the DVR detection and reference generation control is done appropriately. In the detection control of the VSC, a combination of RMS and dq0 measurement techniques is used, whereas in the reference generation control, pre-fault strategy is implemented to restore both phase jump and magnitude distortions. Symmetrical and asymmetrical voltage sags scenarios are considered and the compensation demonstration is carried out using power system computer-aided design (PSCAD/EMTDC) software.
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Rancilio, Giuliano, Arianna Rossi, Claudio Di Profio, Martino Alborghetti, Andrea Galliani, and Marco Merlo. "Grid-Scale BESS for Ancillary Services Provision: SoC Restoration Strategies." Applied Sciences 10, no. 12 (June 15, 2020): 4121. http://dx.doi.org/10.3390/app10124121.
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The future power system, characterized by lower inertia, reduced programmability and more distributed architecture, will depend on prompt and reliable control systems. Quick ancillary services provided by battery energy storage systems (BESS) could be a resource in order to deliver fast and precise response to frequency events. Degrees of freedom in the design of innovative products traded on ancillary services markets give the asset manager room for developing state-of-charge (SoC) restoration mechanisms. These are necessary to effectively exploit BESS as key resources for electricity balancing. This study compares the main SoC restoration strategies. It aims to define which ones are suitable for guaranteeing the reliability of the provision and the return on the investment. A robust regulatory framework analysis describes the degrees of freedom guaranteed by the main experiences around Europe. In this paper, a BESS model with variable efficiency is used to compare the provision of Frequency Containment Reserve (FCR) with different SoC restoration strategies exploiting one or more degrees of freedom. Here, we show that the degrees of freedom are key to the reliability of provision. Among most diffused mechanisms, dead-band strategies secure the desired consistency, but require large energy flows for SoC management. Thus, BESS life and economics decrease. The strategies based on minimum available energy guarantee assured reliability while being fair with BESS life and operation costs.
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Alzain, Elham, Shaha Al-Otaibi, Theyazn H. H. Aldhyani, Ali Saleh Alshebami, Mohammed Amin Almaiah, and Mukti E. Jadhav. "Revolutionizing Solar Power Production with Artificial Intelligence: A Sustainable Predictive Model." Sustainability 15, no. 10 (May 14, 2023): 7999. http://dx.doi.org/10.3390/su15107999.
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Photovoltaic (PV) power production systems throughout the world struggle with inconsistency in the distribution of PV generation. Accurate PV power forecasting is essential for grid-connected PV systems in case the surrounding environmental conditions experience unfavourable shifts. PV power production forecasting requires the consideration of critical elements, such as grid energy management, grid operation and scheduling. In the present investigation, multilayer perceptron and adaptive network-based fuzzy inference system models were used to forecast PV power production. The developed forecasting model was educated using historical data from October 2011 to February 2022. The outputs of the proposed model were checked for accuracy and compared by considering the dataset from a PV power-producing station. Three different error measurements were used—mean square error, root-mean-square error, and Pearson’s correlation coefficient—to determine the robustness of the suggested method. The suggested method was found to provide better results than the most recent and cutting-edge models. The MLP and ANFIS models achieved the highest performance (R = 100%), with less prediction errors (MSE = 1.1116 × 10−8) and (MSE = 1.3521 × 10−8) with respect to MLP and ANFIS models. The study also predicts future PV power generation values using previously collected PV power production data. The ultimate goal of this work is to produce a model predictive control technique to achieve a balance between the supply and demand of energy.
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Maurer, Florian, Christian Rieke, Ralf Schemm, and Dominik Stollenwerk. "Analysis of an Urban Grid with High Photovoltaic and e-Mobility Penetration." Energies 16, no. 8 (April 12, 2023): 3380. http://dx.doi.org/10.3390/en16083380.
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This study analyses the expected utilization of an urban distribution grid under high penetration of photovoltaic and e-mobility with charging infrastructure on a residential level. The grid utilization and the corresponding power flow are evaluated, while varying the control strategies and photovoltaic installed capacity in different scenarios. Four scenarios are used to analyze the impact of e-mobility. The individual mobility demand is modelled based on the largest German studies on mobility “Mobilität in Deutschland”, which is carried out every 5 years. To estimate the ramp-up of photovoltaic generation, a potential analysis of the roof surfaces in the supply area is carried out via an evaluation of an open solar potential study. The photovoltaic feed-in time series is derived individually for each installed system in a resolution of 15 min. The residential consumption is estimated using historical smart meter data, which are collected in London between 2012 and 2014. For a realistic charging demand, each residential household decides daily on the state of charge if their vehicle requires to be charged. The resulting charging time series depends on the underlying behavior scenario. Market prices and mobility demand are therefore used as scenario input parameters for a utility function based on the current state of charge to model individual behavior. The aggregated electricity demand is the starting point of the power flow calculation. The evaluation is carried out for an urban region with approximately 3100 residents. The analysis shows that increased penetration of photovoltaics combined with a flexible and adaptive charging strategy can maximize PV usage and reduce the need for congestion-related intervention by the grid operator by reducing the amount of kWh charged from the grid by 30% which reduces the average price of a charged kWh by 35% to 14 ct/kWh from 21.8 ct/kWh without PV optimization. The resulting grid congestions are managed by implementing an intelligent price or control signal. The analysis took place using data from a real German grid with 10 subgrids. The entire software can be adapted for the analysis of different distribution grids and is publicly available as an open-source software library on GitHub.
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Anagnostopoulos, Theodoros, Faidon Komisopoulos, Andreas Vlachos, Alkinoos ,. Psarras, Ioannis Salmon, and Klimis Ntalianis. "Sustainable Supply Chain Management of Electric Grid Power Consumption Load for Smart Cities Based on Second-order Exponential Smoothing Algorithm." WSEAS TRANSACTIONS ON SYSTEMS 21 (December 9, 2022): 247–56. http://dx.doi.org/10.37394/23202.2022.21.27.
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Electric grid power consumption load is one of the fundamental areas that need to be faced to provide a sustainable and green ecosystem in smart cities. Consumption load as well as supply and availability of electricity to suppliers and customers is a major issue to be faced to have a balanced smart city power grid infrastructure. Balancing in this case is assumed as a well-designed supply chain management system to be applied in the Smart City (SC) of Athens, Greece. Core of such a system is the knowledge of electric power consumption load per weekly basis of a year, that is the granularity of the proposed system is one week of the system’s operation. In this paper, focus is given on the electric load forecast component of an Energy Management System (EMS) such as the Independent Power Transmission Operator (ITPO) of Greece. Concretely, stochastic data of electric energy consumption load are used to predict the demand or offering of electric power in the future. This is achieved by incorporating a machine learning second-order exponential smoothing algorithm. Such an algorithm is able to speculate near or far in the future power consumption load thus providing a promising parameter to predict smart city needs for electric power in the future. Adopted system is evaluated by the evaluation metric of Normalized Root Mean Square Error (NRMSE), which assures that the system can be used for future predictions of electric power consumption load in smart cities.
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Xiang, Yingyu, Haoqing Hu, Qian Fang, Hongwen Liu, and Tianze Cheng. "Research on Cloud-Edge-Terminal function configuration based on differentiated low-voltage intelligent distribution network." Journal of Physics: Conference Series 2479, no. 1 (April 1, 2023): 012061. http://dx.doi.org/10.1088/1742-6596/2479/1/012061.
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Abstract At the present, more than 30 low-voltage intelligent distribution rooms have been built in Yunnan Power Grid, covering incoming cabinets, distribution substations, low-voltage switches and environmental monitoring, etc. The intelligent distribution rooms use the Cloud-Edge-Terminal architecture model for intelligent management, monitoring and control of low-voltage distribution rooms but there are generally problems such as low level of heterogeneous data application, insufficient correlation analysis capability, fault location. However, there are problems such as low level of heterogeneous data application, insufficient correlation analysis capability, inaccurate fault location, excessive network load, insufficient sensing capability of sensing terminals and unreasonable configuration. Based on the application model of low-voltage intelligent distribution network of Yunnan power grid, Our paper intends to summarize the experience and methods to support operation and maintenance, fault repair and customer service and study the differentiated low-voltage intelligent distribution Cloud-Edge-Terminal solution to improve the efficiency of intelligent distribution network operation and maintenance.
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Blair, Enrique, and Craig Lent. "Clock Topologies for Molecular Quantum-Dot Cellular Automata." Journal of Low Power Electronics and Applications 8, no. 3 (September 8, 2018): 31. http://dx.doi.org/10.3390/jlpea8030031.
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Quantum-dot cellular automata (QCA) is a low-power, non-von-Neumann, general-purpose paradigm for classical computing using transistor-free logic. Here, classical bits are encoded on the charge configuration of individual computing primitives known as “cells.” A cell is a system of quantum dots with a few mobile charges. Device switching occurs through quantum mechanical inter-dot charge tunneling, and devices are interconnected via the electrostatic field. QCA devices are implemented using arrays of QCA cells. A molecular implementation of QCA may support THz-scale clocking or better at room temperature. Molecular QCA may be clocked using an applied electric field, known as a clocking field. A time-varying clocking field may be established using an array of conductors. The clocking field determines the flow of data and calculations. Various arrangements of clocking conductors are laid out, and the resulting electric field is simulated. It is shown that that control of molecular QCA can enable feedback loops, memories, planar circuit crossings, and versatile circuit grids that support feedback and memory, as well as data flow in any of the ordinal grid directions. Logic, interconnect and memory now become indistinguishable, and the von Neumann bottleneck is avoided.
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Zhang, Dongying, Kai Yang, Wei Wang, Yunbin Zhou, Xiong Hua, Tianjun Liang, and Kunhao Song. "A Multi-Stage Real-Time Fast Search Method for Closed-Loop Paths Based on Grid Hierarchical Partitioning Characteristics." Energies 16, no. 18 (September 12, 2023): 6561. http://dx.doi.org/10.3390/en16186561.
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Prior to switching operations, the dispatch automation system is required to be able to search for closed-loop paths quickly in real time. In order to improve the efficiency of closed-loop path search, this paper proposes a multi-stage real-time fast search method for closed-loop paths based on the characteristics of power grid hierarchical partitioning. First, we divide the closed-loop judgement process into three phases: initialization, acceptance of the closed-loop judgement command, and post-operation. Then, we define three types of nodes, including root nodes, same-layer contact nodes, and common nodes, and construct path data models for each type of node in accordance with the node liaison relationship in grid hierarchical zoning. In the initialization phase, we design a method for the automatic generation of real-time nodal path data models and study a hierarchical partitioned closed-loop path search method based on a nodal path data model for the phase of accepting closed-loop judgement commands. Next, we design a fast local correction method for nodal path models after the switch closure and disconnection operations in the post-operation idle phase are performed. Finally, a real power grid model is used as an example to test the above closed-loop path search method, which improves the search efficiency by eight times compared with the conventional breadth-first search method. The method is applicable to real large and complex power grids.
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Pathan, E., S. A. Zulkifli, U. B. Tayab, and R. Jackson. "Small Signal Modeling of Inverter-based Grid-Connected Microgrid to Determine the Zero-Pole Drift Control with Dynamic Power Sharing Controller." Engineering, Technology & Applied Science Research 9, no. 1 (February 16, 2019): 3790–95. http://dx.doi.org/10.48084/etasr.2465.
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This paper presents a small signal state space modeling of three-phase inverter-based microgrid (MG) system with consideration of improved droop control. The complete system matrices for one distribution source-grid connects to the local load have been elaborated by applying high, medium and low-frequency clusters to the system without considering the switching action on the inverter during power-sharing. Moreover, the final matrices will be used to determine the location of the eigenvalues for the control parameters gains due to dynamic effect of the MG, by observing the root locus graph on cluster identification. Sensitivity analysis of all types of frequency cluster showed that power-sharing control parameters such as load current, source current, and inverter voltage are influencing system stability and must be considered when designing the proportional-integral (PI) control when different load scenarios have been applied from the zero-pole drifting. Those eigenvalues of the system model are indicating the frequency and damping oscillatory components when there is sudden changed at the inverter-grid connection. The matrices’ eigenvalues are being plotted using MATLAB/Simulink to identify system stability region and find the PI controller parameters.
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Khorram, Mahsa, Pedro Faria, Omid Abrishambaf, and Zita Vale. "Consumption Optimization in an Office Building Considering Flexible Loads and User Comfort." Sensors 20, no. 3 (January 21, 2020): 593. http://dx.doi.org/10.3390/s20030593.
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This paper presents a multiperiod optimization algorithm that is implemented in a Supervisory Control and Data Acquisition system. The algorithm controls lights and air conditioners as flexible loads to reduce the consumption and controls a dishwasher as a deferrable load to implement the load shifting. Several parameters are considered to implement the algorithm for several successive periods in a real building operation. In the proposed methodology, optimization is done regarding user comfort, which is modeled in the objective function related to the indoor temperature in each room, and in the constraints in order to prevent excessive power reduction, according to users’ preferences. Additionally, the operation cycle of a dishwasher is included, and the algorithm selects the best starting point based on the appliance weights and power availability in each period. With the proposed methodology, the building energy manager can specify the moments when the optimization is run with consideration of the operational constraints. Accordingly, the main contribution of the paper is to provide and integrate a methodology to minimize the difference between the actual and the desired temperature in each room, as a measure of comfort, respecting constraints that can be easily bounded by building users and manager. The case study considers the real consumption data of an office building which contains 20 lights, 10 ACs, and one dishwasher. Three scenarios have been designed to focus on different functionalities. The outcomes of the paper include proof of the performance of the optimization algorithm and how such a system can effectively minimize electricity consumption by implementing demand response programs and using them in smart grid contexts.
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Jeon, Byung-Ki, and Eui-Jong Kim. "White-Model Predictive Control for Balancing Energy Savings and Thermal Comfort." Energies 15, no. 7 (March 23, 2022): 2345. http://dx.doi.org/10.3390/en15072345.
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To save energy consumed by a building, utilizing optimal predictive control with model predictive control (MPC) makes the most of energy storage systems (ESSs) to reduce the electrical energy consumption of peak and heavy loads. This study evaluated MPC applicability in a multi-zone commercial building using the EnergyPlus model and conducted multi-objective optimization of thermal comfort and energy savings. As a result of the simulation, optimal ESS charging scenarios responded to the fluctuating electricity pricing system, and changing the peak load time reduced the electricity bill of the grid by 55% compared to the existing operating method. At the same time, room temperatures stayed within the thermal comfort range, and the Pareto curve showed a proper balance between energy saving and thermal comfort. Especially, the proposed method with a white model is applicable for MPC applications in commercial buildings, as it gave optimal solutions within the target time interval.
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Saberi Derakhtenjani, Ali, and Andreas K. Athienitis. "Model Predictive Control Strategies to Activate the Energy Flexibility for Zones with Hydronic Radiant Systems." Energies 14, no. 4 (February 23, 2021): 1195. http://dx.doi.org/10.3390/en14041195.
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This paper presents control strategies to activate energy flexibility for zones with radiant heating systems in response to changes in electricity prices. The focus is on zones with radiant floor heating systems for which the hydronic pipes are located deep in the concrete and, therefore, there is a significant thermal lag. A perimeter zone test-room equipped with a hydronic radiant floor system in an environmental chamber is used as a case study. A low order thermal network model for the perimeter zone, validated with experimental measurements, is utilized to study various control strategies in response to changes in the electrical grid price signal, including short term (nearly reactive) changes of the order of 10–15 min notice. An index is utilized to quantify the building energy flexibility with the focus on peak demand reduction for specific periods of time when the electricity prices are higher than usual. It is shown that the developed control strategies can aid greatly in enhancing the zone energy flexibility and minimizing the cost of electricity and up to 100% reduction in peak power demand and energy consumption is attained during the high-price and peak-demand periods, while maintaining acceptable comfort conditions.
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Foroutan, Armina, Sagnik Basumallik, and Anurag Srivastava. "Estimating and Calibrating DER Model Parameters Using Levenberg–Marquardt Algorithm in Renewable Rich Power Grid." Energies 16, no. 8 (April 18, 2023): 3512. http://dx.doi.org/10.3390/en16083512.
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The proliferation of inverter-based distributed energy resources (IBDERs) has increased the number of control variables and dynamic interactions, leading to new grid control challenges. For stability analysis and designing appropriate protection controls, it is important that IBDER models are accurate. This paper focuses on the accurate estimation and parameter calibration of DER_A, a recently proposed aggregated IBDER model. In particular, we focus on the parameters of the reactive power–voltage regulation module. We formulate the problem of parameter tuning as a non-linear least square minimization problem and solve it using the Levenberg–Marquardt (LM) method. The LM method is primarily chosen due to its flexibility in adaptively selecting between the steepest descent and Gauss–Newton methods through a damping parameter. The LM approach is used to minimize the error between the actual measurements and the estimated response of the model. Further, the computational challenges posed by the numerical calculation of the Jacobian are tackled using a quasi-Newton root-finding approach. The proposed method is validated on a real feeder model in the northeastern part of the United States. The feeder is modeled in OpenDSS and the measurements thus obtained are fed to the DER_A model for calibration. The simulation results indicate that our approach is able to successfully calibrate the relevant model parameters quickly and with high accuracy, with a total sum of square error of 3.57×10−7.
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Bubalo, Matija, Mateo Bašić, Dinko Vukadinović, and Ivan Grgić. "Experimental Investigation of a Standalone Wind Energy System with a Battery-Assisted Quasi-Z-Source Inverter." Energies 14, no. 6 (March 17, 2021): 1665. http://dx.doi.org/10.3390/en14061665.
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This paper presents a wind energy conversion system (WECS) for grid-isolated areas. The system includes a squirrel-cage induction generator (SCIG) and a battery-assisted quasi-Z source inverter (qZSI). The batteries ensure reliable and stable operation of the WECS in spite of the wind power oscillations. The maximum power is captured from both the wind turbine (WT) and the SCIG through adjustment of the WT speed and the SCIG operating flux, respectively. The utilized maximum power point tracking (MPPT) algorithms belong to the group of fuzzy logic (FL) search-based algorithms. The battery state of charge (SOC) is tracked online and controlled. When it reaches the minimum allowed level, the load is automatically disconnected; conversely, when it reaches the maximum allowed level, the battery charging is stopped via WT speed control. The load voltage root-mean-square (RMS) value and frequency are at all times controlled at grid-level values. The performance of the proposed system was experimentally validated, in steady state and during transients, achieving wide ranges of wind speed, load power, SOC, and alternating current/direct current (AC/DC) voltage levels. The system startup and low-wind operation were also analyzed. The control algorithms were executed in real time by means of the DS1103 and MicroLabBox controller boards (dSpace).
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Wang, Yonggui, Yong Qi, Jian Li, Le Huan, Yusen Li, Bitao Xie, and Yongshan Wang. "The Wind and Photovoltaic Power Forecasting Method Based on Digital Twins." Applied Sciences 13, no. 14 (July 19, 2023): 8374. http://dx.doi.org/10.3390/app13148374.
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Wind and photovoltaic (PV) power forecasting are crucial for improving the operational efficiency of power systems and building smart power systems. However, the uncertainty and instability of factors affecting renewable power generation pose challenges to power system operations. To address this, this paper proposes a digital twin-based method for predicting wind and PV power. By utilizing digital twin technology, this approach provides a highly realistic simulation environment that enables accurate monitoring, optimal control, and decision support for power system operations. Furthermore, a digital twin platform for the AI (Artificial Intelligence) Grid is established, allowing real-time monitoring, and ensuring the safe, reliable, and stable operation of the grid. Additionally, a deep learning-based model WPNet is developed to predict wind and PV power at specific future time points. Four datasets are constructed based on weather conditions and historical wind and PV power data from the Flanders and Wallonia regions. The prediction models presented in this paper demonstrate excellent performance on these datasets, achieving mean square error (MSE) values of 0.001399, 0.001833, 0.000704, and 0.002708; mean absolute error (MAE) values of 0.025164, 0.027854, 0.018592, and 0.033501; and root mean square error (RMSE) values of 0.037409, 0.042808, 0.026541, and 0.052042, respectively.
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Rodríguez, Fermín, Fernando Martín, Luis Fontán, and Ainhoa Galarza. "Very Short-Term Load Forecaster Based on a Neural Network Technique for Smart Grid Control." Energies 13, no. 19 (October 6, 2020): 5210. http://dx.doi.org/10.3390/en13195210.
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Electrical load forecasting plays a crucial role in the proper scheduling and operation of power systems. To ensure the stability of the electrical network, it is necessary to balance energy generation and demand. Hence, different very short-term load forecast technologies are being designed to improve the efficiency of current control strategies. This paper proposes a new forecaster based on artificial intelligence, specifically on a recurrent neural network topology, trained with a Levenberg–Marquardt learning algorithm. Moreover, a sensitivity analysis was performed for determining the optimal input vector, structure and the optimal database length. In this case, the developed tool provides information about the energy demand for the next 15 min. The accuracy of the forecaster was validated by analysing the typical error metrics of sample days from the training and validation databases. The deviation between actual and predicted demand was lower than 0.5% in 97% of the days analysed during the validation phase. Moreover, while the root mean square error was 0.07 MW, the mean absolute error was 0.05 MW. The results suggest that the forecaster’s accuracy is considered sufficient for installation in smart grids or other power systems and for predicting future energy demand at the chosen sites.
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Wang, Sue, and Yuxin Xie. "Virtual Synchronous Generator (VSG) Control Strategy Based on Improved Damping and Angular Frequency Deviation Feedforward." Energies 16, no. 15 (July 26, 2023): 5635. http://dx.doi.org/10.3390/en16155635.
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The output active power of a grid-connected inverter controlled by a traditional virtual synchronous generator (VSG) has the problems of oscillation and steady-state errors. A VSG control strategy based on improved damping and angular frequency deviation feedforward is proposed. This strategy reduces the steady-state error of active power by adding a transient damping link to a traditional VSG damping feedback channel. At the same time, the angular frequency deviation feedforward compensation is used to improve the response speed of the VSG to the active power instruction and reduce the active power overshoot in the dynamic process. First, the VSG active power closed-loop small-signal model is established. The effects of inertia and damping on the dynamic and steady-state performance of the VSG are analyzed by the root locus method. The effect of the proposed control strategy on the system is analyzed by using a closed-loop zero-pole diagram. This strategy improves the precision of active power control the dynamic performance of the system effectively. Finally, the effectiveness and superiority of the proposed control strategy are verified by Matlab/Simulink simulation and semi-physical simulation platform RT-LAB.
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Fan, Ya Ju, and Chandrika Kamath. "Identifying and Exploiting Diurnal Motifs in Wind Generation Time Series Data." International Journal of Pattern Recognition and Artificial Intelligence 29, no. 02 (February 27, 2015): 1550012. http://dx.doi.org/10.1142/s0218001415500123.
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Wind energy is scheduled on the power grid using 0–6 h ahead forecasts generated from computer simulations or historical data. When the forecasts are inaccurate, control room operators use their expertise, as well as the actual generation from previous days, to estimate the amount of energy to schedule. However, this is a challenge, and it would be useful for the operators to have additional information they can exploit to make better informed decisions. In this paper, we use techniques from time series analysis to determine if there are motifs, or frequently occurring diurnal patterns in wind generation data. We compare two different representations of the data and four different ways of identifying the number of motifs. Using data from wind farms in Tehachapi Pass and mid-Columbia Basin, we describe our findings and discuss how these motifs can be used to guide scheduling decisions.
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Illa, Vamsi Ram, Rudranarayan Senapati, and Sarat Chandra Swain. "Implementation of UPQC Alleviating Power Quality Issues in a Hybrid Grid Integrated System." WSEAS TRANSACTIONS ON POWER SYSTEMS 16 (December 26, 2021): 316–35. http://dx.doi.org/10.37394/232016.2021.16.32.
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The advances in the field of power systems, distribution utilities ordinance the associated non-linear advance loads compliance with the stern power quality (PQ) enhances the reliableness of the delivery system to provide demands of censorious loads and subtle automation systems. Hurdles for sustaining quality power are linked with the continuation of elemental VAR power necessities of loads; voltage dips and swells at the point of common coupling (PCC) due to sudden switching of large industrial loads as well as VAR power indemnifying capacitors and harmonic distortions due to voltage and/or current along with non-linear loads. The harmonic distortions are pertained to be the major drawback the root cause of the PQ issues also the fluctuating pattern by loads causes degradation of voltage waveform which has been presented with variable loads. Hence, custom power device (CPD) materialized as Unified Power Quality Conditioner (UPQC) settles the issue. Intention of the work is to bring spontaneity in both the voltage and current waveform with the Sinusoidal current control strategy (SCCS), a time dominion strategy founded over instantaneous pq-theory executed with MATLAB 2016a. The results are well analyzed with proper explanation for selection of the said strategy for the UPQC. As an elementary and inherent strategy, it has titanic prospects further to be applied under photo-voltaic environment associated with a proton exchange membrane fuel cell (FC) in a hybrid grid integrated (HGI) system.
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Polanco Vasquez, Luis, Cristian Carreño Meneses, Alejandro Pizano Martínez, Juana López Redondo, Manuel Pérez García, and José Álvarez Hervás. "Optimal Energy Management within a Microgrid: A Comparative Study." Energies 11, no. 8 (August 19, 2018): 2167. http://dx.doi.org/10.3390/en11082167.
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In this work, we focus on optimal energy management within the context of the tertiary control of a microgrid operating in grid-connected mode. Specifically, the optimal energy management problem is solved in a unified way by using the optimal power flow (OPF) and day-ahead concepts. The elements considered in the microgrid are a photovoltaic panel, a wind turbine, electric vehicles, a storage system, and a point of common coupling with the main grid. The aim of this paper consists of optimizing the economic energy dispatch within the microgrid considering known predictions of electricity demand, solar radiation, and wind speed for a given period of time. The OPF is solved using three different algorithms provided by the optimization toolbox of MATLAB® (R2015a, MathWorks®, Natick, MA, USA): the interior point method (IP), a hybrid genetic algorithm with interior point (GA-IP), and a hybrid direct search with interior point (patternsearch-IP). The efficiency and effectiveness of the algorithms to optimize the energy dispatch within the microgrid are verified and analyzed through a case study, where real climatological data of solar irradiance, wind speed in Almería city, photovoltaic system data, and room load from a bioclimatic building were considered.
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Wen, Chunxue, Yifan Gu, and Peng Wang. "Modeling and Stability Analysis of Interconnected System in Weak Grid." Journal of Physics: Conference Series 2260, no. 1 (April 1, 2022): 012053. http://dx.doi.org/10.1088/1742-6596/2260/1/012053.
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Abstract Compared with the conventional grid, the interconnection system has the advantages of high power supply flexibility, high equipment utilization, small installed capacity, and more economical operation. However, unlike in the analysis of stability, the dynamic response of the converter of the interconnected system is faster, and to model its internal structure and control, a new model applicable to it is needed. The article firstly models three different control types of inverters, then starts from the IEEE 9-bus interconnected system composed of multiple types of inverters, models the system and analyzes its stability by root trajectory calculation, and obtains the influence of each parameter change on the stability of the system, based on this and optimizes the sensitive parameters of the system by sensitivity analysis, so as to enhance the stability of the system. Finally, the theory is verified by time domain simulation, and the correctness of the model is verified.
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Bouderbala, Manale, Hala Alami Aroussi, Badre Bossoufi, and Mohammed Karim. "Real-Time Power Control of Doubly Fed Induction Generator Using Dspace Hardware." Sustainability 15, no. 4 (February 16, 2023): 3638. http://dx.doi.org/10.3390/su15043638.
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Numerous studies have been undertaken to evaluate wind energy systems’ active and reactive power control, the energy produced, and their its link to distribution networks. This research makes a novel contribution to the discipline in this setting. The novelty of this work aims to design a new wind emulator and design a power control approach for a doubly fed induction generator (DFIG)-based wind system. A description of the system was provided first. Secondly, the control strategy was described in detail. Then, it was applied to both converters (machine and grid sides). Three stages were used to evaluate the control solution: (1) a MATLAB/Simulink simulation to validate the reference’s persistence (for both real and step wind speeds) and the system’s robustness, (2) implementation in real-time on a dSPACE-DS1104 board linked to an experimental laboratory bench, and (3) overlapped comparison experimental and simulated data to conduct a thorough quantitative and qualitative analysis using the root-mean-square error measures. The simulation and experimental findings demonstrate that the suggested model is valid and presents an excellent correlation between experimental and simulated results regarding wind speed variation.
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He, Qingsu, Muqing Wu, Pei Sun, Jinglin Guo, Lina Chen, Lihua Jiang, and Zhiwei Zhang. "Research on Charging Mechanism of Electric Vehicle Biased to Photovoltaic Nearby Absorption Strategy." Electronics 11, no. 20 (October 20, 2022): 3407. http://dx.doi.org/10.3390/electronics11203407.
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With the promotion of the pilot development of distributed whole county roof photovoltaics in China, problems such as power consumption, energy regional balance, and grid stability have become prominent. In this paper, an application mode of electric vehicle (EV) charging network and distributed photovoltaic power generation local consumption is studied. The management idea of two-layer and four model has been established, including the regional distributed photovoltaic output model, electricity consumption model, EV consumption model, and regional grid load dispatching model, which can realize the scheduling of the energy flow formed by photovoltaic, induce the charging of EVs, and make the photovoltaic consumption in office building areas and residential building areas complementary. Firstly, according to the randomness of photovoltaic power generation and EV charging, the dynamic response capability, power support capability, effective convergence time, system stability, system failure rate, and other characteristics of regional loads are comprehensively analyzed, and the grid energy management model of EV charging network and distributed photovoltaic is proposed. Secondly, according to certain statistical characteristics, the distributed photovoltaic will be concentrated, and EV charging will be prioritized to achieve nearby consumption. Finally, different scenarios are described, and the scenarios of charging in the park, community life, and power supply service are selected for analysis. This mode is intended to guide the consumption of new energy through economic leverage, which can realize the unified regulation of distributed energy convergence, consumption and storage.
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Wilson, Aaron J., Bruce R. J. Warmack, Ali Riza Ekti, and Yilu Liu. "Non-Parametric Statistical Analysis of Current Waveforms through Power System Sensors." Sensors 22, no. 22 (November 15, 2022): 8827. http://dx.doi.org/10.3390/s22228827.
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The protection, control, and monitoring of the power grid is not possible without accurate measurement devices. As the percentage of renewable energy sources penetrating the existing grid infrastructure increases, so do uncertainties surrounding their effects on the everyday operation of the power system. Many of these devices are sources of high-frequency transients. These transients may be useful for identifying certain events or behaviors otherwise not seen in traditional analysis techniques. Therefore, the ability of sensors to accurately capture these phenomena is paramount. In this work, two commercial-grade power system distribution sensors are investigated in terms of their ability to replicate high-frequency phenomena by studying their responses to three events: a current inrush, a microgrid “close-in”, and a fault on the terminals of a wind turbine. Kernel density estimation is used to derive the non-parametric probability density functions of these error distributions and their adequateness is quantified utilizing the commonly used root mean square error (RMSE) metric. It is demonstrated that both sensors exhibit characteristics in the high harmonic range that go against the assumption that measurement error is normally distributed.
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Taherian, Hessam, and Robert W. Peters. "Performance of a Mid-Size Net-Zero Energy Solar House." Applied Sciences 12, no. 6 (March 15, 2022): 3005. http://dx.doi.org/10.3390/app12063005.
Full textAbstract:
The University of Alabama at Birmingham (UAB) was one of 16 collegiate teams from around the world that participated in the U.S. Department of Energy Solar Decathlon 2017 competition. An interdisciplinary team of students from across the university was engaged in a 2-year long process to design and build a house that is powered completely by solar power. The house was equipped to run all the typical appliances of an average modern house at similar levels on a conventional power grid. The net-zero house was built and tested on the UAB campus. Considering Birmingham’s weather, a safe room was built to ensure the safety of occupants during events of extreme weather, such as a tornado. A ductless HVAC unit consisting of an inverter-type 3-speed outdoor unit supplied refrigerant to four high-wall indoor units providing the primary source of space conditioning. To achieve a model of efficiency and cost effectiveness, the house incorporated a heavily insulated envelope and precise glazing protection. The roof, floor framing and walls had R-30 batt and foam insulation. With a design informed by southern vernacular language, the building is oriented to maximize solar access and to use roof planes for shading the majority of the year. Peak power generation of the panels was recorded at 9.6 kW. The home has a centralized energy management system that can provide access to energy consumption data and allow control of lighting, appliances, and plug loads remotely. Energy modeling showed that the annual electricity consumption for heating and cooling with variation in wall types were 8470 to 11,661 kWh. For the month of October, it was calculated varying from 683 to 763 kWh, with varying air changes per hour from 0 to 1.5.
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Valencia-Rivera, Gerardo Humberto, Luis Ramon Merchan-Villalba, Guillermo Tapia-Tinoco, Jose Merced Lozano-Garcia, Mario Alberto Ibarra-Manzano, and Juan Gabriel Avina-Cervantes. "Hybrid LQR-PI Control for Microgrids under Unbalanced Linear and Nonlinear Loads." Mathematics 8, no. 7 (July 4, 2020): 1096. http://dx.doi.org/10.3390/math8071096.
Full textAbstract:
A hybrid Linear Quadratic Regulator (LQR) and Proportional-Integral (PI) control for a MicroGrid (MG) under unbalanced linear and nonlinear loads was presented and evaluated in this paper. The designed control strategy incorporates the microgrid behavior, low-cost LQR, and error reduction in the stationary state by the PI control, to reduce the overall energetic cost of the classical PI control applied to MGs. A Genetic Algorithm (GA) calculates the parameters of LQR with high-accuracy fitness function to obtain the optimal controller parameters as settling time and overshoot. The gain values of the classical PI controller were determined through the improved LQR values and geometrical root locus. When MG operates in the grid-tied mode under unbalanced conditions, the controller performance of the Current Source Inverter (CSI) of the MG is considerably affected. Consequently, the CSI operates in a negative-sequence mode to compensate for unbalanced current at the Point of Common Coupling (PCC) between the MG and the utility grid. The study cases involved the reduction of the negative-sequence percentage in the current at the PCC, mitigation of harmonics in the current signal injected by the MG, and close related power quality issues. All these cases have been analyzed by implementing an MG connected at the PCC of a low-voltage distribution network. A numerical model of the MG in Matlab/Simulink was implemented to verify the performance of the designed LQR-PI control to mitigate or overcome the power quality concerns. The extensive simulations have permitted verifying the robustness and effectiveness of the proposed strategy.
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Nan, Dongliang, Weiqing Wang, Kaike Wang, Rabea Jamil Mahfoud, Hassan Haes Alhelou, and Pierluigi Siano. "Dynamic State Estimation for Synchronous Machines Based on Adaptive Ensemble Square Root Kalman Filter." Applied Sciences 9, no. 23 (November 29, 2019): 5200. http://dx.doi.org/10.3390/app9235200.
Full textAbstract:
Dynamic state estimation (DSE) for generators plays an important role in power system monitoring and control. Phasor measurement unit (PMU) has been widely utilized in DSE since it can acquire real-time synchronous data with high sampling frequency. However, random noise is unavoidable in PMU data, which cannot be directly used as the reference data for power grid dispatching and control. Therefore, the data measured by PMU need to be processed. In this paper, an adaptive ensemble square root Kalman filter (AEnSRF) is proposed, in which the ensemble square root filter (EnSRF) and Sage–Husa algorithm are utilized to estimate measurement noise online. Simulation results obtained by applying the proposed method show that the estimation accuracy of AEnSRF is better than that of ensemble Kalman filter (EnKF), and AEnSRF can track the measurement noise when the measurement noise changes.
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Konstantinou, Maria, Stefani Peratikou, and Alexandros G. Charalambides. "Solar Photovoltaic Forecasting of Power Output Using LSTM Networks." Atmosphere 12, no. 1 (January 18, 2021): 124. http://dx.doi.org/10.3390/atmos12010124.
Full textAbstract:
The penetration of renewable energies has increased during the last decades since it has become an effective solution to the world’s energy challenges. Among all renewable energy sources, photovoltaic (PV) technology is the most immediate way to convert solar radiation into electricity. Nevertheless, PV power output is affected by several factors, such as location, clouds, etc. As PV plants proliferate and represent significant contributors to grid electricity production, it becomes increasingly important to manage their inherent alterability. Therefore, solar PV forecasting is a pivotal factor to support reliable and cost-effective grid operation and control. In this paper, a stacked long short-term memory network, which is a significant component of the deep recurrent neural network, is considered for the prediction of PV power output for 1.5 h ahead. Historical data of PV power output from a PV plant in Nicosia, Cyprus, were used as input to the forecasting model. Once the model was defined and trained, the model performance was assessed qualitative (by graphical tools) and quantitative (by calculating the Root Mean Square Error (RMSE) and by applying the k-fold cross-validation method). The results showed that our model can predict well, since the RMSE gives a value of 0.11368, whereas when applying the k-fold cross-validation, the mean of the resulting RMSE values is 0.09394 with a standard deviation 0.01616.
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Madhu, M. C., K. Badari Narayana, and J. Krishna Kishore. "Hybrid DC-AC homes with roof top solar power." E3S Web of Conferences 239 (2021): 00017. http://dx.doi.org/10.1051/e3sconf/202123900017.
Full textAbstract:
The paper investigates the feasibility of a hybrid DC-AC home with roof top solar power. In recent times, roof top solar power has become popular for residential homes. Generally, the power obtained from roof-top solar panels is converted to AC with a power control unit and routed to the existing wiring network of the houses designed essentially to support the Electric Utilities which deliver AC power. Solar power with DC bus routing power to various sub-units and Brushless DC (BLDC) motor-based systems have been successfully flown in satellites for decades. The study presents the possibility of having a dedicated DC bus (24V / 48V) in the home connected directly to roof-top solar panels along with the traditional wiring network to support AC power (220-230V) from Electric Utilities. The recent success of the BLDC based home appliances further highlights the potential. This will also help to benefit from higher efficiency due to BLDC and avoid the conversion losses as home appliances that can run on DC power are presently available. It is now possible to have an independent local Roof Top solar power-based DC home-grid to support lighting circuit and home-appliances that operate on DC power. The existing wiring network for AC can continue to support high power equipment like motors, boilers, washing machines etc., It will also simplify the power control unit as the traditional inverter portion is avoided. Thus, the proposed hybrid DC-AC home needs be viewed in terms of an overall green approach which will be a paradigm shift for energy efficiency and lower carbon footprint. It has the potential to boost the sale of DC home appliances.
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Madhu, M. C., K. Badari Narayana, and J. Krishna Kishore. "Hybrid DC-AC homes with roof top solar power." E3S Web of Conferences 239 (2021): 00025. http://dx.doi.org/10.1051/e3sconf/202123900025.
Full textAbstract:
The paper investigates the feasibility of a hybrid DC-AC home with roof top solar power. In recent times, roof top solar power has become popular for residential homes. Generally, the power obtained from roof-top solar panels is converted to AC with a power control unit and routed to the existing wiring network of the houses designed essentially to support the Electric Utilities which deliver AC power. Solar power with DC bus routing power to various sub-units and Brushless DC (BLDC) motor-based systems have been successfully flown in satellites for decades. The study presents the possibility of having a dedicated DC bus (24V / 48V) in the home connected directly to roof-top solar panels along with the traditional wiring network to support AC power (220-230V) from Electric Utilities. The recent success of the BLDC based home appliances further highlights the potential. This will also help to benefit from higher efficiency due to BLDC and avoid the conversion losses as home appliances that can run on DC power are presently available. It is now possible to have an independent local Roof Top solar power-based DC home-grid to support lighting circuit and homeappliances that operate on DC power. The existing wiring network for AC can continue to support high power equipment like motors, boilers, washing machines etc., It will also simplify the power control unit as the traditional inverter portion is avoided. Thus, the proposed hybrid DC-AC home needs be viewed in terms of an overall green approach which will be a paradigm shift for energy efficiency and lower carbon footprint. It has the potential to boost the sale of DC home appliances.
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Chamorro, Harold R., Alvaro D. Orjuela-Cañón, David Ganger, Mattias Persson, Francisco Gonzalez-Longatt, Lazaro Alvarado-Barrios, Vijay K. Sood, and Wilmar Martinez. "Data-Driven Trajectory Prediction of Grid Power Frequency Based on Neural Models." Electronics 10, no. 2 (January 12, 2021): 151. http://dx.doi.org/10.3390/electronics10020151.
Full textAbstract:
Frequency in power systems is a real-time information that shows the balance between generation and demand. Good system frequency observation is vital for system security and protection. This paper analyses the system frequency response following disturbances and proposes a data-driven approach for predicting it by using machine learning techniques like Nonlinear Auto-regressive (NAR) Neural Networks (NN) and Long Short Term Memory (LSTM) networks from simulated and measured Phasor Measurement Unit (PMU) data. The proposed method uses a horizon-window that reconstructs the frequency input time-series data in order to predict the frequency features such as Nadir. Simulated scenarios are based on the gradual inertia reduction by including non-synchronous generation into the Nordic 32 test system, whereas the PMU collected data is taken from different locations in the Nordic Power System (NPS). Several horizon-windows are experimented in order to observe an adequate margin of prediction. Scenarios considering noisy signals are also evaluated in order to provide a robustness index of predictability. Results show the proper performance of the method and the adequate level of prediction based on the Root Mean Squared Error (RMSE) index.