Active Power Values Research Articles

Adaptive Control Strategy of Parallel Virtual Synchronizer of Wind–Solar–Storage Microgrid Based on Neural Network

In order to solve the problem that the impedance of each line of the parallel system of the wind–solar–storage virtual synchronous machine(VSG) is inconsistent, resulting in the power circulation between the parallel VSG, a multi-parameter collaborative adaptive control strategy for the parallel virtual synchronizers of a wind–solar–storage microgrid based on a neural network was proposed. Firstly, the topology of the virtual synchronous machine parallel system of the wind–solar–storage microgrid was built, and the VSG was analyzed. Then, the neural network algorithm was used to realize the adaptive adjustment of each parameter of VSG, which improves the uneven power distribution and the influence of circulation. Next, the parameters of multiple parallel VSG control systems were configured. Finally, MATLAB2021a/Simulink was used to model the system, and the VSG capacity under different scale conditions was simulated and analyzed. The simulation results show that when the capacity ratio of VSG1 and VSG2 is 1:1, the active power output is 9000 W, and the reactive power output is 7500 Var, which realizes accurate distribution, and when the capacity ratio of VSG1 and VSG2 is 2:1, the output values of active power and reactive power are 12,000 W/6000 W and 10,000 Var/5000 Var, and the output is carried out according to the ratio of 2:1, which shows that the control strategy can effectively improve the power allocation accuracy, suppressing circulation.

Performance analysis of interlinking converter exchanging power between AC/DC renewable microgrids with advanced control technique

In a distribution system there are many types of AC/DC microgrids integrated at different locations. These microgrids may contain conventional or renewable sources which generate power using natural resources. The power generated by these microgrid sources is uncertain as the natural resources are unpredictable. Therefore, powers from these AC/DC micro grids need to be shared so as to compensate the load demand throughout the distribution system. An interlinking converter (ILC) is connected between the AC/DC microgrids operated by a novel advanced PQ control technique. Both the DC and AC microgrids are interconnected through ILC achieving power exchange between them as per the power demand and generation on both microgrids. Different operating conditions are considered for the analysis and the simulation of these modules are done using MALTAB/Simulink software. Several parameters like DC link voltage, ILC currents, point of common coupling (PCC) frequency, total harmonic distortions (THDs) and active power values are considered for validating the stability of the considered system.

Optimal control of a doubly fed induction generator of a wind turbine in cooperation with weak and rigid grids

In this article a control method for a rotor side converter (RSC) of a doubly fed induction generator of a wind turbine is developed. The doubly-fed induction generator (DFIG) system of a wind energy power plant that improves grid symmetrization was applied. The issue of optimal control was treated as an extended linear quadratic regulator (ELQR) having an extra set of exogenous inputs, which are source voltages of the electric grid. No additional knowledge of equations modelling the exogenous inputs was assumed. The proposed method is much more efficient than the currently available linear quadratic control methods. The control objective for a weak grid was to maintain the given value of the voltage module on load terminals and the given value of active power transferred from the stator’s winding. First harmonic components of relevant waveforms were used for this purpose. This task also required the DFIG system to provide reactive power to the grid. In the case of a rigid grid, this reactive power would be too high. Therefore, in this case, it was assumed that the system would supply only part of the required active and reactive power, based on its capabilities. It was required that the voltage and current ratings of the system, mainly the DFIG, were not exceeded. Therefore, the parameters of the network in these difficult failure cases were corrected only partially. The behaviour of the grid in the conditions of failure, as well as the return to the steady state after failure disappearance, were studied.

A semi-automatic analytical methodology for characterizing the energy consumption of MRI systems using load duration curves.

Magnetic resonance imaging (MRI) scanners are a major contributor to greenhouse gas emissions from the healthcare sector, and efforts to improve energy efficiency and reduce energy consumption rely on quantification of the characteristics of energy consumption. The purpose of this work was to develop a semi-automatic analytical methodology for the characterization of the energy consumption of MRI systems using only the load duration curve (LDC). LDCs are a fundamental tool used across various fields to analyze and understand the behavior of loads over time. An electric current transformer sensor and data logger were installed on two 3T MRI scanners from two vendors, termed M1 (outpatient scanner) and M2 (inpatient/emergency scanner). Data was collected for 1 month (7/11/2023 to 8/11/2023). Active power was calculated, assuming a balanced three-phase system, using the average current measured across all three phases, a 480V reference voltage for both machines, and vendor-provided power factors. An LDC was constructed for each system by sorting the active power values in descending order and computing the cumulative time (in units of percentage) for each data point. The first derivative of the LDC was then computed (LDC'), smoothed by convolution with a window function (sLDC'), and used to detect transitions between different system modes including (in descending power levels): scan, prepared-to-scan, idle, low-power, and off. The final, segmented LDC was used to measure time (% total time), total energy (kWh), and mean power (kW) for each system mode on both scanners. The method was validated by comparing mean power values, computed using the segmented 1-month LDC, for each nonproductive system mode (i.e., prepared-to-scan, idle, lower-power, and off) against power levels measured after a deliberate system shutdown was performed for each scanner (1 day worth of data). The validation revealed differences in mean power values<1.4% for all nonproductive modes and both scanners. In the scan system mode, the mean power values ranged from 29.8 to 37.2kW and the total energy consumed for 1 month ranged from 11106 to 14466kWh depending on the scanner. Over the course of 1 month, the portion of time the scanners were in nonproductive modes ranged from 76% to 80% across scanners and the nonproductive energy consumption ranged from 8010 to 6722kWh depending on the scanner. The M1 (outpatient) scanner consumed 99.9 and 183.9kWh/day in idle mode for weekdays and weekends, respectively, because the scanner spent 23% more time proportionally in idle mode on the weekends. A semi-automatic method for quantifying energy consumption characteristics of MRI scanners was introduced and validated. This method is relatively simple to implement as it requires only power data from the scanners and avoids the technical challenges associated with extracting and processing scanner log files. The methodology enables quantitative evaluation of the power, time, and energy characteristics of MRI scanners in scan and nonproductive system modes, providing baseline data and the capability of identifying potential opportunities for enhancing the energy efficiency of MRI scanners.

Design of Automatic Power Factor Correction for Optimization of Electric Energy Consumption

Electrical energy is a major human need which, when viewed from its main source, namely fossil energy, will increasingly run out. There needs to be an effort to utilize electrical energy more optimally. The problem discussed in this research is the decline in power factor. The State Electricity Company (PLN) has a minimum power factor standard of above 0.85 which is found in the SPLN 70-1 regulation and PERMEN ESDM No. 09 of 2011. If the power factor is below the minimum limit, it will result in losses, because consumers have to pay for excess kilo Volt Ampere Reactive hours (kVARh). Power factor drops are caused by the use of inductive loads. With automatic power factor correction, the poor power factor from the use of inductive loads will be resolved and optimization of the use of electrical energy can be achieved. From the test results conducted using 3 cumulative loads, the worst power factor value was obtained before PF repair was carried out by the system, namely 0.38 and after PF repair by the best power factor system reached 0.99 and obtained the value of active power and apparent power after PF repair is almost the same (comparable) and it can be said that the optimization of electrical energy occurs in this study.

Performance enhancement of a three-phase grid-connected PV inverter system using fractional-order integral sliding mode controls

Grid-integrated photovoltaic (PV) systems hold significant promise for sustainable energy production. However, these systems often struggle with maintaining energy quality and stability in the face of fluctuating conditions. To address these challenges, this study proposes the use of fractional-order integral sliding mode control (FO-ISMC) for grid-connected PV systems. The system comprises solar panel arrays, a DC/DC boost converter with its controller, and a three-phase inverter integrated into the utility grid. The primary goals of this study are to maximize power extraction from the PV system and to regulate system currents, thereby improving effectiveness and power quality. The proposed method is further refined using the particle swarm optimization (PSO) algorithm to fine-tune parameter settings. By optimizing the command gains of the FOI-SMC, the PSO algorithm enhances system performance and stability. Leveraging fractional-order and integral terms provides the control signal with additional degrees of freedom, enhancing system performance in the presence of internal and external disturbances. Simulation results demonstrate the effectiveness of the proposed controller compared to the classical controller, where in the case of Irradiation taking the value of 500 W/m2, the proposed strategy reduced the values of constant voltage, active power, and reactive power by percentages estimated at 88.18%, 90%, and 70%, respectively, compared to the traditional strategy. Also, the overshoot value of active power was reduced in all completed cases compared to the traditional strategy by percentages estimated at 53.57%, 66.66%, and 65%, respectively. The proposed strategy reduced the response time of reactive power in all cases compared to the traditional strategy by percentages estimated at 58.59%, 28.80%, and 75%, respectively. These ratios show the high performance of the proposed control in improving the characteristics of the studied system compared to traditional control based on PI control.

A power-based fault direction estimation method for active distribution networks

This paper presents a strategy for estimating fault direction in active distribution networks, focusing on the high penetration of distributed energy resources, changing operating conditions, untransposed lines, and unbalanced loads.The proposed strategy introduces a power-based directional criterion derived from analysing active power within three-phase unbalanced systems known for their inherent unidirectional nature. The method enables rapid direction estimation by measuring the difference between pre-fault average active power and during-fault average active power values, utilising two moving windows. Notably, this difference is positive for forward faults and negative for backward faults, offering clear directionality insights. The strategy is validated using a modified IEEE 34-bus test system, where it demonstrates feasibility under several fault scenarios, including all fault types, varying fault impedance, operating conditions, noise levels, and sampling frequencies. Additionally, the proposed algorithm is compared with contemporary and conventional approaches, highlighting its effectiveness.

PSO Tuning of a Second-Order Sliding-Mode Controller for Adjusting Active Standard Power Levels for Smart Inverter Applications

In recent years, due to their ability to supply electricity in isolated places where building electrical transmission networks are expensive, Microgrids (MGs) have gained much attention. A new technology called smart inverters (SIs) is currently implemented in inverter-based MGs. SIs are designed to regulate energy under given standards for connecting inverters to the grid. The closed-loop control of SIs technology is still under study and improvement due to several challenges in fields such as stability and reliability. This paper proposes a DQ control for active power regulation on a single-phase voltage source inverter (SPVSI) using a second order sliding mode control (SMC-2) for addressing the abovementioned concerns. The SMC-2 tuning is performed by a metaheuristic algorithm known as particle swarm optimization (PSO). Moreover, to simulate domestic MGs, the SPSVI operation for tracking active power values is performed by ramp rate references based on standard IEEE Std 1547-2018 for inverters connected to the grid. The SMC-2 was appropriately tuned by a PSO algorithm through MATLABTM and the system simulation through PSCADTM. The results show that the algorithm performed better compared to a classical algorithm such as proportional-integral control in terms of integral absolute error (IAE) and integral square error (ISE).

Study and analysis of modified LMF control method for power quality improvement

This paper presents a least fourth-based control method for distribution static compensator for compensation of power quality issues that are reactive power, issues of current, unbalancing loads. The direct current (DC) link voltage of distribution static compensator operated as self-supported. The control method used to extracting the tuned mass reactive and active power values of load values. They are significant divisions in source reference currents. The comparison of harmonic distraction with PI and PSO-PI controller is discussed. The proposed DSTATCOM is tested under nonlinear load condition and its working is seen as palatable. The proposed system is developed and simulated by utilizing MATLAB/Simulink with accessible sim power tool (SPS).

Realtime hybrid offline-online power loss analysis-based Simulink simulation

&lt;p&gt;The power distribution system applied in Indonesia is the radial system. The system is considered to be the simplest and most economical. The bad or good distribution of electrical power can be observed from the quality of the distribution of power supplied. Voltage has to be monitored and kept constant. An analysis was conducted at Bendul Merisi Feeder which has &lt;br /&gt;11 buses, to find the value of supplied power also the value of voltage drop of each bus. The Simulink method is used to simulate and analyze active and reactive power at each cluster. Based on the result of the simulation analysis, the average was obtained by adding up electrical power received every hour, then dividing by 10, the number of buses connected to the load. The smallest average of active power supplied to each bus happened at 09.00 a.m., i.e. 112137.94 VA. The biggest value of active power supplied to each bus happened at 1.00 p.m., i.e. 115129.05 VA. The total voltage drop that occurred in the distribution supply was 224 volts or 1.12% out of 20 kV supplied, indicating that the supply of voltage was according to the standardized rule implemented by PLN (State Electricity Company), i.e. the voltage drop should not exceed the maximum of 10%.&lt;/p&gt;

Rooted Tree Optimization for Wind Turbine Optimum Control Based on Energy Storage System

The integration of wind turbines (WTs) in variable speed drive systems belongs to the main factors causing low stability in electrical networks. Therefore, in order to avoid this issue, WTs hybridization with a storage system is a mandatory. This paper investigates WT system operating at variable speed. The system contains of a permanent magnet synchronous generator (PMSG) supported by a battery storage system (BSS). To enhance the quality of active and reactive power injected into the network, direct power control (DPC) scheme utilizing space-vector modulation (SVM) technique based on proportional-integral (PI) control is proposed. Meanwhile, to improve the rendition of this method (DPC-SVM-PI), the rooted tree optimization technique (RTO) algorithm-based controller parameter identification is used to achieve PI optimal gains. To compare the performance of RTO-based controllers, they were implemented and tested along with some other popular controllers under different working conditions. The obtained results have shown the supremacy of the suggested PIRTO algorithm compared to competing controllers regarding total harmonic distortion (THD), overshoot percentage, settling time, rise time, average active power value, overall efficiency, and active power steady-state error.

Research on Optimal Scheduling of Power System Based on Ant Colony Algorithm

With the development of new energy technology, the installation of new energy is becoming more and more. After a large number of new energy sources are connected to the power system, the capacity of peak regulation and frequency modulation is gradually insufficient, resulting in poor stability of the power system. Aiming at the problem of poor operation stability after new energy is connected to power system, a power system optimization scheduling method based on ant colony algorithm is proposed. In the model, the objective function is to minimize the total operating cost. The improved ant colony algorithm is used to solve the optimal scheduling model, and the effectiveness of the method is verified by simulation. The results show that this method has better ability of peak regulation and frequency modulation after new energy is added to the power system network, the frequency value and active power value of the power system are reduced, the load fluctuation value of the grid is reduced obviously, and the operation of the power system is more stable.

Analysis of Output Signal Distortion of Galvanic Isolation Circuits for Monitoring the Mains Voltage Waveform.

Different methods for galvanically isolated monitoring of the mains voltage waveform were evaluated. The aim was to determine the level of distortion of the output signal relative to the input signal and the suitability of each method for calculating active power values. Six fixtures were tested: two voltage transformers, an electronic circuit with a current transformer, a standalone current transformer, a simple circuit with optocouplers, and a circuit with an A/D-D/A converter with capacitive coupling. The input and output waveforms were mathematically analyzed by three methods: (1) calculating the spectral components of waveforms and the relative changes in their THD (total harmonic distortion) values, (2) determining the similarity of waveforms according to the size of the area bounded by the input and output waveform curves, and (3) determining the accuracy of the active power calculation based on the output waveform. The time difference in the zero crossing of the input and output signals was measured, and further calculations for the second and third method were performed on the zero-crossing time shift-corrected waveforms. Other aspects of selecting the appropriate type of monitoring element, such as power consumption or overall circuit complexity, were also evaluated.

Nonintrusive Load Identification for Industrial Users Integrated with LSQR and Sequential Leader Clustering

Nonintrusive load identification for industrial users can accurately acquire the operation of each load. However, it is a major challenge in the demand-side response due to the hardship of collection data for modelling, and high precision measuring equipment is required. Aiming at this situation, a nonintrusive load identification method is proposed, combining the least square QR (LSQR) with the sequential leader clustering algorithm. Firstly, regarding accurate depiction of industrial loads, some appropriate load feature indices of steady-state and transient processes are extracted, respectively. For steady-state processes, the active power, the reactive power, and the root mean square (RMS) current value are selected as the feature indices. In the case of transient processes, ten feature indices of three stages are employed: before, during, and after transient events, consisting of the duration of transient events, the RMS current value before and after transient events, the average value of active power before and after transient events, the average value of reactive power before and after transient events, the maximum RMS current value of transient events, etc. On this base, the LSQR algorithm is proposed to decompose unknown composite power to access the operation of various loads at steady-state. The sequential leader clustering algorithm is propounded to classify transient events of typical industrial loads and further identify which kind of loads had switched. Finally, to validate the effectiveness of the presented model, data of industrial loads from a concrete plant are collected, including blender, cement screw, sewage dump, and inclined belt conveyor, and simulation analysis is fulfilled. The results indicate that the model proposed can effectively achieve the nonintrusive industrial load identification, and least unified residue (LUR) is about 10−16, which is much better than the factorial hidden Markov model (FHMM) and the artificial neural network (ANN) model.

Research on Reactive Power Optimization Control of a Series-Resonant Dual-Active-Bridge Converter

In order to meet the demands of the bidirectional transmission of electric vehicle charger power, a series-resonant dual-active-bridge (DAB) converter is investigated in this paper. Firstly, the active and reactive power and zero voltage switching (ZVS) conditions of the full-bridge arm under extended phase-shift modulation, dual phase-shift modulation and triple phase-shift modulation are analyzed. Secondly, with the minimum reactive power as the optimization objective, the extended phase shift (EPS) is finally selected as the modulation method after comparing the minimum reactive power under various modulation methods when the normalized value of active power is varied in the range of 0–1. By constructing the objective function and determining the constraints, an off-line reactive power–minimization control strategy is proposed to achieve the ZVS of the full-bridge arm and, finally, the feasibility of the proposed control strategy is verified by simulation and experiment.

Convex Formulation for Optimal Active and Reactive Power Dispatch

This paper proposes a convex programming model to solve the optimal power flow problem (OPF) related to the problems of generation active power dispatch and opportunity costs to meet the reactive power needs in energy markets. The problem is initially represented as a bilevel optimization problem where the upper level considers the minimization of opportunity costs of generating units through a second-order cone programming OPF model, and the lower level is a linear programming model that minimizes the value of active power offered by generators to the market energy. Subsequently, through the concept of strong duality, the problem is transformed into a one-level convex optimization model. Comparisons of the proposed modeling with other level formulations are presented. Results are presented for the IEEE14 and IEEE30 bus systems.

Methods to Improve Dynamic System Response of Power Compensators Using Supercapacitors in Low-Voltage Ride-Through (LVRT) Conditions

In this paper, a power compensator using supercapacitors in parallel to protect grid-connected devices connected to the distributed power supply in the case of a low-voltage ride-through (LVRT) situation in designed, and a grid-connected device control method with improved responsiveness is proposed. In the LVRT situation, the distributed generation power may boost the DC_link voltage, increasing the risk of destroying grid-connected devices. To prevent this, the power compensator designed in this study absorbs active power in a fault situation and stores it in the supercapacitor to suppress the DC_link voltage rise and efficiently use the power. In addition, we propose methods to improve the response of the grid reactive power through the reactive power compensation of the power compensator in LVRT situation. To this end, the power angle (θPW) was extracted through the formula, and the reactive power command, to be compensated by the power compensator, and the reactive power command, compensated by the grid-connected devices, were calculated according to the active power value. In this way, the grid power controlled by the power compensation device and the grid-connected devices was controlled by the active/reactive power of the same power angle and analyzed mathematically. Active power control and static grid support were performed in the normal state where the reduction rate of the normal value of the grid voltage was around 10%. However, when the grid voltage dropped by 10% to 100%, the reactive power control was appropriately performed with dynamic grid support by increasing the voltage from 10% to 20% or more. We conducted a simulation of the new and renewable energy grid-connected devices using the OPAL-RT-based Hardware-in-the Loop Simulation (HILS) system to control the proposed active/reactive power.

Day-Ahead Optimal Dispatch for Active Distribution Network Considering Probability Model of Controllable Distributed Generation

In this paper, the probabilistic model of the controllable distributed generation in active distribution network is developed and applied to the daily stochastic optimal dispatch. The probabilistic characteristics of photovoltaic power generation system with active control capability are explored, and the relationship between the reference value of active power and its cumulative distribution function and mean value is obtained. The active power probability model of wind power generation system is improved according to the actual wind speed power curve. By fully utilizing the inverter capacity and coordinating active power, the reactive power of distributed generation is actively controlled under the constraint of power factor. Then considering the chance constraints, a daily optimal scheduling model for active distribution network with the goal of minimizing the operating cost of distribution network is developed, and the constraints that can calculate the charge and discharge times of the energy storage system are designed. The chance constrained programming is solved by the heuristic method, and the deterministic optimization steps are solved by the second-order cone programming method, respectively. The probabilistic power flow method based on stochastic response surface method is utilized to test chance constraints. Finally, the modified IEEE33 node distribution system example shows that the obtained models and algorithms are correct and can meet the requirements of safe and economic operation.

EVALUATION OF FINANCIAL AND TECHNICAL INDICATORS OF EFFICIENCY OF MICROGRID WORK IN DYNAMIC MODES

The analysis showed the significant spread and successful operation of modern local Microgrid systems, which are considered as a group of interconnected loads and dispersed energy resources within clearly defined territorial boundaries and act as a single managed object for a higher level network and can connect or disconnect from this network to be able to work in both connected and island mode. An assessment of the financial and technical performance of Microgrid in dynamic modes, in particular, the development of Microgrid to ensure optimal generation and consumption regimes in terms of their performance in local markets. The Microgrid has been identified as being able to improve the stability, reliability, quality, and safety of conventional distribution systems, making it a more reliable and useful technique for generating electricity and reducing the use of non-renewable energy sources.&#x0D; It is shown that the advantages of dynamic charging are most fully manifested at the local level, and modern interaction of participants in the market of ancillary services involves increasing the role of aggregates of aggregate and aggregates of dispersed consumption. -models with a combination of physical, communication, information, and business levels. The tariff for dynamic pricing should be considered as one of the most efficient and economical programs, in which the price of electricity changes over a period. At the same time, charging must be based on dynamic models, which should include the fundamentally dynamic nature of regulating the capacity of the system and stimulating the relevant desired actions by the consumer. The application of tariff calculation in dynamic tariffing is proposed not by time interval, but by state; summing up the real balance of energy components (instantaneous and integral values); formation for further control of optimality of levels of generation and consumption of the electric power, in particular, in the form of the reference tariff and reference profiles of generation and consumption of the electric power.&#x0D; The influence of dynamic pricing on Microgrid functions is determined taking into account the factors that affect electricity demand and depend on the modes of operation of the generator and load, in particular, with the allocation of the "reference tariff". It is substantiated that efficient dynamic pricing is possible with the use of Smart meters with minimum requirements that allow you to reliably monitor the cost of primary fuel for generation and electricity consumption in specific time intervals. The developed algorithm for calculating the price of primary fuel depending on the uneven consumption of active power over a period allows you to use dynamic charging when changing modes of operation of Microgrid generators, while providing an adequate price for consumers and producers of primary fuel and electricity supplied and consumed. Using the Frieze power modification, the developed algorithm provides for the calculation of the optimal value of active power, which corresponds to a uniform power consumption and is characterized by minimal use of primary fuel.&#x0D; The need to combine technical and economic (financial, price) indicators in business models and technical means at the Microgrid level is substantiated, which will significantly improve the process of managing electricity demand in the local electricity market. The proposed algorithm allows studying the impact of a rapid change in the level of generator power and power consumption on changes in cost indicators of the system, the introduction of demand management mechanisms and measures to improve energy efficiency.

Model predictive direct power control scheme for Vienna rectifier with constant switching frequency

Model predictive direct power control (MPDPC) has strong robustness and fast dynamic response, so it is widely applied in the control system of grid-connected converter. However, the traditional FCS-MPC bears with variable switching state, which will reduce the current tracking accuracy, accidentally produce current ripple and electromagnetic noise. Here, a double closed-loop control strategy with constant switching frequency based on optimal switching sequence synthesis of model predictive direct power control (MPDPC-CF) in the inner loop and SMC control in the outer loop is proposed for the non-linear system of Vienna rectifier. Firstly, the Vienna rectifier is modelled to obtain the predicted values of input power. Then, the given values of active power and reactive power are obtained through the outer loop. Three adjacent voltage vectors with the lowest cost function in the sector are selected to synthesize the optimal voltage vector, and the pulse time of the corresponding vector is calculated according to the cost function of the voltage vector. To verify the correctness of the theoretical analysis, the Vienna rectifier is taken as the research object, and the comparison with the traditional MPDPC shows that the proposed constant frequency model predictive control has good steadystate and dynamic performance.