Use Of Reactive Power Research Articles

Utilize the Prediction Results from the Neural Network Gate Recurrent Unit (GRU) Model to Optimize Reactive Power Usage in High-Rise Buildings

The growing urbanization and the construction sector, efficient use of electric energy becomes important, especially the use of reactive power. If excessive use causes decreased efficiency and increased operational costs. Decreased efficiency contributes to increasing exhaust gas volumes and greenhouse emissions. Efficient energy can achieved if planning and predictions are correct. This research applies the GRU neural network method with grid search initialization as a novelty predictive model for energy-use high-rise buildings in form fast training without multiple iterations because optimal hyperparameters are obtained. Experimental show the MAE and RMSE performance metrics of the GRU better than LSTM in predicting energy consumption data peak loads, off-peak loads and reactive power. The accuracy of GRU predictions can optimize the use of energy to contribute to saving the environment from exhaust emissions and the greenhouse effect in urban systems. Experimental results demonstrate the superiority of GRU over LSTM, proof of the much lower MAE and RMSE values. This metric shows the accuracy of GRU in generalizing data both during peak and off-peak hours, as well as in reactive power usage. By Utilizing GRU's capabilities, building management can manage reactive power usage effectively, allocate reactive power resources appropriately, and mitigate peak load times and the power factor within the threshold, thus avoiding additional costs and electrical system efficiency and contributing to reducing the carbon footprint and gas emissions greenhouse. Research on GRU is widely open in the high-rise building sector, including its integration with sensors to automatically control energy use.

Analisis Tinjauan Ekonomi Teknis dalam Pemasangan Kapasitor Bank untuk Memperbaiki Nilai Faktor Daya pada Beban Industri

Industry is one of the largest users of reactive power in the distribution of electric power. Industries use equipment such as induction motors, transformers and other equipment to support their production needs. Loads such as induction motors are inductive loads that require reactive power to operate. Reactive power in an electric power distribution network is a loss. Reactive power can reduce the effectiveness of the real power which is converted into active power so that the efficiency of real power usage is reduced. Installing a capacitor bank is one way to compensate for the use of reactive power in a load. Installing capacitor banks aims to improve the value of the power factor that has decreased due to the use of excessive reactive power loads. PLN has set a standard power factor value for consumers of 0.85 and reactive power consumption of 0.62 of the total power consumption. For this reason, it is necessary to carry out further analysis regarding the advantages and disadvantages of installing bank capacitors to improve the value of the power factor so that the ideal economic factor for consumers is obtained.

Analisis Perencanaan Capacitor Bank Untuk Perbaikan Faktor Daya Pada Pusat Perbelanjaan Blitar Square

Power factor is the ratio between active power (W) and apparent power (VA). In an electrical installation, the quality of electric power can be said to be good if the value of the power factor is above a predetermined standard of 0.85 according to the Minister (ESDM) Number 30 of 2012 [1]. From the research that has been done at the Blitar Square Shopping Center, it was found that the power factor value is still below the standard with an average value of 0.711. With the low power factor value, this shopping center gets a penalty from PT. PLN (Persero) due to the use of reactive power. Therefore, it is necessary to make efforts to improve the power factor by installing a capacitor bank. The installation of this capacitor bank is expected to be able to increase the power factor value with a power factor target of 0.98 and reduce the charge for reactive power usage penalties. The calculation results show that global compensation requires 12 capacitor banks with a rating of 10.4 kVAR, while sectoral compensation on the chiller load panel requires 7 capacitor banks with a rating of 10.4 kVAR and the foodmart load panel requires a capacitor bank with a rating of 10. 4 kVAR is 6 pieces. In simulating the installation of a capacitor bank using the ETAP application, it is known that the installation of a capacitor bank can increase the power factor value. In addition, the installation of a capacitor bank also results in an increase in the voltage value in the system, this voltage increase is still below the permissible standard of ± 5%. The simulation of installing a capacitor bank on global compensation can improve the power factor value from 72.99% to 96.97%, with a voltage increase of 0.479% from the initial value of 397 V to 398.9 V, and a decrease in the current value of 24.645% from the initial value. 330.7 A to 249.2 A. While the simulation of installing a capacitor bank in sectoral compensation can improve the power factor value from 72.99% to 93.57%, with a voltage increase of 0.401% from the initial value of 397 V to 398.6 V , and a decrease in the value of current by 21.593% from the initial value of 330.7 A to 258.1 A. The cost of installing a capacitor bank in global compensation was Rp. 189,897,500 while the sectoral compensation is Rp. 211.305.600. It can be concluded that the installation of a capacitor bank using the global compensation method is more effective.

OPTIMISED REACTIVE POWER DISPATCH TO INCREASE NETWORK'S ELECTRIC VEHICLE HOSTING CAPACITY

The transition towards net zero 2050 has begun. As a result, distribution networks are seeing and expecting an increased amount of low carbon technologies (LCTs) connected within distribution networks. Increasing numbers of LCTs connected in distribution networks results in new constraints on the distribution systems that traditionally would have resulted in the installation of more network infrastructure. This project investigated an alternative approach to optimise the reactive power dispatch of existing generators to increase the network's hosting capacity for new LCT connections. This paper presents a potential flexible reactive power service using an optimisation algorithm to determine the reactive power dispatch to increase load headroom, reduce network losses and manage network constraints. Analysis was undertaken using the optimisation algorithm for a range of operating conditions across 3 different Bulk Supply Point (BSP) networks. The results demonstrate that with optimised reactive power dispatch the networks provided headroom for the equivalent of 10,000 additional Electric Vehicles (EVs) connected across the 3 BSP networks. The flexible use of reactive power within distribution networks has the potential to form a key component of the transition to net zero 2050.

Design, Analysis and Tuning of an Optimal Controller for an AVR: A Simulation Approach

Terminal voltage of the generator keeps changing when there is a mismatch between generator supply and load demand. Particularly when load increases terminal voltage of the generator decreases. This problem can be mitigated by the use of reactive power but it leads to the damage of stator winding. To overcome this Automatic voltage regulator (AVR) is used. But it is not robust. To enhance the stability and working of an AVR system, an optimal PID controller is used. In this paper, a combination of Bacteria Foraging (BF) and Particle Swarm Optimization (PSO) is used for regulating the strictures of PID controller of an AVR to get the better optimization parameter values. The performance of the algorithm is studied using MATLAB and is equated with the Bacterial Foraging algorithm and Particle swarm Optimization. Simulation outcome evidently clarify that the suggested approach is very effective and efficient as compared to further population centered global optimization algorithms.

Reactive Power Management Considering Stochastic Optimization under the Portuguese Reactive Power Policy Applied to DER in Distribution Networks

Challenges in the coordination between the transmission system operator (TSO) and the distribution system operator (DSO) have risen continuously with the integration of distributed energy resources (DER). These technologies have the possibility to provide reactive power support for system operators. Considering the Portuguese reactive power policy as an example of the regulatory framework, this paper proposes a methodology for proactive reactive power management of the DSO using the renewable energy sources (RES) considering forecast uncertainty available in the distribution system. The proposed method applies a stochastic sequential alternative current (AC)-optimal power flow (SOPF) that returns trustworthy solutions for the DSO and optimizes the use of reactive power between the DSO and DER. The method is validated using a 37-bus distribution network considering real data. Results proved that the method improves the reactive power management by taking advantage of the full capabilities of the DER and by reducing the injection of reactive power by the TSO in the distribution network and, therefore, reducing losses.

Challenges in analysis of antihypertensive exposures and birth defect rates in women with chronic hypertension: an evaluation of the German Embryotox Database

Distributed photovoltaic (PV) generator systems (especially rooftop PV) have been increasing significantly in electrical power systems. However, due to the variability of their output power, it is challenging to integrate large number of these PV generator systems into the existing electrical grid. These distributed PV generator systems can cause large voltage fluctuations due to the oscillation in their power output and reverse power flow in highly penetrated areas. While real power curtailment is an option to manage voltage issues, it reduces the production of this clean energy and is governed by policies and contracts. Traditionally, the use of reactive power to control voltage on a power grid is done through maintaining the voltage within a tolerable range by using transformer tap-changers (TPC), capacitor banks (CB), voltage regulators (VR), static synchronous compensator (STATCOM), and static Var compensators (SVC). Installation and maintenance costs of these devices can be quite high and some have relatively slow response times on the order of many seconds. A smart PV inverter can help regulate voltage by absorbing and injecting reactive power (Var) to/from the grid by using the Volt-Var control function. This paper presents an experimental analysis of the inverter Volt-Var control method for voltage regulation. The capacitive (i.e., Var injection) and inductive (i.e., Var absorption) effects of using a smart inverter and its ability to influence the voltage at the distribution level is investigated in this paper. When the smart PV inverter injects reactive power, it increases the distribution voltage. Conversely, voltage is reduced when the smart inverter absorbs reactive power. As a result, electric power utilities can control the distribution voltage without installing additional devices on the power network. The analyses from a field deployment under the Maui Advanced Solar Initiative Project in Hawaii is discussed here.

Distributed voltage regulation using Volt-Var controls of a smart PV inverter in a smart grid: An experimental study

Distributed photovoltaic (PV) generator systems (especially rooftop PV) have been increasing significantly in electrical power systems. However, due to the variability of their output power, it is challenging to integrate large number of these PV generator systems into the existing electrical grid. These distributed PV generator systems can cause large voltage fluctuations due to the oscillation in their power output and reverse power flow in highly penetrated areas. While real power curtailment is an option to manage voltage issues, it reduces the production of this clean energy and is governed by policies and contracts. Traditionally, the use of reactive power to control voltage on a power grid is done through maintaining the voltage within a tolerable range by using transformer tap-changers (TPC), capacitor banks (CB), voltage regulators (VR), static synchronous compensator (STATCOM), and static Var compensators (SVC). Installation and maintenance costs of these devices can be quite high and some have relatively slow response times on the order of many seconds. A smart PV inverter can help regulate voltage by absorbing and injecting reactive power (Var) to/from the grid by using the Volt-Var control function. This paper presents an experimental analysis of the inverter Volt-Var control method for voltage regulation. The capacitive (i.e., Var injection) and inductive (i.e., Var absorption) effects of using a smart inverter and its ability to influence the voltage at the distribution level is investigated in this paper. When the smart PV inverter injects reactive power, it increases the distribution voltage. Conversely, voltage is reduced when the smart inverter absorbs reactive power. As a result, electric power utilities can control the distribution voltage without installing additional devices on the power network. The analyses from a field deployment under the Maui Advanced Solar Initiative Project in Hawaii is discussed here.

Active Management of Low-Voltage Networks for Mitigating Overvoltages Due to Photovoltaic Units

In this paper, the overvoltage problems that might arise from the integration of photovoltaic (PV) panels into low-voltage (LV) distribution networks is addressed. A distributed scheme is proposed that adjusts the reactive and active power output of inverters to prevent or alleviate such problems. The proposed scheme is model-free and makes use of limited communication between the controllers in the form of a distress signal only during emergency conditions. It prioritizes the use of reactive power, while active power curtailment is performed only as a last resort. The behavior of the scheme is studied using dynamic simulations on a single LV feeder and on a larger network composed of 14 LV feeders. Its performance is compared with a centralized scheme based on the solution of an optimal power flow (OPF) problem, whose objective function is to minimize the active power curtailment. The proposed scheme successfully mitigates overvoltage situations due to high PV penetration and performs almost as well as the OPF-based solution with significantly less information and communication requirements.

Distributed Energy Storage with Real and Reactive Power Controller for Power Quality Issues Caused by Renewable Energy and Electric Vehicles

AbstractThe integration of renewable energy sources (RE) and electric vehicles (EV) into the low voltage (LV) networks can create a number of power quality issues. RE or EV can cause voltage unbalance and low power factor when it injects or absorbs real power from the network. The energy storage system can be connected to the network to manipulate the power flow from or to those devices with the use of reactive power as a complementary support, hence correcting the voltage unbalance and power factor effectively without wasting any generated energy. To be able to correct the voltage unbalance and power factor effectively under the intermittent power of RE and EV, a novel fuzzy controller is developed and implemented in the energy storage to manipulate the flow of real and reactive power between the energy storage and the network based on the network conditions. The fuzzy controller is able to reduce any voltage excursions with the use of real and reactive power from the energy storage, hence reducing the v...

Combined Central and Local Active and Reactive Power Control of PV Inverters

The increasing amount of photovoltaic (PV) generation results in a reverse power flow and a violation of the overvoltage limits in distribution networks. PV inverters can curtail active power or consume reactive power to avoid these excessive high voltages. Local controllers of active and reactive power that are based on measurements of the produced PV power have a fast response to the changing production levels of the PV installation. The performance of these local controllers depends on the tuning of the control parameters, which are grid and time dependent. In this paper, local control functions are defined as piecewise linear functions. The parameters of all the local control functions are regularly reoptimized. This results in an optimal use of reactive power and a minimum amount of curtailed active power, while respecting network limitations. The optimization of these parameters is formulated as a convex optimization problem, which can be solved sufficiently fast. The performance of the control is evaluated on an existing three-phase four-wire distribution grid and is compared with different local control methods.

Performance of a reactive power-based adaptive estimation of inverse rotor time constant for vector controlled induction motor drives

A detail investigation on an adaptive estimation of rotor time constant is presented here. The adaptation mechanism forms a Model Reference Adaptive System (MRAS) for the online estimation of inverse rotor time constant for high performance Indirect Vector Controlled Induction Motor Drive. The instantaneous and steady state reactive powers are utilised in the proposed MRAS. A merit of the scheme is that the flux computation is not required in both the models (reference model and adjustable model) of MRAS. So, the low speed estimation problems like drift and saturation of integrator (related to flux estimation from voltage model) are overcome. The use of reactive power as a functional candidate of MRAS naturally makes the scheme independent of stator resistance. The workability of the proposed MRAS is verified through extensive simulation and experiment. The stability of the system is investigated and a study on the sensitivity to stator and rotor parameters is reported. The technique is simple and can be implemented in the existing indirect vector controlled system without any additional hardware.

03/01765 On the use of reactive power as an endogenous variable in short-term load forecasting: Santos, P. J. et al. International Journal of Energy Research, 2003, 27, (5), 513–529

03/01765 On the use of reactive power as an endogenous variable in short-term load forecasting: Santos, P. J. et al. International Journal of Energy Research, 2003, 27, (5), 513–529

On the use of reactive power as an endogenous variable in short-term load forecasting

In the last decades, short-term load forecasting(STLF) has been the object of particular attention in the power systems field. STLF has been applied almost exclusively to the generation sector, based on variables, which are transversal to most models. Among the most significant variables we can find load, expressed as active power (MW), as well as exogenous variables, such as weather and economy-related ones; although the latter are applied in larger forecasting horizons than STLF. In this paper, the application of STLF to the distribution sector is suggested including inductive reactive power as a forecasting endogenous variable. The inclusion of this additional variable is mainly due to the evidence that correlations between load and weather variables are tenuous, due to the mild climate of the actual case-study system and the consequent feeble penetration of electrical heating ventilation and air conditioning loads. Artificial neural networks (ANN) have been chosen as the forecasting methodology, with standard feed forward back propagation algorithm, because it is a largely used method with generally considered satisfactory results. Usually the input vector to ANN applied to load forecasting is defined in a discretionary way, mainly based on experience, on engineering judgement criteria and on concern about the ANN dimension, always taking into consideration the apparent (or actually evaluated) correlations within the available data. The approach referred in the paper includes pre-processing the data in order to influence the composition of the input vector in such a way as to reduce the margin of discretion in its definition. A relative entropy analysis has been performed to the time series of each variable. The paper also includes an illustrative case study. Copyright © 2003 John Wiley & Sons, Ltd.