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![Fig. 6: Standard IEEE 14 bus system [25]](profile/Sharmin-Rahman/publication/350421392/figure/fig3/AS:1021879288602629@1620646416909/Standard-IEEE-14-bus-system-25_Q320.jpg)
Grid integration of solar photovoltaic (PV) systems has been escalating in recent years, with two main motivations: reducing greenhouse gas emission and minimizing energy cost. However, the intermittent nature of solar PV generated power can significantly affect the grid voltage stability. Therefore, intermittent solar PV power generation and uncer...
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... general, a typical PV system comprises PV arrays, power electronic DC-AC inverter and associated controllers. Fig. 1 demonstrates a generic structure of a PV energy system. Large scale PV energy systems are usually connected to the grid through a step-up transformer. The associated control algorithms driving a PV system includes maximum power point tracking (MPPT) control and DC-AC inverter control. The MPPT control approach facilitates harvesting ...
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... method is implemented to determine expected values of total active power loss and reactive power loss of the modified system for different PV penetration levels at the weakest bus 14. Hourly expected total active power loss and total reactive power loss of the test system for different PV penetration levels (20%, 50% and 80%) are displayed in Fig. 10 and Fig. 11 respectively. These figures reflect that both of the losses decrease with increasing PV penetration, specially during the peak hours of solar irradiance (10 a.m.-3p.m.). with the integration of PVPP as opposed to the system with no PV at all. It is also observed that the reactive power reserve is improved by 0.8 MVAR for 80% PV ...
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... reflect that both of the losses decrease with increasing PV penetration, specially during the peak hours of solar irradiance (10 a.m.-3p.m.). with the integration of PVPP as opposed to the system with no PV at all. It is also observed that the reactive power reserve is improved by 0.8 MVAR for 80% PV penetration as compared to 20% penetration. Fig. 13 and Fig. 14 represent the probability distribution of reactive power margin and critical eigenvalue with different PV penetrations and no penetration at three different times (9 a.m., 12 p.m. and 6 p.m.) respectively. These distributions are obtained using approximating normal distribution of the data from Monte Carlo simulation. The ...
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... both of the losses decrease with increasing PV penetration, specially during the peak hours of solar irradiance (10 a.m.-3p.m.). with the integration of PVPP as opposed to the system with no PV at all. It is also observed that the reactive power reserve is improved by 0.8 MVAR for 80% PV penetration as compared to 20% penetration. Fig. 13 and Fig. 14 represent the probability distribution of reactive power margin and critical eigenvalue with different PV penetrations and no penetration at three different times (9 a.m., 12 p.m. and 6 p.m.) respectively. These distributions are obtained using approximating normal distribution of the data from Monte Carlo simulation. The distribution ...
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... distribution of reactive power margin and critical eigenvalue with different PV penetrations and no penetration at three different times (9 a.m., 12 p.m. and 6 p.m.) respectively. These distributions are obtained using approximating normal distribution of the data from Monte Carlo simulation. The distribution of reactive power margin in Fig. 13 reflects that the probabiliy of an increase in this margin is the highest with high PV penetration as compared to low PV penetration and no PV penetration. Fig. 14 implies that the probability of increased critical eigenvalue is improved with PV integration as compared to no PV ...
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... and 6 p.m.) respectively. These distributions are obtained using approximating normal distribution of the data from Monte Carlo simulation. The distribution of reactive power margin in Fig. 13 reflects that the probabiliy of an increase in this margin is the highest with high PV penetration as compared to low PV penetration and no PV penetration. Fig. 14 implies that the probability of increased critical eigenvalue is improved with PV integration as compared to no PV ...
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... methods' applicability in a large scale system. Since for this system, bus 30 is the weakest node, this node has been integrated with a PV system considering 20%, 50% and 80% PV penetration individually. After the rigourous analysis, the expected values of all the aforementioned indices have been found throughout the hours of solar irradiance. Fig. 15, 16, 17 and 18 represent expected critical eigenvalue, total real and reactive power loss and reactive power margin respectively for IEEE 30 bus system over the solar hours of a day. These results from IEEE 30 bus system comply with the findings on IEEE 14 bus system as presented in section V. For example, Fig. 15 shows that the placement of a ...
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... the hours of solar irradiance. Fig. 15, 16, 17 and 18 represent expected critical eigenvalue, total real and reactive power loss and reactive power margin respectively for IEEE 30 bus system over the solar hours of a day. These results from IEEE 30 bus system comply with the findings on IEEE 14 bus system as presented in section V. For example, Fig. 15 shows that the placement of a PV system at the weakest node 30 improves the critical eigenvalue more as compared to the PV placement at a strong node (here bus 20) and no PV placement. Expected values of total real power loss and total reactive power loss decrease and reactive power margin of the PV connected bus increases with ...
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... improves the critical eigenvalue more as compared to the PV placement at a strong node (here bus 20) and no PV placement. Expected values of total real power loss and total reactive power loss decrease and reactive power margin of the PV connected bus increases with increasing PV penetration during peak hours of solar irradiance as reflected by Fig. 16, 17 and 18. Overall, this analysis provides a clear understanding of expected profile of each voltage stability index at a certain hour with respect to a certain level of PV penetration. To understand how expected profiles of voltage stability indices get affected due to different locations of PV placement and different PV penetration levels ...
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... is usually quantified as the short circuit level (SCL) at that point, since low SCL increases the voltage sensitivity of the grid location under consideration to external disturbances [48]. In the following an analysis on the requirement of grid strength while integrating a PV farm in the grid. Let us considered a PV farm connected to a grid in Fig. 21, where the grid is modelled as a Thevenin equivalent circuit at the point of common connection (PCC). In the figure, S P V = P P V +jQ P V is the power supplied by the PV farm to the grid; V T and V g are the PCC and grid voltage respectively. From the figure, the PCC voltage can be written as ...
Citations
... Associated with that, stability of the grid operation is of concern. It is known that solar power generation highly depends on the weather conditions, challenging the grid's voltage and frequency stability [1,2]. ...
The fast growth of solar photovoltaic (PV) power generation raises the concern of grid stability due to intermittency. The traditional solution based on the broad installation of energy storage systems (ESS) is considered to be costly. Hence, the latest research focuses on the active power ramp rate control (PRRC) that decouples the heavy reliance on ESS. While power-forecasting-based PRRC can be a promising solution, the relevant research is still limited and does not cover the prediction error's negative effect on the power ramp rate control. With the above, this paper investigates the over-regulation issue that is induced by inaccurate prediction and can lead to power losses. More importantly, this paper proposes a novel PRRC scheme incorporating a Gaussian confidence estimator and best-performed deep neural networks (DNN) predictor to implement more accurate control actions while overcoming the over-regulation problem. The experimental tests show that the proposed scheme can simultaneously achieve a more promising PRRC performance and relatively higher energy harvest efficiency compared to the prior arts.
... A three stage voltage allocation and distribution model is presented in [9], to support electric two wheelers in charging station. A power grid voltage stability analysis framework is presented in [10], which analyze power generation and load demand with Monte Carlo simulation. The driving data of Toyota prius car has been demonstrated and analyzed in [11]. ...
The problem of drive span maximization in electric vehicle is well studied. There exist number of approaches around the problem which uses residual energy and sleep mode as key in maximizing the drive span. However, they suffer to achieve higher performance in drive span maximization. This article presents a novel Dual Model Photovoltaic Power System Based Drive Span Maximization Model (DPDSM). The model is focused on maximizing the storage of voltage in the PV cells and utilizing maximum battery supply. The model generates the voltage from the photovoltaic system and regulates the power to the electric vehicle. The model has been connected with number of photovoltaic cells, which has been connected in serial. Using them, the required voltage has been regulated to the electric motor. In another mode, the residual voltage of the vehicle battery has been changed to discharge mode which support the regulation of voltage for the vehicle. The dual mode photovoltaic power system regulates effective power for the electric vehicle continuously with less voltage loss.
... A three stage voltage allocation and distribution model is presented in [9] and the stability of power grids is analyzed with the framework in [10]. The driving data of Toyota prius car has been demonstrated and analyzed in [11]. ...
Towards effective voltage regulation and power stability, there exist number of approaches available in literature. The methods consider the residual voltage in various power grids in maximizing the power stability. However, the methods suffer to achieve higher performance in power stability and voltage regulation. To handle this issue, an efficient Electric Patter Based Voltage regulation model (EPVRM) is presented in this article. The method maintains the voltage trace belongs to various grids of the power system. Using the traces maintained, the method preprocesses the traces to remove the noisy records. The preprocessed trace has been used to generate the electrical pattern which contains residual voltage of various grid units. Using the electric pattern the method computes Electric Pattern Stability Support (EPSS) towards the required voltage. Based on the EPSS value, the method identifies the most efficient pattern to be scheduled for current cycle. The selected pattern has been scheduled to maintain the power stability. The proposed method improves the performance of voltage regulation and power stability.
... A power grid voltage stability analysis model is presented in [3], which consider the uncertainties of PV power generation and load demand. ...
The power stability in power distribution systems are well studied. There exist numbers of models towards maintaining the power stability which consider the residual energy of PV systems. However, there are not efficient in maintaining the power stability and suffer to achieve higher efficiency in potential maximization. Towards maintaining higher potential maximization, an efficient Optimized Solar Potential Maximization Model (OSPMM) is presented in this article. The model considers the factors like Mean Voltage Generation, Mean Voltage Supply and Residual Voltage as the key in the selection of PV system towards power stability. To perform this, the method monitors the incoming voltage produced by various PV systems and collects such factors mentioned above. According to the factors identified, the method estimates Potential Maximization Support (PMS) for various PV systems. Based on the value of PMS, the method selects the PV system towards maintaining power stability. The proposed approach improves the performance of solar potential maximization and power stability maximization.
... The number of Distributed Generators equipped with Battery Energy Storage Systems (DERs) connected to Active Distribution Networks (ADNs) by a Voltage Source Converter (VSC) is rapidly increasing to meet the carbon-free target [1]. However, the randomness of the primary source (wind and sun), the undesired interactions among the DERs and the unpredictability of the load demand make the voltage control imperative in the existing distribution networks to avoid larger voltage variations and voltage instability [2][3][4][5][6][7][8][9][10][11]. Failing to mitigate over-voltage can also result in VSC tripping, leading to the uncontrolled disconnection of the affected DER unit [12]. ...
Distributed Energies Resources (DERs) can be controlled for supporting the voltage regulation at nodes of an Active Distribution Network (ADN) where they are connected. However, since the ADN is a Multi-Input Multi-Output (MIMO) system with coupled dynamics, the controller of a DER mutually interacts with all other controllers through the distribution lines. These interactions lead to operating conflicts which may drive the ADN to work close to its voltage stability boundaries. To achieve a stable voltage regulation without new investment in the existing ADNs, the present paper proposes a straightforward decentralized design of the multi-loop controllers based on the property of integral controllability. The main feature of the method is that the design problem can be expressed by a single parameter designed both for reducing the effects of the undesired coupling and for increasing the degree of robust stability in the presence of parameter uncertainty in the matrix plant. Simulation studies are developed to illustrate the design result and the performance achieved under different operating conditions. The performance is also compared with the one obtained by another method in terms of the integral absolute error.
... The fundamental cell temperature and irradiance dependent equation are used to calculate the output power of a PV generator. SPV system's power output can be shown as follows [44]. To calculate the output power of a PV generator, we use the actual temperature and irradiance dependent equation. ...
The modern power systems incorporate high penetration of renewable is a large, composite, interconnected network with dynamic behavior. The small disturbances occurring in the system may induce low-frequency oscillations (LFOs) in the system. If the (LFOs) are not suppressed within a stipulated time, it may cause system islanding or even blackouts. Hence, it is essential to investigate the behavior of the system under various levels of disturbances and control action must be taken to damp these oscillations. The established approach to damping the LFOs is by installing power system stabilizers (PSS). PSS uses the local signals from generators to control the oscillations. The dominant source of inter-area oscillations in power systems is due to overloaded weak interconnected lines, converter-interfaced generation, and the action of the high gain exciter present in the system. Consequently, wide area control is needed to control the inter-area oscillations existent in the system. This paper developed a coordinated design of conventional PSS, static compensator, renewable converters, and wide area controller for damping the local and inter-area oscillations in renewable incorporated power systems. The performance of the developed controller is evaluated through the time domain analysis and eigenvalue analysis. A comparison of the introduced controller has been done with other standard conventional methods. The choice of input signals for the wide area controller from the wide-area measurement system is done based on the controllability index. Additionally, the location of the controller must be identified to dampen the inter-area oscillations in the system. In this paper, the controllability index is calculated to find out the highly affected wide area signals for considering it as the feedback signal to a developed controller. The location of the controller is recognized by computing the participation factor. The developed controller has experimented on renewable incorporated large study power systems when time delay and noise are present in wide area signals.
... People who become consumers of electricity at the same time can become electricity producers. With the development of Industry 4.0, development is needed in the generation sector from renewable energy that does not depend on central generators (Idoniboyeobu et al., 2020;Rahman et al., 2021). ...
The need for electricity in Indonesia is increasing along with the growth of world industry in Indonesia. The use of power plants with fossil energy sources is decreasing with the aim of improving the environmental system. Electricity needs can be fulfilled by Distributed Generation (DG), namely generation that is connected to a distribution network in order to fulfill power needs and improve electricity quality. In Bekasi City, the Directorate General of the Bantar Gebang Waste-to-Energy Plant (WtE) is being built with a drained power of around 786 kW. In this research, an analysis will be carried out on the Bantar Gebang WtE, which is connected to the Tambun area distribution network. The simulation results show that the voltage drop at the transformer load is 0.3% to 3% in general. With PVUR values on sample transformers of 0.171%, 0.578%, and 0.187% and real and reactive power losses on Underground Lines, Overhead Lines, and transformers of 144 kW and 173 kvar leading before interconnection. After interconnection, there was an increase in real power loss to 147 kW and an improvement in PVUR values to 0.156%, 0.563%, and 0.183%, and reactive power to 164 kvar. The use of power at the Tambun feeder Dodge Substation has also decreased due to the interconnection of the Bantar Gebang WtE, which can generate around 786 kW of power to supply power to the distribution network connected to the Bantar Gebang WtE DG.
... As the penetration rate of photovoltaic grid connection increases, the intermittent components in the power grid will also increase, which will significantly affect the stability of the overall power grid. Literature [1] analyzes the impact of solar photovoltaic power grid connection on voltage stability, and its stability is highly dependent on the location of distributed energy resources. ...
The degradation in power quality due to the high penetration of grid-connected photovoltaic (PV) systems is a critical issue that urgently needs to be addressed in the field of renewable energy generation. Solar PV systems typically lack mechanical inertia, which means that they are unable to provide additional mechanical inertia to maintain voltage and frequency stability when the power system is subjected to external disturbances. Therefore, to ensure stable operation of the power system, alternative measures need to be relied on to maintain voltage stability. This article first analyzes the mechanism of voltage fluctuations when photovoltaic power generation is connected to the grid. It then delves into the challenges of power quality brought about by the grid integration of renewable distributed generation systems, as well as the current research status of mainstream voltage improvement technologies, customized power devices, and energy storage systems. Finally, the paper presents recommendations for improving grid voltage quality, enhancing the stability and reliability of the power system, and promoting the widespread application of renewable energy in power systems.
... Research [21], proposes a methodology to analyze the voltage stability of the power grid that uses Monte Carlo simulation to account for uncertainty related to PV power output and load demand. A data-enhanced hierarchical control (DEHC) architecture's development process and evaluation findings are described in depth in [22]. ...
This paper proposed a method to investigate the effect of increasing PV penetration on the voltage stability of an IEEE 14-bus test system considering maximum PV penetration and system loadability limit. The critical bus of the test system has been decided based on nose curve analysis. The solar PV system is deployed with the most critical bus of the system. The effect of increasing PV penetration on the improvement in the loading capacity of various power system components like transmission lines, transmission line transformers, and generators is investigated over the adopted test system. Based on solar PV penetration up to 100 MW, the maximum loadability limit of the IEEE 14-bus test system increases, as shown by the results. Bus 14 is found to be the most severe bus of the test system using the continuation power flow (CPF) method. However, in some cases, overloading situations develop after a certain limit of PV penetration in the power system. In this condition, the overloading of the power system equipment is improved by the use of a Static Synchronous Compensator (STATCOM) at bus number 14, a double circuit line in the critical line (9–14), and Static Synchronous Series Compensator (SSSC) in the most severe line (9–14) in the system. The maximum loadability of the system gets maximum enhanced from 4.0349 p.u. to 4.5602 p.u. under simultaneous use of solar PV generation, SSSC, and STATCOM at the most critical bus and in most severe line of the system. As evidence, the enhancement in maximum loadability of the system found using the proposed method has been also compared with the existing research. The maximum system loadability has been also enhanced under normal and (N-1) contingency conditions by the use of PV penetration in the system. PSAT/MATLAB software is used for simulation and maximum loadability has been investigated by continuation power flow (CPF) method.
... In these studies, dynamic changes related to system stability are relatively small, and most dynamic voltage stability analyses still leverage the system's static operating parameters. The modal approach of voltage stability evaluation of large power systems is among the most effective ways of determining voltage collapse zones and the causal factors of the problem [12,13,14]. This technique is based on the eigen-analysis approach, where the notion of stability of modes is used to assess voltage stability. ...
The voltage stability of the Tunisian power system, which includes 1750 MW of renewable energy resources power plants, is evaluated and analyzed. The study is based on a developed stability analysis tool based on an eigen-analysis approach and employs the concept of mode stability. The system model is the Tunisian 225 kV system, which a 23-bus equivalent model represents. The base case and the case of increased renewable energy resource power penetration are presented, compared, and predicted using Recurrent Neural Networks (RNNs). The main focus here is on the unavoidable consequences of the latter case on overall voltage decrease or increase. Each case study presents the critical mode's characterizations, the power system element's participation in each mode, and the generator PV-PQ state transitions.
