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Samundra Gurung
Department of Electrical Engineering, Faculty of Engineering, King Mongkut’s University of Technology Thonburi (KMUTT), Bangkok 10 140, Thailand

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Journal article
Published: 26 April 2021 in Applied Sciences
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Recently due to air pollution concerns, a large number of electric vehicles have been integrated into the electric distribution system. However, the uncoordinated charging of this technology can cause different voltage issues. This paper proposes a two-stage optimization approach with active and reactive power control to coordinate electric vehicles with both grid-to-vehicle and vehicle-to-grid capabilities to satisfy both grid requirements and electric vehicle prosumer requirements. The system requirements considered are voltage deviation and unbalance and the electric vehicle prosumer requirements considered are minimization of charging and battery degradation costs. The coordination problem is formulated as an optimization problem, where the first stage objectives are: minimization of voltage unbalance, customer charging and battery degradation costs. The first stage optimization problem is solved using the meta-heuristic optimization algorithm known as particle swarm optimization to obtain an optimized real power schedule for the electric vehicles. The second stage is then solved of which the objective is to minimize the bus voltage deviation and provides the reactive power schedule for electric vehicles. All the analyses were carried out on the IEEE 34 bus distribution system and the study results show that the proposed method allows prosumers to charge at a minimum cost without any grid voltage unbalance factors and under/over voltage problems under different scenarios. Thus, this work can be beneficial for system operators or electric vehicle aggregators to create a day-ahead schedule.

ACS Style

Trinnapop Boonseng; Anawach Sangswang; Sumate Naetiladdanon; Samundra Gurung. A New Two-Stage Approach to Coordinate Electrical Vehicles for Satisfaction of Grid and Customer Requirements. Applied Sciences 2021, 11, 3904 .

AMA Style

Trinnapop Boonseng, Anawach Sangswang, Sumate Naetiladdanon, Samundra Gurung. A New Two-Stage Approach to Coordinate Electrical Vehicles for Satisfaction of Grid and Customer Requirements. Applied Sciences. 2021; 11 (9):3904.

Chicago/Turabian Style

Trinnapop Boonseng; Anawach Sangswang; Sumate Naetiladdanon; Samundra Gurung. 2021. "A New Two-Stage Approach to Coordinate Electrical Vehicles for Satisfaction of Grid and Customer Requirements." Applied Sciences 11, no. 9: 3904.

Journal article
Published: 19 February 2021 in IEEE Access
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This paper proposes a computationally efficient method based on deep neural network and a meta-heuristic optimization algorithm known as bat algorithm to coordinate power oscillation damping controllers incorporated in renewable energy stations to enhance system small signal stability considering uncertainties. The proposed method consists of three main stages: database generation, supervised learning, and optimization using the created model. A database is first created of Probabilistic small-signal stability margin calculated using the combined cumulant and Gram-Charlier expansion and the parameters of damping controllers, which is then given to different supervised machine learning algorithms such as linear regression, support vector machine, random forest, and chiefly deep neural network to create a surrogate model. The surrogate model provides an approximate relationship between the probabilistic small-signal instability margin and damping controller parameters. An optimization problem is then formulated to minimize the surrogate probabilistic instability margin with damping controller parameters acting as constraints. Finally, this optimization problem is solved using the bat algorithm to obtain the optimized parameters for power oscillation damping controllers. Our study results tested on a large IEEE 16 machines, 68 bus system show that the power oscillation damping controllers optimized using the proposed method can largely improve the system low frequency oscillatory stability margin in a very low computational time (around 19 times faster than the conventional method). This study can be used by the power system operators to tune the parameters of damping controller in a fast manner.

ACS Style

Samundra Gurung; Sumate Naetiladdanon; Anawach Sangswang. A Surrogate Based Computationally Efficient Method to Coordinate Damping Controllers for Enhancement of Probabilistic Small-Signal Stability. IEEE Access 2021, 9, 32882 -32896.

AMA Style

Samundra Gurung, Sumate Naetiladdanon, Anawach Sangswang. A Surrogate Based Computationally Efficient Method to Coordinate Damping Controllers for Enhancement of Probabilistic Small-Signal Stability. IEEE Access. 2021; 9 ():32882-32896.

Chicago/Turabian Style

Samundra Gurung; Sumate Naetiladdanon; Anawach Sangswang. 2021. "A Surrogate Based Computationally Efficient Method to Coordinate Damping Controllers for Enhancement of Probabilistic Small-Signal Stability." IEEE Access 9, no. : 32882-32896.

Journal article
Published: 20 January 2020 in Electric Power Systems Research
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The modern power system consists of a large mixture of renewable energy sources (RES), varying and flexible loads, and is also experiencing a situation where a significant number of conventional generators are being replaced by power electronics based sources. All of these factors may lead to a decrease in the small-signal stability (SSS) margin of the system which in turn can cause power system instability. Power system stabilizers (PSSs) are widely used to improve the low-frequency oscillatory stability of power systems. Currently, there are two popular methods to coordinate multiple PSSs to improve SSS: deterministic and probabilistic method. This paper first formulates the problem of coordinating multiple PSSs to improve SSS as a deterministic and a probabilistic optimization problem which is then solved using the new directional bat algorithm. A detailed comparison between the two design methods under different scenarios based on obtained results is carried out afterward. All of the analysis was carried out on a modified IEEE 68 bus system. The obtained results provide key insights as well as the advantages and limitations of the probabilistic and deterministic approach to optimize the PSS parameters.

ACS Style

Samundra Gurung; Francisco Jurado; Sumate Naetiladdanon; Anawach Sangswang. Comparative analysis of probabilistic and deterministic approach to tune the power system stabilizers using the directional bat algorithm to improve system small-signal stability. Electric Power Systems Research 2020, 181, 106176 .

AMA Style

Samundra Gurung, Francisco Jurado, Sumate Naetiladdanon, Anawach Sangswang. Comparative analysis of probabilistic and deterministic approach to tune the power system stabilizers using the directional bat algorithm to improve system small-signal stability. Electric Power Systems Research. 2020; 181 ():106176.

Chicago/Turabian Style

Samundra Gurung; Francisco Jurado; Sumate Naetiladdanon; Anawach Sangswang. 2020. "Comparative analysis of probabilistic and deterministic approach to tune the power system stabilizers using the directional bat algorithm to improve system small-signal stability." Electric Power Systems Research 181, no. : 106176.

Original paper
Published: 23 September 2019 in Electrical Engineering
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Communication latency which inherently occurs in wide area measurement system greatly degrades small-signal stability (SSS) and is stochastic in nature, and thus, the current power oscillation damping controllers (PODCs) designed to improve SSS must consider this crucial factor. This paper proposes a probabilistic method to tune the parameters of PODCs incorporated in renewable farms to improve SSS under stochastic time delay and under other power system uncertainties arising due to renewable energy resources and loads. The proposed method is composed of two stages: The first stage quantifies the effect of time delay and other power system uncertainties on SSS, and the second stage uses this information to formulate an optimization problem. This optimization problem is solved with the help of four swarm intelligence-based optimization algorithms which are: bat algorithm, cuckoo search algorithm, firefly algorithm, and particle swarm optimization algorithm. The solutions from all these four optimization algorithms are compared, and the best result is used to optimize the parameters of the PODCs. All the analyses were conducted on a modified IEEE 68 bus system. The results show that the PODCs tuned using the proposed method greatly enhances the SSS margin under different scenarios and are probabilistically robust to the varying time delay and other power system uncertainties.

ACS Style

Samundra Gurung; Francisco Jurado; Sumate Naetiladdanon; Anawach Sangswang. Optimized tuning of power oscillation damping controllers using probabilistic approach to enhance small-signal stability considering stochastic time delay. Electrical Engineering 2019, 101, 969 -982.

AMA Style

Samundra Gurung, Francisco Jurado, Sumate Naetiladdanon, Anawach Sangswang. Optimized tuning of power oscillation damping controllers using probabilistic approach to enhance small-signal stability considering stochastic time delay. Electrical Engineering. 2019; 101 (3):969-982.

Chicago/Turabian Style

Samundra Gurung; Francisco Jurado; Sumate Naetiladdanon; Anawach Sangswang. 2019. "Optimized tuning of power oscillation damping controllers using probabilistic approach to enhance small-signal stability considering stochastic time delay." Electrical Engineering 101, no. 3: 969-982.

Journal article
Published: 22 March 2019 in TURKISH JOURNAL OF ELECTRICAL ENGINEERING & COMPUTER SCIENCES
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Currently, large-scale solar farms are being rapidly integrated in electrical grids all over the world. However, the photovoltaic (PV) output power is highly intermittent in nature and can also be correlated with other solar farms located at different places. Moreover, the increasing PV penetration also results in large solar forecast error and its impact on power system stability should be estimated. The effects of these quantities on small-signal stability are difficult to quantify using deterministic techniques but can be conveniently estimated using probabilistic methods. For this purpose, the authors have developed a method of probabilistic analysis based on combined cumulant and Gram– Charlier expansion technique. The output from the proposed method provides the probability density function and cumulative density function of the real part of the critical eigenvalue, from which information concerning the stability of low-frequency oscillatory dynamics can be inferred. The proposed method gives accurate results in less computation time compared to conventional techniques. The test system is a large modified IEEE 16-machine, 68-bus system, which is a benchmark system to study low-frequency oscillatory dynamics in power systems. The results show that the PV power fluctuation has the potential to cause oscillatory instability. Furthermore, the system is more prone to small-signal instability when the PV farms are correlated as well as when large PV forecast error exists.

ACS Style

Samundra Gurung; Sumate Naetiladdanon; Anawach Sangswang. Probabilistic small-signal stability analysis of power system with solar farm integration. TURKISH JOURNAL OF ELECTRICAL ENGINEERING & COMPUTER SCIENCES 2019, 1276 -1289.

AMA Style

Samundra Gurung, Sumate Naetiladdanon, Anawach Sangswang. Probabilistic small-signal stability analysis of power system with solar farm integration. TURKISH JOURNAL OF ELECTRICAL ENGINEERING & COMPUTER SCIENCES. 2019; ():1276-1289.

Chicago/Turabian Style

Samundra Gurung; Sumate Naetiladdanon; Anawach Sangswang. 2019. "Probabilistic small-signal stability analysis of power system with solar farm integration." TURKISH JOURNAL OF ELECTRICAL ENGINEERING & COMPUTER SCIENCES , no. : 1276-1289.

Journal article
Published: 15 March 2019 in Applied Sciences
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This paper proposes a probabilistic method to obtain optimized parameter values for different power-system controllers, such as power-system stabilizers (PSSs) and battery energy-storage systems (BESSs) to improve probabilistic small-signal stability (PSSS) considering stochastic output power due to wind- and solar-power integration. The proposed tuning method is based on a combination of an analytical method that assesses the small-signal-stability margin, and an optimization technique that utilizes this statistical information to optimally tune power-system controllers. The optimization problem is solved using a metaheuristic technique known as the firefly algorithm. Power-system stabilizers, as well as sodium–sulfur (NaS)-based BESS controllers with power-oscillation dampers (termed as BESS controllers) are modeled in detail for this purpose in DIGSILENT. The results show that the sole use of PSSs and BESS controllers is insufficient to improve dynamic stability under fluctuating input power due to the integration of renewable-energy resources. However, the proposed strategy of using BESS and PSS controllers in a coordinated manner is highly successful in enhancing PSSS under renewable-energy-resource integration and under different critical conditions.

ACS Style

Samundra Gurung; Sumate Naetiladdanon; Anawach Sangswang. Coordination of Power-System Stabilizers and Battery Energy-Storage System Controllers to Improve Probabilistic Small-Signal Stability Considering Integration of Renewable-Energy Resources. Applied Sciences 2019, 9, 1109 .

AMA Style

Samundra Gurung, Sumate Naetiladdanon, Anawach Sangswang. Coordination of Power-System Stabilizers and Battery Energy-Storage System Controllers to Improve Probabilistic Small-Signal Stability Considering Integration of Renewable-Energy Resources. Applied Sciences. 2019; 9 (6):1109.

Chicago/Turabian Style

Samundra Gurung; Sumate Naetiladdanon; Anawach Sangswang. 2019. "Coordination of Power-System Stabilizers and Battery Energy-Storage System Controllers to Improve Probabilistic Small-Signal Stability Considering Integration of Renewable-Energy Resources." Applied Sciences 9, no. 6: 1109.

Conference paper
Published: 01 December 2017 in 2017 IEEE Innovative Smart Grid Technologies - Asia (ISGT-Asia)
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This paper applies cumulant method to analyze the influence of Photovoltaic Penetration (PV) considering fluctuations in small signal stability The cumulant method for small signal stability is mainly based on sensitivity analysis which is then used with Gram-Charlier expansion to obtain the valuable information of probability density function (PDF) and Cumulative Density Function (CDF) of the real part of the critical eigen value and damping factor. A supplementary controller to enhance small signal stability is also presented and its performance is also analyzed. The test system is a modified IEEE 16 machine, 68 bus system which is benchmarked to study small signal oscillatory dynamics in power systems. The results show that the PV fluctuations have potential to cause oscillatory instability and the future large PV farms should also contain Power Oscillation Damper (POD) to damp these oscillations.

ACS Style

Samundra Gurung; Sumate Naetiladdanon; Anawach Sangswang. Impact of photovoltaic penetration on small signal stability considering uncertainties. 2017 IEEE Innovative Smart Grid Technologies - Asia (ISGT-Asia) 2017, 1 -6.

AMA Style

Samundra Gurung, Sumate Naetiladdanon, Anawach Sangswang. Impact of photovoltaic penetration on small signal stability considering uncertainties. 2017 IEEE Innovative Smart Grid Technologies - Asia (ISGT-Asia). 2017; ():1-6.

Chicago/Turabian Style

Samundra Gurung; Sumate Naetiladdanon; Anawach Sangswang. 2017. "Impact of photovoltaic penetration on small signal stability considering uncertainties." 2017 IEEE Innovative Smart Grid Technologies - Asia (ISGT-Asia) , no. : 1-6.

Conference paper
Published: 01 November 2016 in 2016 IEEE Region 10 Conference (TENCON)
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This paper investigates the impact of solar photovoltaic generation in small signal stability in a two area system at different penetration levels. The tested system also consists of the Flexible AC Transmission system (FACTS) device. This paper uses the Static Var Compensator (SVC) and Thyristor Controlled Series Capacitor (TCSC). The analysis can be categorized into three cases. The first case is performed without incorporating any FACTS device. The second case corresponds to the investigation with SVC and the third with TCSC. The study uses the linearized eigen value analysis to obtain the crucial information about the critical modes, oscillation frequency and system damping. The analysis is further enhanced through the time domain simulation results. The study has shown that the integration of PV has mostly the beneficial impact on small signal stability. Moreover, this analysis has also shown that at very high PV penetration which causes the displacement of a large synchronous generator, the combined use of PV and TCSC can overcome this problem of loss of damping and still enhance the small signal stability.

ACS Style

Samundra Gurung; Sumate Naetiladdanon; Anawach Sangswang. Impact of large photovoltaic penetration on small signal stability. 2016 IEEE Region 10 Conference (TENCON) 2016, 646 -650.

AMA Style

Samundra Gurung, Sumate Naetiladdanon, Anawach Sangswang. Impact of large photovoltaic penetration on small signal stability. 2016 IEEE Region 10 Conference (TENCON). 2016; ():646-650.

Chicago/Turabian Style

Samundra Gurung; Sumate Naetiladdanon; Anawach Sangswang. 2016. "Impact of large photovoltaic penetration on small signal stability." 2016 IEEE Region 10 Conference (TENCON) , no. : 646-650.