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Dr. HyungSeon Oh
Electrical and Computer Engineering Department, United States Naval Academy, Annapolis, MD 21402, USA

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Research Keywords & Expertise

0 State Estimation
0 power system dynamics
0 energy system optimization
0 Nonlinear nonconvex optimization
0 Tensor computation

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Physical sciences
Published: 18 June 2021 in PLOS ONE
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Objective The objectives of this paper are to 1) construct a new network model compatible with distributed computation, 2) construct the full optimal power flow (OPF) in a distributed fashion so that an effective, non-inferior solution can be found, and 3) develop a scalable algorithm that guarantees the convergence to a local minimum. Existing challenges Due to the nonconvexity of the problem, the search for a solution to OPF problems is not scalable, which makes the OPF highly limited for the system operation of large-scale real-world power grids—“the curse of dimensionality”. The recent attempts at distributed computation aim for a scalable and efficient algorithm by reducing the computational cost per iteration in exchange of increased communication costs. Motivation A new network model allows for efficient computation without increasing communication costs. With the network model, recent advancements in distributed computation make it possible to develop an efficient and scalable algorithm suitable for large-scale OPF optimizations. Methods We propose a new network model in which all nodes are directly connected to the center node to keep the communication costs manageable. Based on the network model, we suggest a nodal distributed algorithm and direct communication to all nodes through the center node. We demonstrate that the suggested algorithm converges to a local minimum rather than a point, satisfying the first optimality condition. Results The proposed algorithm identifies solutions to OPF problems in various IEEE model systems. The solutions are identical to those using a centrally optimized and heuristic approach. The computation time at each node does not depend on the system size, and N iter does not increase significantly with the system size. Conclusion Our proposed network model is a star network for maintaining the shortest node-to-node distances to allow a linear information exchange. The proposed algorithm guarantees the convergence to a local minimum rather than a maximum or a saddle point, and it maintains computational efficiency for a large-scale OPF, scalable algorithm.

ACS Style

HyungSeon Oh. Distributed optimal power flow. PLOS ONE 2021, 16, e0251948 .

AMA Style

HyungSeon Oh. Distributed optimal power flow. PLOS ONE. 2021; 16 (6):e0251948.

Chicago/Turabian Style

HyungSeon Oh. 2021. "Distributed optimal power flow." PLOS ONE 16, no. 6: e0251948.

Journal article
Published: 06 June 2020 in Sustainable Futures
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Wind energy has been integrated into power systems with the hope that it can improve energy efficiency and decrease greenhouse gas emissions. However, several studies from around the world have implied that this integration has had an opposite effect, mainly because of the negative correlation between wind availability and load. Under this dynamic situation, coal power plants are forced to cycle, which is not within their designed mode of operation. To prevent this unwanted result, a unit commitment decision should include the fuel usage and emission rates during the ramp up/down process. This paper proposes a new unit commitment decision process to accommodate the economic and environmental costs associated with the ramping process. These costs are generally not convex, because there is a positive cost if a generator output changes significantly (regardless of direction). As a result, the problem might be nonconvex. A piece-wise linear cost curve is introduced to model the impact of ramping processes. With this curve, convex linear programming is formulated and the impact of governmental policy is discussed.

ACS Style

HyungSeon Oh. Unit commitment considering the impact of deep cycling. Sustainable Futures 2020, 2, 100031 .

AMA Style

HyungSeon Oh. Unit commitment considering the impact of deep cycling. Sustainable Futures. 2020; 2 ():100031.

Chicago/Turabian Style

HyungSeon Oh. 2020. "Unit commitment considering the impact of deep cycling." Sustainable Futures 2, no. : 100031.

Preprint
Published: 25 November 2019
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Objective: To derive a closed-form analytical solution to the swing equation describing the power system dynamics, which is a nonlinear second order differential equation. Existing challenges: No analytical solution to the swing equation has been identified, due to the complex nature of power systems. Two major approaches are pursued for stability assessments on systems: (1) computationally simple models based on physically unacceptable assumptions, and (2) digital simulations with high computational costs. Motivation: The motion of the rotor angle that the swing equation describes is a vector function. Often, a simple form of the physical laws is revealed by coordinate transformation. Methods: The study included the formulation of the swing equation in the Cartesian coordinate system, which is different from conventional approaches that describe the equation in the polar coordinate system. Based on the properties and operational conditions of electric power grids referred to in the literature, we identified the swing equation in the Cartesian coordinate system and derived an analytical solution within a validity region. Results: The estimated results from the analytical solution derived in this study agree with the results using conventional methods, which indicates the derived analytical solution is correct. Conclusion: An analytical solution to the swing equation is derived without unphysical assumptions, and the closed-form solution correctly estimates the dynamics after a fault occurs.

ACS Style

HyungSeon Oh. Analytical solution to swing equations in power grids. 2019, 1 .

AMA Style

HyungSeon Oh. Analytical solution to swing equations in power grids. . 2019; ():1.

Chicago/Turabian Style

HyungSeon Oh. 2019. "Analytical solution to swing equations in power grids." , no. : 1.

Research article
Published: 19 November 2019 in PLOS ONE
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To derive a closed-form analytical solution to the swing equation describing the power system dynamics, which is a nonlinear second order differential equation. No analytical solution to the swing equation has been identified, due to the complex nature of power systems. Two major approaches are pursued for stability assessments on systems: (1) computationally simple models based on physically unacceptable assumptions, and (2) digital simulations with high computational costs. The motion of the rotor angle that the swing equation describes is a vector function. Often, a simple form of the physical laws is revealed by coordinate transformation. The study included the formulation of the swing equation in the Cartesian coordinate system, which is different from conventional approaches that describe the equation in the polar coordinate system. Based on the properties and operational conditions of electric power grids referred to in the literature, we identified the swing equation in the Cartesian coordinate system and derived an analytical solution within a validity region. The estimated results from the analytical solution derived in this study agree with the results using conventional methods, which indicates the derived analytical solution is correct. An analytical solution to the swing equation is derived without unphysical assumptions, and the closed-form solution correctly estimates the dynamics after a fault occurs.

ACS Style

HyungSeon Oh. Analytical solution to swing equations in power grids. PLOS ONE 2019, 14, e0225097 .

AMA Style

HyungSeon Oh. Analytical solution to swing equations in power grids. PLOS ONE. 2019; 14 (11):e0225097.

Chicago/Turabian Style

HyungSeon Oh. 2019. "Analytical solution to swing equations in power grids." PLOS ONE 14, no. 11: e0225097.

Journal article
Published: 30 July 2019 in Energies
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Regular transmission maintenance is important to keep the infrastructure resilient and reliable. Delays providing on-time maintenance increase the forced outage rate of those assets, causing unexpected changes in the operating conditions and even catastrophic consequences, such as local blackouts. The current process of maintenance schedule is based on the transmission owners’ choice, with the final decision of system operator about the reliability. The requests are examined on a first-come, first-served basis, which means a regular maintenance request may be rejected, delaying the tasks that should be performed. To incorporate optimization knowledge into the transmission maintenance schedule, this study focuses on the co-optimization of maintenance scheduling and the production cost minimization. The mathematical model co-optimizes generation unit commitment and line maintenance scheduling while maintaining N-1 reliability criterion. Three case studies focusing on reliability, renewable energy delivery, and service efficiency are conducted leading up to 4% production cost savings as compared to the business-as-usual approach.

ACS Style

Gokturk Poyrazoglu; HyungSeon Oh; Oh. Co-Optimization of Transmission Maintenance Scheduling and Production Cost Minimization. Energies 2019, 12, 2931 .

AMA Style

Gokturk Poyrazoglu, HyungSeon Oh, Oh. Co-Optimization of Transmission Maintenance Scheduling and Production Cost Minimization. Energies. 2019; 12 (15):2931.

Chicago/Turabian Style

Gokturk Poyrazoglu; HyungSeon Oh; Oh. 2019. "Co-Optimization of Transmission Maintenance Scheduling and Production Cost Minimization." Energies 12, no. 15: 2931.

Journal article
Published: 24 June 2019 in Energies
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Highly nonlinear and nonconvex power flow analysis plays a key role in the monitoring, control, and operation of power systems. There is no analytic solution to power flow problems, and therefore, finding a numerical solution is oftentimes an aim of modern computation in power system analysis. An iterative Newton-Raphson method is widely in use. While most times this method finds a solution in a reasonable time, it often involves numerical robustness issues, such as a limited convergence region and an ill-conditioned system. Sometimes, the truncation error may not be small enough to ignore, which can make the iterative process significantly expansive. We propose a new unified framework, based on the Kronecker product, that does not involve any truncation, and which is bilinear to make it possible to incorporate statistical analysis. The proposed method is tested for power flow, state estimation, probabilistic power flow, and optimal power flow studies on various IEEE model systems.

ACS Style

HyungSeon Oh. A Unified and Efficient Approach to Power Flow Analysis. Energies 2019, 12, 2425 .

AMA Style

HyungSeon Oh. A Unified and Efficient Approach to Power Flow Analysis. Energies. 2019; 12 (12):2425.

Chicago/Turabian Style

HyungSeon Oh. 2019. "A Unified and Efficient Approach to Power Flow Analysis." Energies 12, no. 12: 2425.

Journal article
Published: 14 September 2018 in Energies
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Power networks are gateways to transfer power from generators to end-users. Often, it is assumed that the transfer occurs freely without any limiting factors. However, power flows over a network can be limited by predetermined limits that may come from physical reasons, such as line capacity or Kirchhoff’s laws. When flow is constrained by these limits, this is called congestion, which reduces the energy efficiency and splits the price for electricity across the congested lines. One promising, cost-effective way to relieve the impact of the congestion is demand-side management (DSM). However, it is unclear how much DSM can impact congestion and where it can control the demand. This paper proposes a new DSM mechanism based on locational willingness-to-pay (WTP) centered around income statistics; utilizes a state-space tool to determine the possibility to alter prices by DSM; and formulates a convex optimization problem to decide the DSM. The proposed methodology is tested on IEEE (Institute of Electrical and Electronics Engineers) systems with two commonly used objectives: cost minimization and social welfare maximization.

ACS Style

HyungSeon Oh. Demand-Side Management with a State Space Consideration. Energies 2018, 11, 2444 .

AMA Style

HyungSeon Oh. Demand-Side Management with a State Space Consideration. Energies. 2018; 11 (9):2444.

Chicago/Turabian Style

HyungSeon Oh. 2018. "Demand-Side Management with a State Space Consideration." Energies 11, no. 9: 2444.