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Marko Jereminov

Publications and source records attributed to Marko Jereminov.

At least 19 recordsLinked to original sources

Equivalent Circuit Programming for Power Flow Analysis and Optimization

The utility of domain-specific knowledge for modeling, simulation, and optimization has been demonstrated for various research problem domains, including power systems. The concept of Equivalent Circuit Programming was previously developed and facilitated for robust, efficient, and scalable solution of network simulation and optimization problems. This paper extends the theoretical foundation of Equivalent Circuit Programming to enable the fusion of optimization theory and algorithms with the numerical methods that utilize the domain-specific knowledge of power flow models. The generality, scalability, and numerical robustness of the resulting framework are demonstrated on realistic AC power flow (ACPF) models of up to 70k buses with proper enforcement of industry-required operational and security constraints.

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SUGAR-R: Robust Online Restoration Platform for SCADA-Absent Grid

Secure and fast grid restoration from a collapsed state is increasingly critical as blackouts are becoming more prevalent around the globe. Generally, the restoration of grid during a blackout is achieved with the help of Supervisory Control and Data Acquisition System (SCADA) based central control; however, with the threat of cyber-blackouts, this presumption of an available and secure SCADA system is not valid. This is also true for grids in developing countries as well as for many distribution and micro grids that lack SCADA. In this paper, we introduce an online framework for localized grid restoration that validates and updates a pre-defined crank path in real-time based on the vital grid states of voltages, currents and frequency. The proposed framework maintains an online network topology of the localized grid that can continuously sample local measurements and update the grid model, thereby circumventing SCADA based central control. In the results section we demonstrate the efficacy of this framework for blackstart by ensuring a feasible crank path with voltage and frequency states within bounds, while further assisting in synchronization of two disconnected sub-grids during the re-energization process using a distributed framework.

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Evaluating Feasibility within Power Flow

Recent development of techniques that improve the convergence properties of power flow simulation have been demonstrated to facilitate scaling to large system sizes (80k+ buses). However, the problem remains to reliably identify cases that are infeasible, system configurations that have no solution. In this paper, we use the circuit theoretic approach based on adjoint networks to evaluate the feasibility of a power flow test case and further locate and quantify the source of infeasibility in the cases operating beyond the tip of the nose curve. By creating infeasibility current source models that are added to each node of the system model and further coupling each source to its corresponding node of the adjoint network, any locations of insufficient real or reactive power are captured by a non-zero response of the adjoint network. Furthermore, it is shown that the proposed joint simulation of power flow and its adjoint network models provide the optimally minimized currents that can be later utilized to inform corrective actions to restore the feasibility of power flow problems.

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Robust Sequential Steady-State Analysis of Cascading Outages

Simulating potential cascading failures can be useful for avoiding or mitigating such events. Currently, existing steady-state analysis tools are ill-suited for simulating cascading outages as they do not model frequency dependencies, they require good initial conditions to converge, and they are unable to distinguish between a collapsed grid state from a hard-to-solve test case. In this paper, we extend a circuit-theoretic approach for simulating the steady-state of a power grid to incorporate frequency deviations and implicit models for underfrequency and undervoltage load shedding. Using these models, we introduce a framework capable of robustly solving cascading outages of large-scale systems that can also locate infeasible regions. We demonstrate the efficacy of our approach by simulating entire cascading outages on more than 8000 nodes sample testcase.

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A LASSO-Inspired Approach for Localizing Power System Infeasibility

A method is proposed to identify and localize the cause of network collapse with augmented power flow analysis for a grid model with insufficient resources. Owing to heavy network loading, insufficient generation, component failures and unavoidable disturbances, power grid models can sometimes fail to converge to a feasible solution for a steady-state power flow study. For applications such as system expansion planning, it is desirable to locate the system buses that are contributing to network infeasibilities to facilitate corrective actions. This paper proposes a novel LASSO-inspired regularization of the power flow matrix that enforces sparsity to localize and quantify infeasibilities in the network. One of the examples demonstrates how the proposed method is capable of localizing a source of blackout to a single dominant bus on an 80k+ bus eastern interconnection model.

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Implicitly Modeling Frequency Control within Power Flow

In this paper, we extend a circuit-based, current-voltage power flow formulation to include frequency deviations and implicitly model generator primary and secondary control actions as a function of their temporal dependence. This includes extending the slack bus generator model(s) to better represents its true behavior with frequency controls. These implicit models obviate the need for outer iteration loops and improve the robustness of the simulation convergence when frequency deviations are considered. The simulation framework is highly scalable and is demonstrated on 85k+ bus systems.

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Enhanced Modelling Framework for Equivalent Circuit-Based Power System State Estimation

The equivalent split-circuit formulation is a novel approach that has recently been applied to a range of power system related problems. As a result, a linear and a nonlinear method for power system state estimation with simultaneous treatment of the conventional and synchrophasor measurements have been proposed. In this paper, new circuit models are introduced for different combinations of conventional measurements, thus providing a complete modelling framework for these methods. Additionally, handling cases of null injections and buses with no measurements are included. Simulations are performed on several test systems in order to evaluate the performance of both methods with the enhanced modelling framework and to compare them to a hybrid constrained estimator based on the conventional WLS approach.

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Improving Voltage Profile of the Nigerian Power Grid

Extreme voltages at the system nodes are one of the primary causes for total and partial collapse of the Nigerian grid. In this paper, we develop a framework to re-dispatch the voltage set-points of committed generators in the grid to improve the voltage profile of the system nodes thus lowering the likelihood of a grid collapse. This framework is an extension of circuit-theoretic formulation that can robustly solve general-purpose grid optimization problems. In the results section, we re-dispatch the voltage setpoints for committed generators in real-life Nigerian grid operation and planning test cases to improve the overall voltage profile of the grid. We further demonstrate that the re-dispatched grid is more resilient and secure than the base case through running contingency analyses.

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A Probabilistic Approach to Power System State Estimation using a Linear Algorithm

An equivalent circuit formulation for power system analysis was demonstrated to improve robustness of Power Flow and enable more generalized modeling, including that for RTUs (Remote Terminal Units) and PMUs (Phasor Measurement Units). These measurement device models, together with an adjoint circuit based optimization framework, enable an alternative formulation to Power System State Estimation (SE) that can be solved within the equivalent circuit formulation. In this paper, we utilize a linear RTU model to create a fully linear SE algorithm that includes PMU and RTU measurements to enable a probabilistic approach to SE. Results demonstrate that this is a practical approach that is well suited for real-world applications.

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Equivalent Circuit Programming for Estimating the State of a Power System

An Equivalent Circuit Programming (ECP) approach that expresses the optimality conditions of an optimization problem in terms of an equivalent circuit model and uses circuit simulation techniques to solve for an optimal solution, is applied to the state estimation problem for power systems. The benefits of using an equivalent circuit formulation for incorporating both Phasor Measurement Units (PMU) and Remote Terminal Units (RTU), as well as for reducing the nonlinearities of the state estimation problem was previously demonstrated. In this paper we further exploit the circuit nature of the state estimation problem to formulate not only the model but also the optimality conditions as an ECP problem. The efficiency and accuracy of our approach are demonstrated by estimating the states of large-scale power grids (80k+ buses).

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Robust and Efficient Power Flow Convergence with G-min Stepping Homotopy Method

Recent advances have shown that the circuit simulation algorithms that allow for solving highly nonlinear circuits of over one billion variables can be applicable to power system simulation and optimization problems through the use of an equivalent circuit formulation. It was demonstrated that large-scale (80k+ buses) power flow simulations can be robustly solved, independent of the initial starting point. In this paper, we extend the electronic circuit-based G-min stepping homotopy method to power flow simulations. Preliminary results indicate that the proposed algorithm results in significantly better simulation runtime performance when compared to existing homotopy methods.

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Impact of Load Models on Power Flow Optimization

Aggregated load models, such as PQ and ZIP, are used to represent the approximated load demand at specific buses in grid simulation and optimization problems. In this paper we examine the impact of model choice on the optimal power flow solution and demonstrate that it is possible for different load models to represent the same amount of real and reactive power at the optimal solution yet correspond to completely different grid operating points. We introduce the metric derived from the maximum power transfer theorem to identify the behavior of an aggregated model in the OPF formulation to indicate its possible limitations. A dataset from the Carnegie Mellon campus is used to characterize three types of load models using a time-series machine learning algorithm, from which the optimal power flow results demonstrate that the choice of load model type has a significant impact on the solution set points. For example, our results show that the PQ load accurately characterizes the CMU data behavior correctly for only 16.7% of the cases.

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An Equivalent Circuit Formulation for Power System State Estimation including PMUs

In this paper, a novel formulation for the power system state estimation is proposed, based on the recently introduced equivalent split-circuit formulation of the power flow problem. The formulation models the conventional and time synchronized measurements simultaneously and contains a significantly lower level of nonlinearity compared to the available hybrid state estimators. The appropriate circuit models are derived for different types of measurements and integrated into the existing circuit framework for the power flow problem. A constrained optimization problem is then formulated to estimate the states of the system in rectangular coordinates, while satisfying the circuit equations and bounds on the measurement data. To further prove the concept and validate the accuracy of the proposed formulation, several test cases are solved and the results are presented and discussed.

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Linear Power Grid State Estimation with Modeling Uncertainties

Recent advances in power system State Estimation (SE) have included equivalent circuit models for representing measurement data that allows incorporation of both PMU and RTU measurements within the state estimator. In this paper, we introduce a probabilistic framework with a new RTU model that renders the complete SE problem linear while not affecting its accuracy. It is demonstrated that the probabilistic state of a system can be efficiently and accurately estimated not only with the uncertainties from the measurement data, but also while including variations from transmission network models. To demonstrate accuracy and scalability we present probabilistic state estimation results for the 82k test case that represents the transmission level grid of the entire USA. It is shown that the estimated state distributions include the true grid state, while their mean exactly corresponds to the estimated deterministic state obtained from the nonlinear state estimator.

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A Linear Formulation for Power System State Estimation including RTU and PMU Measurements

In this paper, a novel linear formulation for power system state estimation that simultaneously treats conventional and synchrophasor measurements is proposed. A linear circuit model for conventional measurements is introduced to enable a fully linear equivalent circuit representation of the power system. The estimated system state is then obtained by formulating the optimization problem to minimize the measurement errors and solving the resulting linear set of optimality conditions. To evaluate the accuracy of the proposed method, simulations are performed on several test cases of various sizes and the results are presented and discussed.

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Continuously Differentiable Analytical Models for Implicit Control within Power Flow

Achieving robust and scalable convergence for simulation of realistic power flow cases can be challenging. One specific issue relates to the disconnected solution space that is created by the use of piecewise-discontinuous models of power grid devices that perform control mechanisms. These models are generally resolved by outer iteration loops around power flow, which can result in solution oscillations, increased iteration count, divergence or even convergence to a solution in an unstable operational region. This paper introduces a continuously differentiable model for device control mechanisms that is incorporated within the power flow formulation. To ensure robust power flow convergence properties, recently introduced homotopy methods are extended to include these continuous models. The scalability and efficacy of the proposed formulation is demonstrated on several large-scale test cases that represent the US Eastern Interconnect network, the Synthetic USA, and the Nigerian grid.

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Unified power system analyses and models using equivalent circuit formulation

In this paper we propose and demonstrate the potential for unifying models and algorithms for the steady state and transient simulation of single-phase and three-phase power systems. At present, disparate algorithms and models are used for the different analyses, which can lead to inconsistencies such as the transient analysis as time approaches infinity not matching the steady state analysis of the same conditions. Using our equivalent circuit formulation of the power system, we propose a methodology for forming physics-based models that can facilitate transient, balanced power flow, and three-phase power flow in one simulation environment. The approach is demonstrated on a three-phase induction motor. Existing industry tools are used to validate the model and simulation results for the different analyses.

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Robust Power Flow and Three-Phase Power Flow Analyses

Robust simulation is essential for reliable operation and planning of transmission and distribution power grids. At present, disparate methods exist for steady-state analysis of the transmission (power flow) and distribution power grid (three-phase power flow). Due to the non-linear nature of the problem, it is difficult for alternating current (AC) power flow and three-phase power flow analyses to ensure convergence to the correct physical solution, particularly from arbitrary initial conditions, or when evaluating a change (e.g. contingency) in the grid. In this paper, we describe our equivalent circuit formulation approach with current and voltage variables that models both the positive sequence network of the transmission grid and three-phase network of the distribution grid without loss of generality. The proposed circuit models and formalism enable the extension and application of circuit simulation techniques to solve for the steady-state solution with excellent robustness of convergence. Examples for positive sequence transmission and three-phase distribution systems, including actual 75k+ nodes Eastern Interconnection transmission test cases and 8k+ nodes taxonomy distribution test cases, are solved from arbitrary initial guesses to demonstrate the efficacy of our approach.

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