MATPOWER: Steady-State Operations, Planning, and Analysis Tools for Power Systems Research and Education
TL;DR: The details of the network modeling and problem formulations used by MATPOWER, including its extensible OPF architecture, are presented, which are used internally to implement several extensions to the standard OPF problem, including piece-wise linear cost functions, dispatchable loads, generator capability curves, and branch angle difference limits.
Abstract: MATPOWER is an open-source Matlab-based power system simulation package that provides a high-level set of power flow, optimal power flow (OPF), and other tools targeted toward researchers, educators, and students. The OPF architecture is designed to be extensible, making it easy to add user-defined variables, costs, and constraints to the standard OPF problem. This paper presents the details of the network modeling and problem formulations used by MATPOWER, including its extensible OPF architecture. This structure is used internally to implement several extensions to the standard OPF problem, including piece-wise linear cost functions, dispatchable loads, generator capability curves, and branch angle difference limits. Simulation results are presented for a number of test cases comparing the performance of several available OPF solvers and demonstrating MATPOWER's ability to solve large-scale AC and DC OPF problems.
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TL;DR: A novel model-specific DNN is developed for real-time PSSE requiring only offline training and minimal tuning effort and outperforms nearly by an order-of-magnitude its competing alternatives, including the widely adopted Gauss–Newton PSSE solver.
Abstract: Contemporary power grids are being challenged by rapid and sizeable voltage fluctuations that are caused by large-scale deployment of renewable generators, electric vehicles, and demand response programs. In this context, monitoring the grid's operating conditions in real time becomes increasingly critical. With the emergent large scale and nonconvexity, existing power system state estimation (PSSE) schemes become computationally expensive or often yield suboptimal performance. To bypass these hurdles, this paper advocates physics-inspired deep neural networks (DNNs) for real-time power system monitoring. By unrolling an iterative solver that was originally developed using the exact ac model, a novel model-specific DNN is developed for real-time PSSE requiring only offline training and minimal tuning effort. To further enable system awareness, even ahead of the time horizon, as well as to endow the DNN-based estimator with resilience, deep recurrent neural networks (RNNs) are also pursued for power system state forecasting. Deep RNNs leverage the long-term nonlinear dependencies present in the historical voltage time series to enable forecasting, and they are easy to implement. Numerical tests showcase improved performance of the proposed DNN-based estimation and forecasting approaches compared with existing alternatives. In real load data experiments on the IEEE 118-bus benchmark system, the novel model-specific DNN-based PSSE scheme outperforms nearly by an order-of-magnitude its competing alternatives, including the widely adopted Gauss–Newton PSSE solver.
147 citations
Cites methods from "MATPOWER: Steady-State Operations, ..."
...by a factor of 5 (2) for the IEEE 57-bus (118-bus) system. Subsequently, the resultant load instances were normalized to match the scale of power demands in the simulated system. The MATPOWER toolbox [41] was used to solve the AC power flow equations with the normalized load series as inputs, to obtain the ground-truth voltages fv ˝g, and produce measurements fz ˝gthat comprise all forwarding-end activ...
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TL;DR: A scalable and analytically tractable probabilistic model for the cascading failure dynamics in power grids is constructed while retaining key physical attributes and operating characteristics of the power grid.
Abstract: A scalable and analytically tractable probabilistic model for the cascading failure dynamics in power grids is constructed while retaining key physical attributes and operating characteristics of the power grid. The approach is based upon extracting a reduced abstraction of large-scale power grids using a small number of aggregate state variables while modeling the system dynamics using a continuous-time Markov chain. The aggregate state variables represent critical power-grid attributes, which have been shown, from prior simulation-based and historical-data-based analysis, to strongly influence the cascading behavior. The transition rates among states are formulated in terms of certain parameters that capture grid's operating characteristics comprising loading level, error in transmission-capacity estimation, and constraints in performing load shedding. The model allows the prediction of the evolution of blackout probability in time. Moreover, the asymptotic analysis of the blackout probability enables the calculation of the probability mass function of the blackout size. A key benefit of the model is that it enables the characterization of the severity of cascading failures in terms of the operating characteristics of the power grid.
145 citations
Cites methods from "MATPOWER: Steady-State Operations, ..."
...R. D. Zimmerman, C. E. Murillo-Sanchez, R. J. Thomas, "MATPOWER: Steady-state operations planning and analysis tools for power systems research and education", IEEE Trans....
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...We use MATPOWER [24], which is a package of MATLAB m-files, for solving the optimal power flow and simulating cascading failures....
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TL;DR: In this paper, a probabilistic energy flow framework of integrated electrical and gas systems is initially proposed considering correlated varying energy demands and wind power, and a multilinear method is specially designed to produce a deterministic energy flow solution for each sample generated by Monte Carlo simulation (MCS).
Abstract: The deep interdependence between electrical and gas systems entails a potential threat to the security (or reliability) of both systems. It is imperative to investigate the impacts of massive uncertainties on the overall secure and economical operation of both systems. In this paper, a probabilistic energy flow framework of integrated electrical and gas systems is initially proposed considering correlated varying energy demands and wind power. Three aspects of couplings between electrical and gas systems are considered: gas-fired generators, electric-driven compressors, and energy hubs integrated with power to gas (P2G) units. Furthermore, a multilinear method is specially designed to produce a deterministic energy flow solution for each sample generated by Monte Carlo simulation (MCS). Finally, test results have verified that the proposed multilinear MCS method prevails over the nonlinear MCS. In addition, P2G effectively benefits the operation of both electrical and gas networks.
143 citations
Cites methods from "MATPOWER: Steady-State Operations, ..."
...An integrated energy system composed of the IEEE39node system [28] and the NGS48-node system (as shown in Fig....
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TL;DR: Comparison of obtained results with those reported in the literature shows clearly the superiority of ALO algorithm over other recently published algorithms in regards to real power losses and computational time, and hence confirmation of the efficiency ofALO algorithm in providing near-optimal solution.
143 citations
TL;DR: An intelligent operation strategy for energy storage which improves reliability considering the renewable energy integration is presented and a bulk power system reliability evaluation framework is proposed to study the reliability impact brought by the energy storage integration and operation.
Abstract: Electric power industry is experiencing a movement from the existing conventional electric grid to a more reliable, efficient and secure smart grid. In order to achieve these goals, components such as energy storage will be included, and potentially in large scale. Many feasible applications of energy storage in power systems have been investigated. The major benefits of energy storage include electric energy time-shift, frequency regulation and transmission congestion relief. In this paper, we focus on the reliability improvement of the bulk power system brought by the utilization of energy storage in the local distribution systems integrated with renewable energy generation. An intelligent operation strategy for energy storage which improves reliability considering the renewable energy integration is presented. The smart grid communication and control network is utilized to implement the proposed energy storage operation. A bulk power system reliability evaluation framework is proposed to study the reliability impact brought by the energy storage integration and operation. A detailed case study and sensitivity analysis is performed to demonstrate the effectiveness of the presented operation strategy and evaluation framework, and to provide valuable insights on the power system reliability impact derived from the energy storage integration.
142 citations
Cites methods from "MATPOWER: Steady-State Operations, ..."
...DC Optimal Power Flow is performed using MatPower [22] to determine the bulk power system state and dispatch energy storage discharge....
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References
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Book•
01 Jan 1984
TL;DR: In this paper, the authors present a graduate-level text in electric power engineering as regards to planning, operating, and controlling large scale power generation and transmission systems, including characteristics of power generation units, transmission losses, generation with limited energy supply, control of generation, and power system security.
Abstract: Topics considered include characteristics of power generation units, transmission losses, generation with limited energy supply, control of generation, and power system security. This book is a graduate-level text in electric power engineering as regards to planning, operating, and controlling large scale power generation and transmission systems. Material used was generated in the post-1966 period. Many (if not most) of the chapter problems require a digital computer. A background in steady-state power circuit analysis is required.
6,344 citations
TL;DR: This paper describes a simple, very reliable and extremely fast load-flow solution method that is attractive for accurate or approximate off-and on-line routine and contingency calculations for networks of any size, and can be implemented efficiently on computers with restrictive core-store capacities.
Abstract: This paper describes a simple, very reliable and extremely fast load-flow solution method with a wide range of practical application. It is attractive for accurate or approximate off-and on-line routine and contingency calculations for networks of any size, and can be implemented efficiently on computers with restrictive core-store capacities. The method is a development on other recent work employing the MW-?/ MVAR-V decoupling principle, and its precise algorithmic form has been determined by extensive numerical studies. The paper gives details of the method's performance on a series of practical problems of up to 1080 buses. A solution to within 0.01 MW/MVAR maximum bus mismatches is normally obtained in 4 to 7 iterations, each iteration being equal in speed to 1? Gauss-Seidel iterations or 1/5th of a Newton iteration. Correlations of general interest between the power-mismatch convergence criterion and actual solution accuracy are obtained.
1,447 citations
TL;DR: The ac power flow problem can be solved efficiently by Newton's method because only five iterations, each equivalent to about seven of the widely used Gauss-Seidel method are required for an exact solution.
Abstract: The ac power flow problem can be solved efficiently by Newton's method. Only five iterations, each equivalent to about seven of the widely used Gauss-Seidel method, are required for an exact solution. Problem dependent memory and time requirements vary approximately in direct proportion to problem size. Problems of 500 to 1000 nodes can be solved on computers with 32K core memory. The method, introduced in 1961, has been made practical by optimally ordered Gaussian elimination and special programming techniques. Equations, programming details, and examples of solutions of large problems are given.
1,112 citations
"MATPOWER: Steady-State Operations, ..." refers methods in this paper
...The default solver is based on a standard Newton’s method [7] using a polar form and a full Jacobian updated at each iteration....
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TL;DR: Basic features, algorithms, and a variety of case studies are presented in this paper to illustrate the capabilities of the presented tool and its suitability for educational and research purposes.
Abstract: This paper describes the Power System Analysis Toolbox (PSAT), an open source Matlab and GNU/Octave-based software package for analysis and design of small to medium size electric power systems. PSAT includes power flow, continuation power flow, optimal power flow, small-signal stability analysis, and time-domain simulation, as well as several static and dynamic models, including nonconventional loads, synchronous and asynchronous machines, regulators, and FACTS. PSAT is also provided with a complete set of user-friendly graphical interfaces and a Simulink-based editor of one-line network diagrams. Basic features, algorithms, and a variety of case studies are presented in this paper to illustrate the capabilities of the presented tool and its suitability for educational and research purposes.
890 citations
"MATPOWER: Steady-State Operations, ..." refers background or methods in this paper
...This at least partially explains the lack of a graphical user interface used by some related tools such as PSAT [5]....
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...A nice summary of their features is presented in [5]....
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