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: In this paper, a spatio-temporal correlation analysis approach for anomaly detection and location in distribution networks is proposed, which is sensitive to the anomalies and robust to random fluctuations, which makes it possible for detecting early anomalies and reducing false alarming rate.
Abstract: The online monitoring data in distribution networks contain rich information on the running states of the networks. By leveraging the data, this paper proposes a spatio-temporal correlation analysis approach for anomaly detection and location in distribution networks. First, spatio-temporal matrix for each feeder line in a distribution network is formulated and the spectrum of its covariance matrix is analyzed. The spectrum is complex and exhibits two aspects: 1) bulk, which arises from random noise or fluctuations and 2) spikes, which represents factors caused by anomaly signals or fault disturbances. Then, by connecting the estimation of the number of factors to the limiting empirical spectral density of covariance matrices of residuals, the spatio-temporal parameters are accurately estimated, during which free random variable techniques are used. Based on the estimators, anomaly indicators are designed to detect and locate the anomalies by exploring the variations of spatio-temporal correlations in the data. The proposed approach is sensitive to the anomalies and robust to random fluctuations, which makes it possible for detecting early anomalies and reducing false alarming rate. Case studies on both synthetic data and real-world online monitoring data verify the effectiveness and advantages of the proposed approach.
43 citations
Posted Content•
TL;DR: The set of optimization problems in electric power systems engineering known collectively as Optimal Power Flow (OPF) is one of the most practically important and well-researched subfields of constrained nonlinear optimization.
Abstract: The set of optimization problems in electric power systems engineering known collectively as Optimal Power Flow (OPF) is one of the most practically important and well-researched subfields of constrained nonlinear optimization. OPF has enjoyed a rich history of research, innovation, and publication since its debut five decades ago. Nevertheless, entry into OPF research is a daunting task for the uninitiated---both due to the sheer volume of literature and because OPF's familiarity within the electric power systems community has led authors to assume a great deal of prior knowledge that readers unfamiliar with electric power systems may not possess. This primer provides a practical introduction to OPF from an Operations Research perspective; it describes a complete and concise basis of knowledge for beginning OPF research. The primer is tailored for the Operations Researcher who has experience with optimization but little knowledge of Electrical Engineering. Topics include power systems modeling, the power flow equations, typical OPF formulations, and data exchange for OPF.
43 citations
TL;DR: Two parallel PF solvers are presented that exploit the massively parallel architecture of graphics processing units (GPU) in a hybrid GPU-central processing unit (CPU) computing environment using compute unified device architecture and OpenMP in order to significantly speedup the concurrent analysis of many instances of a network.
Abstract: The power flow (PF) analysis provides the steady state of the power system and is key to the simulation of transmission networks. It is a tool commonly used by system operators to visualize the effect of generator settings on the network prior to making a change. In situations involving large networks, hundreds or even thousands of PF analysis may have to be run on the network before finding the optimal power dispatch. This process requires significant computation time and does not allow for rapid control of the network. To address this problem, this paper presents two parallel PF solvers that exploit the massively parallel architecture of graphics processing units (GPU) in a hybrid GPU-central processing unit (CPU) computing environment using compute unified device architecture and OpenMP in order to significantly speedup the concurrent analysis of many instances of a network. Both implementations use sparse matrices, double precision operations, and enforce the reactive power limit of generators. The parallel Gauss-Seidel (G-S) and Newton-Raphson (N-R) PF algorithms are tested on networks ranging from 4 to 2383 buses. The accuracy is validated using MATPOWER and the maximum speedup achieved, compared with a sequential execution on CPU, is $45.2 \boldsymbol {\times }$ for G-S and $17.8 \boldsymbol {\times }$ for N-R.
43 citations
Cites background or methods from "MATPOWER: Steady-State Operations, ..."
...To perform this test, we used MATPOWER v5....
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...In our test, we used the input files included with MATPOWER and ran the power flow analysis using our sequential G-S and N-R on CPU, our parallel G-S and N-R on GPU and the MATPOWER G-S and N-R solvers....
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...The number of iterations before the convergence of our G-S implementations is higher than that of MATPOWER....
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...The line model and the composition of the Ybus matrix is discussed in [41]....
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...The program is compatible with MATPOWER [41] and supports the MPC v2 input file format....
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TL;DR: A framework that co-optimizes the VPP provision of multiple market, system, and local network services with the aim of maximizing its revenue and demonstrates how the framework enables effective deployment of VPP flexibility to maximize its multi-service value stack, within an uncertain operating environment, and within technical limits.
Abstract: Market and network integration of distributed energy resources can be facilitated by their coordination within a virtual power plant (VPP). However, VPP operation subject to network limits and different market and physical uncertainties is a challenging task. This paper introduces a framework that co-optimizes the VPP provision of multiple market (e.g., energy, reserve), system (e.g., fast frequency response, inertia, upstream reactive power), and local network (e.g., voltage support) services with the aim of maximizing its revenue. To ensure problem tractability, while accommodating the uncertain nature of market prices, local demand, and renewable output and while operating within local network constraints, the framework is broken down into three sequentially coordinated optimization problems. Specifically, a scenario-based robust optimization for day-ahead resource scheduling, with linearized power flows, and two receding horizon optimizations for close-to-real-time dispatch, with a more accurate second-order cone relaxation of the power flows. The results from a real Australian case study demonstrate how the framework enables effective deployment of VPP flexibility to maximize its multi-service value stack, within an uncertain operating environment, and within technical limits.
43 citations
TL;DR: In this article, a risk-based security assessment methodology is presented, which allows the assessment of operational security of a power system's future state under uncertainty deriving from varying topology scenarios (contingencies) and forecast errors (loads and renewable infeeds).
Abstract: In this paper, a risk-based security assessment methodology is presented, which allows the assessment of operational security of a power system's future state under uncertainty deriving from varying topology scenarios (contingencies) and forecast errors (loads and renewable infeeds). The methodology models input uncertainty with a copula function-based Monte–Carlo (MC) framework. Furthermore, it provides the highest level of accuracy on initiating causes of failures through an AC power flow (AC PF) framework. Finally, it achieves speed in solution by the combination of two measures of risk. A fast screening tool, based on severity functions, allows us to quickly screen the system for the most severe states. A detailed analysis tool, based on an AC optimal power flow (AC OPF) framework and the notion of lost load, provides additional valuable information, including remedial actions to steer away from severe system states. This paper presents results from the application of the methodology proving the necessity of such a framework. It is shown that not taking into account stochastic dependence through a proper MC setup seriously underestimates system risk and that an AC framework is needed, as voltage deviations are shown to often be initiators of system collapse.
43 citations
Cites methods from "MATPOWER: Steady-State Operations, ..."
...The presented methodology is implemented in MATLAB using the MATPOWER package [21] for power system modeling....
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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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