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.
Citations
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01 Jan 2018
TL;DR: This paper presents a study based on versatile bio-inspired metaheuristic stud krill herd (SKH) algorithm to tackle the optimal power flow problems in a power system network and the results obtained are compared with the other evolutionary algorithms recently reported in the literature.
Abstract: This paper presents a study based on versatile bio-inspired metaheuristic stud krill herd (SKH) algorithm to tackle the optimal power flow (OPF) problems in a power system network. SKH consists of stud selection and crossover operator that is incorporated into the original krill herd algorithm to improve the quality of the solution and especially to avoid being trapped in local optima. In order to investigate the performance, the proposed algorithm is demonstrated on the optimal power flow problems of IEEE 14-bus, IEEE 30-bus and IEEE 57-bus systems. The different objective functions considered are minimization of total production cost with and without valve point loading effect, minimization of active power loss, minimization of L-index and minimization of emission pollution. The OPF results obtained with the proposed approach are compared with the other evolutionary algorithms recently reported in the literature.
62 citations
Cites background or methods from "MATPOWER: Steady-State Operations, ..."
...…41718.945 13.68 – ICA (Jadhav and Bamane 2016) 41709.7292 41712.6836 41715.6957 11.57 – GA (Jadhav and Bamane 2016) 41711.9365 41719.604 41734.1638 18.15 – MATPOWER (Zimmerman et al. 2011) 51,347.86 – – – – M2 SKH 10.6877 11.1110 12.0016 0.4751 49.58 KH 11.2158 12.0275 13.5281 0.6360…...
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...…and shunt capacitors lie between 0 and 0.05 p.u.Detailed information about IEEE 14-bus system and generator cost coefficients are considered from Zimmerman et al. (2011); emission coefficients are referred from Sarat and Sudhansu (2015), and for fair comparison, the generator cost coefficients…...
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...…these OPF problems, such as nonlinear programming (Shoults and Sun 1982), linear programming (LP) (Zehar and Sayah 2008), quadratic programming (QP) (Reid andHasdorf 1973), Newton’s algorithm (Sun et al. 1984), interior point (IP) (Torres andQuintana 1998),MATPOWER (Zimmerman et al. 2011), etc....
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...The bus data, fuel cost coefficients and branch data are referred from Zimmerman et al. (2011). For IEEE 57-bus system, the minimum total production cost value over 20 independent trials with different values of Nmax, Dmax, Vf , for single- and two-point crossover arementioned inTable 7....
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...1984), interior point (IP) (Torres andQuintana 1998),MATPOWER (Zimmerman et al. 2011), etc....
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TL;DR: Computational results show that the MIP methods, while lacking the speed of the genetic algorithm, can find improved solutions within conservative time requirements and provide useful information on optimality.
Abstract: This paper applies recently developed mixed-integer programming (MIP) tools to the problem of optimal siting and sizing of distributed generators in a distribution network. We investigate the merits of three MIP approaches for finding good installation plans: a full AC power flow approach, a linear DC power flow approximation, and a nonlinear DC power flow approximation with quadratic loss terms, each augmented with integer generator placement variables. A genetic algorithm-based approach serves as a baseline for the comparison. A simple knapsack problem method involving generator selection is presented for determining lower bounds on the optimal design objective. Solution methods are outlined, and computational results show that the MIP methods, while lacking the speed of the genetic algorithm, can find improved solutions within conservative time requirements and provide useful information on optimality.
62 citations
Cites methods from "MATPOWER: Steady-State Operations, ..."
...The full AC Newton’s method power flow module of MATLAB-based power flow package, MATPOWER [32], version...
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...following the default settings in MATPOWER [32]....
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Posted Content•
30 Oct 2019TL;DR: DeepOPF is inspired by the observation that solving SC-DCOPF problems for a given power network is equivalent to depicting a high-dimensional mapping from the load inputs to the generation and phase angle outputs and develops a post-processing procedure based on $\ell _1$-projection to ensure the feasibility of the obtained solution.
Abstract: We develop DeepOPF as a Deep Neural Network (DNN) approach for solving security-constrained direct current optimal power flow (SC-DCOPF) problems, which are critical for reliable and cost-effective power system operation.DeepOPF is inspired by the observation that solving SC-DCOPF problems for a given power network is equivalent to depicting a high-dimensional mapping from the load inputs to the generation and phase angle outputs. We first train a DNN to learn the mapping and predict the generations from the load inputs. We then directly reconstruct the phase angles from the generations and loads by using the power flow equations. Such a predict-and-reconstruct approach reduces the dimension of the mapping to learn, subsequently cutting down the size of the DNN and the amount of training data needed. We further derive a condition for tuning the size of the DNN according to the desired approximation accuracy of the load-generation mapping. We develop a post-processing procedure based on $\ell_1$-projection to ensure the feasibility of the obtained solution, which can be of independent interest. Simulation results for IEEE test cases show that DeepOPF generates feasible solutions with less than 0.2% optimality loss, while speeding up the computation time by up to two orders of magnitude as compared to a state-of-the-art solver.
61 citations
Cites methods from "MATPOWER: Steady-State Operations, ..."
...As the Power Grid Lib only has linear cost functions for generators, we use the cost functions from the test cases with same bus from MATPOWER [51] (version 7....
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...As the Power Grid Lib only has linear cost functions for generators, we use the cost functions from the test cases with same bus from MATPOWER [51] (version 7.0) while all other parameters are taken from the Power Grid Lib cases....
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...[51] R. D. Zimmerman et al., “MATPOWER: Steady-state operations, planning, and analysis tools for power systems research and education,” IEEE Trans....
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TL;DR: In this article, the authors show that the economic benefits of reducing the peak system load using storage or controllable demand will be higher with high penetrations of wind generation, and that the benefits are very sensitive to how much of the inherent variability of wind power is mitigated, and how the missing money is determined.
Abstract: Earlier research has shown that adding wind generation to a network can lower the total annual operating cost by displacing conventional generation. At the same time, the variability of wind generation and the need for higher levels of reserve generating capacity to maintain reliability standards impose additional costs on the system that should not be ignored. The important implication for regulators is that the capacity payments ["missing money"] for each MW of peak system load are now much higher. Hence, the economic benefits of reducing the peak system load using storage or controllable demand will be higher with high penetrations of wind generation. These potential benefits are illustrated in a case study using a test network and a security constrained Optimal Power Flow (OPF) with endogenous reserves (SuperOPF). The results show that the benefits are very sensitive to 1) how much of the inherent variability of wind generation is mitigated, and 2) how the missing money is determined (e.g. comparing regulation with deregulation).
61 citations
TL;DR: This paper presents an algorithm that is guaranteed to compute the entire feasible spaces of small OPF problems to within a specified discretization tolerance.
Abstract: The solution to an optimal power flow (OPF) problem provides a minimum cost operating point for an electric power system. The performance of OPF solution techniques strongly depends on the problem's feasible space. This paper presents an algorithm that is guaranteed to compute the entire feasible spaces of small OPF problems to within a specified discretization tolerance. Specifically, the feasible space is computed by discretizing certain of the OPF problem's inequality constraints to obtain a set of power flow equations. All solutions to the power flow equations at each discretization point are obtained using the Numerical Polynomial Homotopy Continuation algorithm. To improve computational tractability, “bound tightening” and “grid pruning” algorithms use convex relaxations to preclude consideration of many discretization points that are infeasible for the OPF problem. The proposed algorithm is used to generate the feasible spaces of two small test cases.
61 citations
Cites methods from "MATPOWER: Steady-State Operations, ..."
...approaches, such as a Newton-based power flow solver in place of the NPHC algorithm and a local optimization solver instead of the moment relaxations (for instance, the algorithms available in MATPOWER [58])....
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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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