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 article, the value of P2P trading compared to cases where no local markets are available, along with the impact of PV, batteries, and EVs deployment in a real-life neighbourhood of 52 households in Norway.
51 citations
TL;DR: DeepOPF as mentioned in this paper is 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.
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.
51 citations
Posted Content•
TL;DR: In this paper, a new probabilistic forecasting technique is proposed based on a multiparametric programming formulation that partitions the uncertainty parameter space into critical regions from which the conditional probability distribution of the real-time LMP/congestion is obtained.
Abstract: The short-term forecasting of real-time locational marginal price (LMP) and network congestion is considered from a system operator perspective. A new probabilistic forecasting technique is proposed based on a multiparametric programming formulation that partitions the uncertainty parameter space into critical regions from which the conditional probability distribution of the real-time LMP/congestion is obtained. The proposed method incorporates load/generation forecast, time varying operation constraints, and contingency models. By shifting the computation cost associated with multiparametric programs offline, the online computation cost is significantly reduced. An online simulation technique by generating critical regions dynamically is also proposed, which results in several orders of magnitude improvement in the computational cost over standard Monte Carlo methods.
51 citations
TL;DR: In this paper, the authors propose a flexible market led by the distribution system operator (DSO) and aimed at solving distribution grid congestions, which includes a flexibility market clearing algorithm, which is easy to implement, has low computational requirements and considers the energy rebound effect.
Abstract: Nowadays, problems facing Distribution System Operators (DSOs) due to demand increase and the wide penetration of renewable energy are usually solved by means of grid reinforcement. However, the smart grid paradigm enables the deployment of demand flexibility for congestion management in distribution grids. This could substitute, or at least postpone, these needed investments. A key role in this scheme is the aggregator, who can act as a “flexibility provider” collecting the available flexibility from the consumers. Under this paradigm, this paper proposes a flexibility market led by the DSO and aimed at solving distribution grid congestions. The proposal also includes a flexibility market clearing algorithm, which is easy to implement, has low computational requirements and considers the energy rebound effect. The proposed design has the advantage of excluding the DSO’s need for trading in energy markets. Also, the solution algorithm proposed is fully compatible with already existing grid analysis tools. The proposed electricity market is tested with two case studies from a real Spanish distribution network, where the proposed clearing algorithm is used, and finally, results are presented and discussed.
50 citations
TL;DR: This article provides a review of existing methods and describes a new formulation of the LOPF that expresses the loading constraints directly in terms of the flows themselves, using a decomposition of the network graph into a spanning tree and closed cycles.
50 citations
Cites methods from "MATPOWER: Steady-State Operations, ..."
...gtheproblemusingPower TransferDistributionFactors(PTDFs)[16,17]andaparallelizablealgorithmusingtheprimal-dualinteriorpointmethod[18]. In textbooks [6, 19] and major software packages such as MATPOWER [20], DIgSILENT PowerFactory [21], PowerWorld [22] and PSAT [23], the linearizationof the relationsbetween power flows in the network and power injection at the buses is expressed indirectly through auxili...
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... removes an unnecessary degree of freedom. Here and in the following the p i are used as a short-hand notation accordingto equation (15). ThePureAngleformulationis usedinthefreesoftwaretools MATPOWER [20] and PYPOWER [31]; it is therefore used as the benchmark implementation against which we compare all other formulationsin Section 5. 3.2. Angle+Flowformulation For the Angle+Flow formulation of the LO...
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...k. 5.1. Problem preparation Seven different network topologies are considered. case118, case300, case1354pegase, case1951rte, case2383wp and case2869pegase are taken from the MATPOWER software package [20] test cases (the IEEE standard cases as well as snapshots from the French TSO RTE and European networks [39]). In addition the open data SciGRID model of Germany’s transmission network [40] is also te...
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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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