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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11 Jun 2018
TL;DR: An approach to estimate the flexibility of an Active Distribution Network to provide ancillary services across voltage levels by the regulation of the power flow over the transmission-distribution interface is described.
Abstract: This paper describes an approach to estimate the flexibility of an Active Distribution Network (ADN) to provide ancillary services across voltage levels by the regulation of the power flow over the transmission-distribution interface. Therefore, a modelling framework is introduced to describe and discuss the impact of time-variant and time-invariant influencing factors on the flexibility of an ADN. Building on this framework, two methodologies are suggested: The first can be used to determine the flexibility of an ADN under the premise of perfect information, i.e. when all modelled influencing factors are known. The second is meant to assess in advance the flexibility that an ADN will have in future time intervals using forecasts of time-variant influencing factors handling uncertainty by a probabilistic approach. The applicability of the proposed methods is demonstrated in a case-study. Central findings regarding properties and determinability of the flexibility of ADNs are discussed.
56 citations
TL;DR: Experimental results show that the proposed unsupervised method to distinguish between attack and normal patterns can be fed into an expert system for further improvement of the security of the power grid.
Abstract: An unsupervised method is proposed for detecting cyber-attacks after topology changes.Detection is performed by quantifying the probability distributions of the state vectors.Quantification is done through extracting several statistical measures.Localization of attacks is performed by Fuzzy c-means.Performance of classification methods is analyzed in managing system reconfigurations. To achieve intelligence in the future grid, a highly accurate state estimation is necessary as it is a prerequisite for many key functionalities in the successful operation of the power grid. Recent studies show that a new type of cyber-attack called False Data Injection (FDI) attack can bypass bad data detection mechanisms in the power system state estimation. Existing countermeasures might not be able to manage topology changes and integration of distributed generations because they are designed for a specific system configuration. To address this issue, an unsupervised method to distinguish between attack and normal patterns is proposed in this paper. This method can detect FDI attacks even after topology changes and integration of renewable energy sources. In this method, we assume that injecting false data into the power systems will lead to a deviation in the probability distribution of the state vector from the normal trend. The main phases of the proposed algorithm are: (1) Normalizing the dataset, (2) Adding several statistical measures as the new features to the dataset to quantify the probability distribution of the state vectors, (3) Employing principal component analysis to reduce the dimensionality of the dataset, (4) Visualizing the reduced data for humans and exploiting their creativity to detect attacks, and (5) Locating the attacks using Fuzzy C-means clustering algorithm.The proposed method is tested on both the IEEE 14-bus and IEEE 9-bus systems using real load data from the New York independent system operator with the following attack scenarios: (1) attacks without any topology change, (2) attacks after a contingency, and (3) attacks after integration of distributed generations. Experimental results show that our proposed method is superior to the state-of-the-art classification algorithms in dealing with changes. In addition, the reduced data which is helpful in distinguishing between attack and normal patterns can be fed into an expert system for further improvement of the security of the power grid.
56 citations
TL;DR: The experimental evaluation results show that the DQND outperforms the existing deep reinforcement learning-based detection scheme in terms of detection accuracy and rapidity in the IEEE 9, 14, and 30 bus systems.
Abstract: State estimation plays a critical role in monitoring and managing operation of smart grid. Nonetheless, recent research efforts demonstrate that data integrity attacks are able to bypass the bad data detection mechanism and make the system operator obtain the misleading states of system, leading to massive economic losses. Particularly, data integrity attacks have become critical threats to the power grid. In this paper, we propose a deep-Q-network detection (DQND) scheme to defend against data integrity attacks in alternating current (AC) power systems. DQND is a deep reinforcement learning scheme, which avoids the problem of curse of dimension that conventional reinforcement learning schemes have. Our strategy in DQND applies a main network and a target network to learn the optimal defending strategy. To improve the learning efficiency, we propose the quantification of observation space and utilize the concept of slide window as well. The experimental evaluation results show that the DQND outperforms the existing deep reinforcement learning-based detection scheme in terms of detection accuracy and rapidity in the IEEE 9, 14, and 30 bus systems.
56 citations
Cites methods from "MATPOWER: Steady-State Operations, ..."
...The initial state vector (phase angles and voltagemagnitudes) is determined based onMATPOWER [47]....
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TL;DR: In this article, a probabilistic approach to network planning is presented to determine the technically and economically optimal solution that will ensure continuity of supply and adequate power quality as well as allow further integration of distributed generation, despite its substantial impact on the network performance.
55 citations
TL;DR: In this paper, a dc optimal power flow that co-optimizes FACTS set points alongside generation dispatch is proposed, which is then reformulated to a mixed-integer linear program.
Abstract: Enhanced utilization of the existing transmission network is a cheaper and paramount alternative to building new transmission lines. Flexible ac transmission system (FACTS) devices are advanced technologies that offer transfer capability improvements via power flow control. Although many FACTS devices exist in power systems, their set points are not frequently changed for power flow control purposes, which is mainly due to the computational complexity of incorporating FACTS flexibility within the market problem. This paper proposes a computationally efficient method for adjustment of variable impedance-based FACTS set points, which is also compatible with existing market solvers. Thus, the method can be employed by the existing solvers with minimal modification efforts. This paper models FACTS reactance control as injections to keep the initial shift factors unchanged. Next, the paper formulates a dc optimal power flow that co-optimizes FACTS set points alongside generation dispatch. The resulting problem, which is in a nonlinear program, is then reformulated to a mixed-integer linear program. Finally, an engineering insight is leveraged to further reduce the computational complexity to a linear program. Simulation studies on IEEE 118-bus and Polish 2383-bus test cases show that the method is extremely effective in finding quality solutions and being very fast.
55 citations
Cites background from "MATPOWER: Steady-State Operations, ..."
...The data is taken from [40], [41], which represents the Polish electric grid in a peak winter hour in year 2000....
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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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