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 Jun 2020
TL;DR: A spiking-neural-network-based technique for dynamic cyber-attack detection in a smart grid through judiciously integrating spiking neurons with a special recurrent neural network called the delayed feedback reservoir computing is developed.
Abstract: Spiking neural networks have been widely used for supervised pattern recognition exploring the underlying spatio-temporal correlation. Meanwhile, spatio-temporal correlation manifests significantly between different components in a smart grid making the spiking neural network a desirable candidate for false data injection attack detection. In this paper, we develop a spiking-neural-network-based technique for dynamic cyber-attack detection in a smart grid. This is achieved through judiciously integrating spiking neurons with a special recurrent neural network called the delayed feedback reservoir computing. The inter-spike interval encoding is also explored in the precise-spike-driven synaptic plasticity based training process. The simulation results suggest that the introduced method outperforms multi-layer perceptrons and can achieve a significantly better performance compared to the state-of-the-art techniques. Furthermore, our analysis indicates that the delay value in the delayed feedback reservoir will have a substantial impact on the overall system performance.
30 citations
TL;DR: Detailed numerical experiments are presented to illustrate the effectiveness and flexibility of the proposed methodology for balancing efficiency, constraint violation risk, and out-of-sample performance, offering systematic techniques for system operators to balance these objectives.
Abstract: This is the second part of a two-part paper on data-based distributionally robust stochastic optimal power flow. The general problem formulation and methodology have been presented in Part I (Y. Guo, K. Baker, E. Dall’Anese, Z. Hu, and T.H. Summers, “Data-based distributionally robust stochastic optimal power flow—Part I: Methodologies,” IEEE Trans. Power Syst. , 2018.). Here, we present extensive numerical experiments in both distribution and transmission networks to illustrate the effectiveness and flexibility of the proposed methodology for balancing efficiency, constraint violation risk, and out-of-sample performance. On the distribution side, the method mitigates overvoltages due to high photovoltaic penetration using local energy storage devices. On the transmission side, the method reduces $N-1$ security line flow constraint risks due to high wind penetration using reserve policies for controllable generators. In both cases, the data-based distributionally robust model-predictive control algorithm explicitly utilizes forecast error training datasets, which can be updated online. The numerical results illustrate inherent tradeoffs between the operational costs, risks of constraints violations, and out-of-sample performance, offering systematic techniques for system operators to balance these objectives.
30 citations
Cites methods from "MATPOWER: Steady-State Operations, ..."
...We consider a modified IEEE 118-bus test system [45] to demonstrate our proposed data-based distributionally robust stochastic DC OPF shown in Fig....
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TL;DR: In this paper, a Virtual Energy Storage System (VESS) is proposed to provide voltage control in distribution networks in order to accommodate more distributed generation capacity and to compensate for the uncertainty of demand response.
Abstract: —Increasing amount of Distributed Generation (DG)
connected to distribution networks may lead to the voltage and
thermal limits violation. This paper proposes a Virtual Energy
Storage System (VESS) to provide voltage control in distribution
networks in order to accommodate more DG. A VESS control
scheme coordinating the demand response and the energy storage
system was developed. The demand response control measures the
voltage of the connected bus and changes the power consumption
of the demand to eliminate voltage violations. The response of
energy storage systems was used to compensate for the
uncertainty of demand response. The voltage control of energy
storage system is a droop control with droop gain values
determined by voltage sensitivity factors. The control strategy of
the VESS was applied to a medium-voltage network and results
show that the control of VESS not only facilitates the
accommodation of higher DG capacity in the distribution network
without voltage violations or network reinforcements but also
prolongs the lifetime of transformer on-load tap changer.
30 citations
01 Dec 2017
TL;DR: This work employs polynomial chaos expansion to rewrite the infinite-dimensional random-variable optimization problem as a finite-dimensional convex second-order cone program that can be solved efficiently in a single numerical run for all realizations of the uncertainty.
Abstract: The increasing penetration of renewable energy sources to power grids necessitates a structured consideration of uncertainties for optimal power flow problems. Modeling uncertainties via continuous random variables of finite variance we propose a tractable convex formulation of the uncertain optimal power flow problem. The uncertainties can be (non-)Gaussian, multivariate and/or correlated. We employ polynomial chaos expansion to rewrite the infinite-dimensional random-variable optimization problem as a finite-dimensional convex second-order cone program. This problem can be solved efficiently in a single numerical run for all realizations of the uncertainty. The solution provides a feedback policy in terms of the fluctuations. No Monte Carlo sampling is required to obtain either the solution or its statistics. The reduced computational effort and yet consistent results stemming from polynomial chaos are demonstrated in comparison to a Monte-Carlo-based solution for the ieee 300-bus test system.
30 citations
Cites methods from "MATPOWER: Steady-State Operations, ..."
...The MC solution is ‘true’ in the sense of full information: for a total of NMC realizations of the uncertain fixed power d the corresponding deterministic DCOPF (4) is solved (using Matpower [20] with Gurobi)....
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06 Jan 2014
TL;DR: This work presents a method to correct OTS solutions obtained in the DC model to ensure feasible AC power flow solutions that are both AC feasible and generate significant system cost reductions - in some cases larger than the cost reductions suggested by the DC OTS.
Abstract: Optimal Transmission Switching (OTS) has demonstrated significant savings potential on test systems when formulated in a linearized DC power flow framework. OTS solutions generated from DC models, however, are not guaranteed to produce a feasible AC dispatch. Additionally, whether AC-feasible OTS solutions will generate cost savings similar to those suggested in the DC model is not guaranteed. We present a method to correct OTS solutions obtained in the DC model to ensure feasible AC power flow solutions. When applied to the RTS-96 benchmark network, the method achieves results that are both AC feasible and generate significant system cost reductions - in some cases larger than the cost reductions suggested by the DC OTS.
30 citations
Cites methods from "MATPOWER: Steady-State Operations, ..."
...ACOPF problems are solved using the Matpower version 4.1 toolbox in MATLAB [12], using the constrained nonlinear multivariate minimization tool in the MATLAB Optimization Toolbox....
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...1 toolbox in MATLAB [12], using the constrained nonlinear multivariate minimization tool in the...
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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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