Solving the optimal power flow (OPF) problem on a large power system is computationally expensive. Network reduction and ac-to-dc network conversion can relieve this burden by simplifying the full system model to a smaller and mathematically simpler model. Traditional reduction methods, like Ward reduction, fractionalize generators when the buses they are attached to are removed, and scatters these fractions to topologically adjacent buses. In some OPF applications, this type of generator modeling is problematic. An improved approach is to keep generators intact by moving them whole to buses in reduced model and then redistributing loads to maintain base-case line flows. Determining generator placement using a traditional shortest electrical distance (SED) based method may result in cases where the OPF solution on reduced model is infeasible while the full model has a feasible solution. In this paper, an improved generator placement method is proposed. Tests show that the proposed method yields a better approximation to the full model OPF solutions and is more likely to produce a reduced model with a feasible solution if the unreduced model has a feasible solution.

10aCERTS10anetwork reduction10aoptimal power flow (OPF)10areliability and markets10aRM11-0051 aZhu, Yujia1 aTylavsky, Daniel, J. uhttps://certs.lbl.gov/publications/optimization-based-generator01144nas a2200181 4500008003900000245007700039210006900116260004400185300001000229520053600239653001300775653002900788653001000817653002600827100001400853700002400867856007100891 2014 d00aTransient stability constrained optimal power flow for cascading outages0 aTransient stability constrained optimal power flow for cascading aNational Harbor, MD, USAbIEEEc07/2014 a1 - 53 aThis paper presents a strategy to implement transient stability constrained optimal power flow in cascading outages. Anticipatory computing detects transient instability due to weakened system conditions in cascading progressions and prepares transient stability constraints for optimal power flow. The prepared constraints use trajectory sensitivities, which can speed up the analysis by estimating rotor angle response changing with generation levels. The proposed strategy has been tested on a 140-bus, 48-machine system.

10aAA09-00110aoptimal power flow (OPF)10aRTGRM10aSystem Security Tools1 aTang, Lei1 aMcCalley, James, D. uhttps://certs.lbl.gov/publications/transient-stability-constrained01788nas a2200229 4500008003900000022001400039245009600053210006900149260001100218300001600229490000700245520106900252653001301321653000901334653002901343653001001372100002401382700002201406700002701428700002901455856007401484 2013 d a0885-895000aImplementation of a Large-Scale Optimal Power Flow Solver Based on Semidefinite Programming0 aImplementation of a LargeScale Optimal Power Flow Solver Based o c4/2013 a3987 - 39980 v283 aThe application of semidefinite programming to the optimal power flow (OPF) problem has recently attracted significant research interest. This paper provides advances in modeling and computation required for solving the OPF problem for large-scale, general power system models. Specifically, a semidefinite programming relaxation of the OPF problem is presented that incorporates multiple generators at the same bus and parallel lines. Recent research in matrix completion techniques that decompose a single large matrix constrained to be positive semidefinite into many smaller matrices has made solution of OPF problems using semidefinite programming computationally tractable for large system models. We provide three advances to existing decomposition techniques: a matrix combination algorithm that further decreases solver time, a modification to an existing decomposition technique that extends its applicability to general power system networks, and a method for obtaining the optimal voltage profile from the solution to a decomposed semidefinite program.10aAA13-00510aAARD10aoptimal power flow (OPF)10aRTGRM1 aMolzahn, Daniel, K.1 aHolzer, Jesse, T.1 aLesieutre, Bernard, C.1 aDeMarco, Christopher, L. uhttps://certs.lbl.gov/publications/implementation-large-scale-optimal01240nas a2200193 4500008003900000020002200039245009700061210006900158260003800227300001000265520058600275653001300861653002900874653001000903653002600913100001400939700002400953856006900977 2012 d a978-1-4673-2306-200aAn efficient transient stability constrained optimal power flow using trajectory sensitivity0 aefficient transient stability constrained optimal power flow usi aChampaign, IL, USAbIEEEc09/2012 a1 - 63 aA well-structured two-step efficient transient stability constrained optimal power flow is proposed. The transient stability constraints are obtained through time domain simulation and its corresponding trajectory sensitivity calculation. The process to obtain the constraints is an independent step from the dispatch problem solving. The added transient stability constraints prevent first swing instability, and bring much less computational burden than steady state security constraints. The proposed method was tested on a 9-bus system and the New England 39-bus system.

10aAA09-00110aoptimal power flow (OPF)10aRTGRM10aSystem Security Tools1 aTang, Lei1 aMcCalley, James, D. uhttps://certs.lbl.gov/publications/efficient-transient-stability01434nas a2200253 4500008003900000022001400039245007800053210006900131260001200200300001200212490000800224520071000232653001300942653000900955653001000964653002900974653001001003653002601013100001501039700001301054700001301067700002401080856007601104 2012 d a1748-006X00aLong-term benefits of online risk-based direct-current optimal power flow0 aLongterm benefits of online riskbased directcurrent optimal powe c02/2012 a65 - 740 v2263 aAn online operational risk management method is presented in this paper. In this method, a risk-based direct-current (DC) optimal power flow approach is utilized to replace a traditional security-constrained DC optimal power flow approach. This risk management method is integrated into a commercial energy management system/dispatcher training simulator system to monitor and control system operation risk online. Comparison of the approach with traditional security assessment shows significant benefits over the long term via cost reduction and risk mitigation. A case study provides supporting evidence of risk mitigation in terms of steady-state angular separation reduction and cascading prevention.10aAA09-00110aAARD10aCERTS10aoptimal power flow (OPF)10aRTGRM10aSystem Security Tools1 aDai, R.-C.1 aPham, H.1 aWang, Y.1 aMcCalley, James, D. uhttps://certs.lbl.gov/publications/long-term-benefits-online-risk-based01848nas a2200289 4500008003900000020002200039245007100061210006800132260003800200300001000238520094200248653001001190653002801200653002401228653002901252653002601281653002801307653001301335100001201348700002401360700001201384700002501396700002001421700002301441700002501464856006901489 2012 d a978-1-4673-2306-200aOptimal generation investment planning: Pt. 1: network equivalents0 aOptimal generation investment planning Pt 1 network equivalents aChampaign, IL, USAbIEEEc09/2012 a1 - 63 aThe requirements of a network equivalent to be used in new planning tools are very different from those used in traditional equivalencing procedures. For example, in the classical Ward equivalent, each generator in the external system is broken up into fractions. For newer long-term investment applications that take into account such things as greenhouse gas (GHG) regulations and generator availability, it is computationally impractical to model fractions of generators located at many buses. To overcome this limitation, a modified- Ward equivalencing scheme is proposed in this paper. The proposed scheme is applied to the entire Eastern Interconnection (EI) to obtain several backbone equivalents and these equivalents are tested for accuracy under a range of operating conditions. In a companion paper, the application of an equivalent developed by this procedure is used to perform optimal generation investment planning.

10aCERTS10aEastern Interconnection10ainvestment planning10aoptimal power flow (OPF)10aPower system modeling10areliability and markets10aRM11-0051 aShi, Di1 aShawhan, Daniel, L.1 aLi, Nan1 aTylavsky, Daniel, J.1 aTaber, John, T.1 aZimmerman, Ray, D.1 aSchulze, William, D. uhttps://certs.lbl.gov/publications/optimal-generation-investment01709nas a2200241 4500008003900000022001400039245010900053210006900162260001200231300001200243490000700255520093400262653001001196653001401206653002901220653002701249653002801276653001301304100002301317700003201340700002301372856007201395 2011 d a0885-895000aMATPOWER: Steady-State Operations, Planning, and Analysis Tools for Power Systems Research and Education0 aMATPOWER SteadyState Operations Planning and Analysis Tools for c02/2011 a12 - 190 v263 aMATPOWER 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.10aCERTS10aload flow10aoptimal power flow (OPF)10apower system economics10areliability and markets10aRM07-0021 aZimmerman, Ray, D.1 aMurillo-Sanchez, Carlos, E.1 aThomas, Robert, J. uhttps://certs.lbl.gov/publications/matpower-steady-state-operations01486nas a2200229 4500008003900000022001400039245007200053210006900125260001200194300001600206490000700222520077400229653002401003653001401027653002901041653001301070100002701083700002501110700002401135700002101159856007601180 2011 d a0885-895000aA Sensitivity Approach to Detection of Local Market Power Potential0 aSensitivity Approach to Detection of Local Market Power Potentia c11/2011 a1980 - 19880 v263 aMarket power gives certain market participants the ability to manipulate the market to their advantage when their product is not substitutable by competitors. Identification of generators which have the potential for market power either individually or within a small group is performed using sensitivity information from the linear programming optimal power flow (LP OPF). The impact of network constraints on admissible price perturbations are used to group generators that have the potential to exhibit local market power. Specific price perturbation vectors are found that highlight a constraint-induced locational advantage for these suppliers. In practice, this is most commonly observed in “load pockets,” for which ISO policies mitigate market power.

10aelectricity markets10aload flow10aoptimal power flow (OPF)10aRM05-0021 aLesieutre, Bernard, C.1 aRogers, Katherine, M1 aOverbye, Thomas, J.1 aBorden, Alex, R. uhttps://certs.lbl.gov/publications/sensitivity-approach-detection-local01918nas a2200217 4500008003900000020002200039245008100061210006900142260003700211300001400248520119000262653001901452653002901471653002801500653001501528653001301543100002501556700002301581700002501604856007101629 2010 d a978-1-4577-0488-800aDynamic optimization for the management of stochastic generation and storage0 aDynamic optimization for the management of stochastic generation aSao Paulo, BrazilbIEEEc11/2010 a860 - 8663 aIn order to increase the amounts of renewable energy accommodated in the system, new tools that take into account the horizon of the decision taken are necessary. Feature like the availability of new information can be included in a dynamic optimization framework and therefore help mitigate congestion in the system and have positive effects on distribution systems. This study proposes a new algorithm and shows some preliminary results for the use of Energy Storage Systems (ESS) interacting with stochastic sources of generation. The initial motivation came from the study of the adoption of renewables for electricity, and how to better harness the power of sources that are inherently oscillatory in power output. The benefits of ESS in a dynamic optimization go beyond the amount of renewable energy actually dispatched in the system. The current debate and probable adoption of electrified transportation will most likely increase the pressure on local distribution systems. However, the availability of distributed energy will also increase, in the form of energy storage, once the interface between the grid and the power sources in the vehicles is developed in a mass scale.10aenergy storage10aoptimal power flow (OPF)10areliability and markets10arenewables10aRM12-0041 aLamadrid, Alberto, J1 aMount, Timothy, D.1 aShoemaker, Christine uhttps://certs.lbl.gov/publications/dynamic-optimization-management01595nas a2200229 4500008003900000020002200039245006100061210006000122260003500182300001000217520086800227653001301095653000901108653003901117653001401156653002901170653002701199653002901226100001301255700002401268856007301292 2009 d a978-1-4244-4241-600aRisk-based optimal power flow and system operation state0 aRiskbased optimal power flow and system operation state aCalgary, CanadabIEEEc07/2009 a1 - 63 aIn this paper, the risk-based optimal power flow is proposed, which minimizes the economic cost considering the system reliability, and a refined system operation state is provided to clarify this approach. In order to obtain better economic benefit than traditional security-constrained optimal power flow, the corrective optimal power flow is used in this work. The reliability is represented by the risk index, which captures the expected impact to the system. This problem is solved by Benders decomposition. The specific designed Benders subproblem will assure that no collapse or cascading overload occurs for the corrective optimal power flow problem. The approach auto-steers the dispatch between different risk level according to the probability and consequence of the upcoming contingency events. Case studies with a six-bus system are presented.

10aAA09-00110aAARD10aAutomatic Switchable Network (ASN)10aload flow10aoptimal power flow (OPF)10apower system economics10apower system reliability1 aLi, Yuan1 aMcCalley, James, D. uhttps://certs.lbl.gov/publications/risk-based-optimal-power-flow-and01290nas a2200205 4500008003900000020002200039245008400061210006900145260003900214300001000253520057600263653002400839653002900863653002800892653001300920100002300933700003200956700002300988856007301011 2008 d a978-1-4244-1905-000aAn advanced security constrained OPF that produces correct market-based pricing0 aadvanced security constrained OPF that produces correct marketba aPittsburgh, PA, USAbIEEEc07/2008 a1 - 63 aSecurity constrained optimal power flow programs are important tools for ensuring correct dispatch of supply while respecting the many constraints imposed by the delivery system. In addition to getting the dispatch right, locational prices must be calculated with equal precision in order to infuse market participants with the proper incentives for operation and investment. In this paper we discuss a co-optimization framework in which contingencies, ancillary services, and network constraints are correctly accounted for in determining both dispatch and price.

10aelectricity markets10aoptimal power flow (OPF)10areliability and markets10aRM07-0021 aThomas, Robert, J.1 aMurillo-Sanchez, Carlos, E.1 aZimmerman, Ray, D. uhttps://certs.lbl.gov/publications/advanced-security-constrained-opf01168nas a2200241 4500008003900000022001400039245007800053210006900131260001200200300001600212490000700228520042200235653001300657653000900670653003900679653002900718653002600747653002600773653001800799100001400817700002400831856007100855 2007 d a0885-895000aRisk-Based Security and Economy Tradeoff Analysis for Real-Time Operation0 aRiskBased Security and Economy Tradeoff Analysis for RealTime Op c11/2007 a2287 - 22880 v223 aThis letter describes a new perspective on balancing system security level with cost for real-time operation. Security level is quantified using risk, which provides that security may be optimized. A risk-based multiple-objective (RBMO) model, considering security and economy together, is compared with the traditional security-constrained OPF (SCOPF) model. A six-bus test system is used to show the merits of RBMO.10aAA09-00110aAARD10aAutomatic Switchable Network (ASN)10aoptimal power flow (OPF)10aPower system modeling10apower system security10arisk analysis1 aXiao, Fei1 aMcCalley, James, D. uhttps://certs.lbl.gov/publications/risk-based-security-and-economy