A coordinated economic dispatch method for multi-area power systems is proposed. Choosing boundary phase angles as coupling variables, the proposed method exploits the structure of critical regions in local problems defined by active and inactive constraints. For a fixed boundary state given by the coordinator, local operators compute the coefficients of critical regions containing the boundary state and the optimal value functions then communicate them to the coordinator who in turn optimizes the boundary state to minimize the overall cost. By iterating between local operators and the coordinator, the proposed algorithm converges to the global optimal solution in finite steps, and it requires limited information sharing.

10aRM13-0021 aGuo, Ye1 aTong, Lang1 aWu, Wenchuan1 aZhang, Boming1 aSun, Hongbin uhttps://certs.lbl.gov/publications/coordinated-multi-area-economic01458nas a2200145 4500008004100000020002200041245009900063210006900162260001200231520097100243100001601214700001501230700001501245856005201260 2017 eng d a978-0-9981331-0-200aProbabilistic Forecasting and Simulation of Electricity Markets via Online Dictionary Learning0 aProbabilistic Forecasting and Simulation of Electricity Markets c01/20173 aThe problem of probabilistic forecasting and online simulation of real-time electricity market with stochastic generation and demand is considered. By exploiting the parametric structure of the direct current optimal power flow, a new technique based on online dictionary learning (ODL) is proposed. The ODL approach incorporates real-time measurements and historical traces to produce forecasts of joint and marginal probability distributions of future locational marginal prices, power flows, and dispatch levels, conditional on the system state at the time of forecasting. Compared with standard Monte Carlo simulation techniques, the ODL approach offers several orders of magnitude improvement in computation time, making it feasible for online forecasting of market operations. Numerical simulations on large and moderate size power systems illustrate its performance and complexity features and its potential as a tool for system operators.

1 aDeng, Weisi1 aJi, Yuting1 aTong, Lang uhttp://aisel.aisnet.org/hicss-50/es/markets/10/01123nas a2200145 4500008003900000245005700039210005600096260003500152300001000187520066300197653001300860100001500873700001500888856007400903 2016 d00aMulti-proxy interchange scheduling under uncertainty0 aMultiproxy interchange scheduling under uncertainty aBoston, MA, USAbIEEEc07/2016 a1 - 53 aThe problem of inter-regional interchange scheduling using a multiple proxy bus representation is considered. A new scheduling technique is proposed for the multi-proxy bus system based on a stochastic optimization that captures uncertainty in renewable generation and stochastic load. In particular, the proposed algorithm iteratively optimizes the interchange across multiple proxy buses using a vectorized notion of demand and supply functions. The proposed technique leverages the operator's capability of forecasting locational marginal prices (LMPs) and obtains the optimal interchange schedule directly without iterations between operators.

10aRM13-0021 aJi, Yuting1 aTong, Lang uhttps://certs.lbl.gov/publications/multi-proxy-interchange-scheduling01394nas a2200157 4500008003900000022001400039245007000053210006900123260001200192520089100204653001301095100001501108700002301123700001501146856007501161 2016 d a0885-895000aProbabilistic Forecasting of Real-Time LMP and Network Congestion0 aProbabilistic Forecasting of RealTime LMP and Network Congestion c07/20163 aThe 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 associated with multiparametric programs offline, the online computational 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.

10aRM13-0021 aJi, Yuting1 aThomas, Robert, J.1 aTong, Lang uhttps://certs.lbl.gov/publications/probabilistic-forecasting-real-time01181nas a2200169 4500008003900000022001400039245007400053210006900127260001200196300001000208520065800218653001300876100001500889700001900904700001500923856007300938 2016 d a0885-895000aStochastic Interchange Scheduling in the Real-Time Electricity Market0 aStochastic Interchange Scheduling in the RealTime Electricity Ma c08/2016 a1 - 13 aThe problem of inter-regional interchange schedul- ing in the presence of stochastic generation and load is consid- ered. An interchange scheduling technique based on a two-stage stochastic minimization of expected operating cost is proposed. Because directly solving the stochastic optimization is intractable, an equivalent problem that maximizes the expected social welfare is formulated. The proposed technique leverages the operator’s capability of forecasting locational marginal prices and obtains the optimal interchange schedule without iterations among op- erators. Several extensions of the proposed technique are also discussed.

10aRM13-0021 aJi, Yuting1 aZheng, Tongxin1 aTong, Lang uhttps://certs.lbl.gov/publications/stochastic-interchange-scheduling01319nas a2200181 4500008003900000245007600039210006900115260002900184520065000213653001000863653003200873653002800905653001300933100001500946700002300961700001500984856013800999 2015 d00aProbabilistic Forecast of Real-Time LMP via Multiparametric Programming0 aProbabilistic Forecast of RealTime LMP via Multiparametric Progr aKauai, HIbIEEEc01/20153 aThe problem of short-term probabilistic forecast of real-time locational marginal price (LMP) is considered. A new forecast technique is proposed based on a multiparametric programming formulation that partitions the uncertainty parameter space into critical regions from which the conditional probability mass function of the real-time LMP is estimated using Monte Carlo techniques. The proposed methodology incorporates uncertainty models such as load and stochastic generation forecasts and system contingency models. With the use of offline computation of multiparametric linear programming, online computation cost is significantly reduced.10aCERTS10alocational marginal pricing10areliability and markets10aRM13-0021 aJi, Yuting1 aThomas, Robert, J.1 aTong, Lang uhttp://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=7070121&refinements%3D4260156971%26filter%3DAND%28p_IS_Number%3A7069647%2901532nas a2200145 4500008003900000245008200039210006900121260003500190300001000225520103700235653001301272100001501285700001501300856007101315 2015 d00aRenewable in distribution networks: Centralized vs. decentralized integration0 aRenewable in distribution networks Centralized vs decentralized aDenver, CO, USAbIEEEc07/2015 a1 - 53 aThe problem of integrating renewable generation in a distribution network is considered under two integration models: a centralized utility-based model in which the utility owns and operates the renewable generation as part of its portfolio of energy resources, and a decentralized consumer-based model in which each consumer owns and operates the renewable generation and is allowed to sell surplus electricity back to the utility in a net-metering setting. Interactions between the utility and its consumers are captured by the retail price of electricity set by the utility. Under the day ahead hourly pricing scheme, the Pareto frontier of the tradeoff between consumer surplus and retail profit is characterized under the two models. It is shown that, depending on the level of regulated utility profit, the consumer-based decentralized integration may lead to lower consumer surplus than that when no renewable is integrated. On the other hand, the utility based centralized integration always improve consumer surplus.

10aRM13-0021 aJia, Liyan1 aTong, Lang uhttps://certs.lbl.gov/publications/renewable-distribution-networks01002nas a2200145 4500008003900000245007700039210006900116260003500185300001000220520050900230653001300739100001500752700001500767856007400782 2015 d00aStochastic coordinated transaction scheduling via probabilistic forecast0 aStochastic coordinated transaction scheduling via probabilistic aDenver, CO, USAbIEEEc07/2015 a1 - 53 aThe problem of real-time interchange scheduling between two independently operated regions is considered. An optimal scheduling scheme is proposed by maximizing the expected economic surplus based on Coordinated Transaction Scheduling (CTS) mechanism. The proposed technique incorporates probabilistic forecasts of renewable generation to optimize the interchange schedule using a parametric programming formulation, from which statistical real-time generation supply offer curves are constructed.

10aRM13-0021 aJi, Yuting1 aTong, Lang uhttps://certs.lbl.gov/publications/stochastic-coordinated-transaction01288nas a2200229 4500008003900000022001400039245006600053210006500119260001200184300001400196490000700210520060600217653002400823653003200847653002800879653001300907100001500920700001600935700002300951700001500974856006900989 2014 d a0885-895000aImpact of Data Quality on Real-Time Locational Marginal Price0 aImpact of Data Quality on RealTime Locational Marginal Price c03/2014 a627 - 6360 v293 aThe problem of characterizing impacts of data quality on real-time locational marginal price (LMP) is considered. Because the real-time LMP is computed from the estimated network topology and system state, bad data that cause errors in topology processing and state estimation affect real-time LMP. It is shown that the power system state space is partitioned into price regions of convex polytopes. Under different bad data models, the worst case impacts of bad data on real-time LMP are analyzed. Numerical simulations are used to illustrate worst case performance for IEEE-14 and IEEE-118 networks.10aelectricity markets10alocational marginal pricing10areliability and markets10aRM11-0031 aJia, Liyan1 aKim, Jinsub1 aThomas, Robert, J.1 aTong, Lang uhttps://certs.lbl.gov/publications/impact-data-quality-real-time01414nas a2200217 4500008003900000245007900039210006900118260004400187300001000231520069000241653001000931653002200941653002600963653002800989653002801017100002601045700001801071700001501089700001801104856007401122 2014 d00aPiecewise affine dispatch policies for economic dispatch under uncertainty0 aPiecewise affine dispatch policies for economic dispatch under u aNational Harbor, MD, USAbIEEEc07/2014 a1 - 53 aStochastic optimization has become one of the fundamental mathematical frameworks for modeling power systems with important sources of uncertainty in the demand and supply sides. In this framework, a main challenge is to find optimal dispatch policies and settlement schemes that support a market equilibrium. In this paper, the economic dispatch under linear network constraints and resource uncertainty is revisited. Piece-wise affine continuous dispatch policies and locational prices that support a market equilibrium using a two-settlement scheme are derived. We find that the ex-post locational prices are piecewise affine continuous functions of the system uncertainties.

10aCERTS10aeconomic dispatch10aPower system modeling10areliability and markets10astochastic optimization1 aMunoz-Alvarez, Daniel1 aBitar, Eilyan1 aTong, Lang1 aWang, Jianhui uhttps://certs.lbl.gov/publications/piecewise-affine-dispatch-policies01582nas a2200205 4500008003900000245007600039210006900115260004200184300001400226520091200240653001001152653003201162653002801194653001301222100001501235700001601250700002301266700001501289856007201304 2013 d00aForecasting real-time locational marginal price: A state space approach0 aForecasting realtime locational marginal price A state space app aPacific Grove, CA, USAbIEEEc11/2013 a379 - 3833 aThe problem of forecasting the real-time locational marginal price (LMP) by a system operator is considered. A new probabilistic forecasting framework is developed based on a time in-homogeneous Markov chain representation of the realtime LMP calculation. By incorporating real-time measurements and forecasts, the proposed forecasting algorithm generates the posterior probability distribution of future locational marginal prices with forecast horizons of 6-8 hours. Such a short-term forecast provides actionable information for market participants and system operators. A Monte Carlo technique is used to estimate the posterior transition probabilities of the Markov chain, and the real-time LMP forecast is computed by the product of the estimated transition matrices. The proposed forecasting algorithm is tested on the PJM 5-bus system. Simulations show marked improvements over benchmark techniques.10aCERTS10alocational marginal pricing10areliability and markets10aRM13-0021 aJi, Yuting1 aKim, Jinsub1 aThomas, Robert, J.1 aTong, Lang uhttps://certs.lbl.gov/publications/forecasting-real-time-locational01298nas a2200157 4500008003900000245008300039210006900122260003300191300001000224520075200234653002800986653001301014100002601027700001501053856007201068 2013 d00aMitigating risk of random resources within a two-settlement electricity market0 aMitigating risk of random resources within a twosettlement elect aVancouver, BCbIEEEc07/2013 a1 - 53 aBased on a two-settlement electricity market model built within a stochastic programming framework, this paper proposes a market-clearing mechanism that allows flexible random participants - such as variable renewable energy resources and price-sensitive load-serving entities - to mitigate their risks of facing economic losses in the market. More precisely, the mechanism extends to flexible random participants the risk-mitigating capabilities that reserve capacity offers enable for firm generators (i.e., conventional generators). The proposed mechanism is based on the premise that flexible random participants should be remunerated for the partial control capabilities they may have over their resources in spite of their randomness.

10areliability and markets10aRM11-0031 aMunoz-Alvarez, Daniel1 aTong, Lang uhttps://certs.lbl.gov/publications/mitigating-risk-random-resources01596nas a2200229 4500008003900000022001400039245008100053210006900134260001200203300001600215490000700231520091000238653002701148653002601175653001201201653002801213653001301241653001501254100001601269700001501285856006601300 2013 d a0733-871600aOn Topology Attack of a Smart Grid: Undetectable Attacks and Countermeasures0 aTopology Attack of a Smart Grid Undetectable Attacks and Counter c07/2013 a1294 - 13050 v313 aCovert data attacks on the network topology of a smart grid is considered. In a so-called man-in-the-middle attack, an adversary alters data from certain meters and network switches to mislead the control center with an incorrect network topology while avoiding detections by the control center. A necessary and sufficient condition for the existence of an undetectable attack is obtained for strong adversaries who can observe all meter and network data. For weak adversaries with only local information, a heuristic method of undetectable attack is proposed. Countermeasures to prevent undetectable attacks are also considered. It is shown that undetectable attacks do not exist if a set of meters satisfying a certain branch covering property are protected. The proposed attacks are tested with IEEE 14-bus and IEEE 118-bus system, and their effect on real-time locational marginal pricing is examined.10apower system economics10apower system security10apricing10areliability and markets10aRM11-00310asmart grid1 aKim, Jinsub1 aTong, Lang uhttps://certs.lbl.gov/publications/topology-attack-smart-grid01140nas a2200217 4500008003900000020002200039245008200061210006900143260003300212300001600245520042500261653002400686653002200710653002800732653001300760653002400773100001500797700002300812700001500835856007200850 2012 d a978-1-4577-1925-700aImpacts of Malicious Data on Real-Time Price of Electricity Market Operations0 aImpacts of Malicious Data on RealTime Price of Electricity Marke aMaui, HI, USAbIEEEc01/2012 a1907 - 19143 aImpacts of malicious data data attack on the real-time electricity market are studied. It is assumed that an adversary has access to a limited number of meters and has the ability to construct data attack based on what it observes. Different observation models are considered. A geometric framework is introduced based on which upper and lower bounds on the optimal data attack are obtained and evaluated in simulations.10aelectricity markets10areal-time pricing10areliability and markets10aRM11-00310asmart grid security1 aJia, Liyan1 aThomas, Robert, J.1 aTong, Lang uhttps://certs.lbl.gov/publications/impacts-malicious-data-real-time01186nas a2200181 4500008003900000020002200039245007300061210006600134260003300200300001000233520059200243653002800835653001300863100001500876700002300891700001500914856007500929 2012 d a978-1-4673-2727-500aOn the nonlinearity effects on malicious data attack on power system0 anonlinearity effects on malicious data attack on power system aSan Diego, CAbIEEEc07/2012 a1 - 83 aThere has been a growing literature on the malicious data attack (or data injection attack) on power systems. Most existing work focuses on the DC (linear) model with linear state estimators. This paper examines the effects of nonlinearity in the power systems on the effectiveness of malicious data attack on state estimation and real-time market. It is demonstrated that attack algorithms designed for the DC model may not be effective when they are applied to nonlinear system with nonlinear state estimators. Discussion and experiments results about nonlinearity are provided.

10areliability and markets10aRM11-0031 aJia, Liyan1 aThomas, Robert, J.1 aTong, Lang uhttps://certs.lbl.gov/publications/nonlinearity-effects-malicious-data