In this paper we present a new value proposition for load flexibility. This value is derived through enabling a congestion free dispatch, which brings economic benefits to the market participants (loads and generators), subject to certain conditions on the network. If participant classes are considered as collectives, then no class of participants is economically disadvantaged. We show that load flexibility increases the opportunity for congestion free dispatch. The economic implications of this new paradigm are studied using a simple two bus example.

10areliability and markets10aRM11-0061 aMather, Jonathan1 aBaeyens, Enrique1 aPoolla, Kameshwar1 aVaraiya, Pravin uhttps://certs.lbl.gov/publications/real-value-load-flexibility01545nas a2200277 4500008003900000022001400039245005000053210004900103260001200152300001600164490000600180520074400186653001000930653003900940653001800979653001700997653002801014653002701042653001301069100002301082700002301105700002501128700002201153700002001175856007201195 2013 d a1949-305300aReal-Time Scheduling of Distributed Resources0 aRealTime Scheduling of Distributed Resources c12/2013 a2122 - 21300 v43 aWe develop and analyze real-time scheduling algorithms for coordinated aggregation of deferrable loads and storage. These distributed resources offer flexibility that can enable the integration of renewable generation by reducing reserve costs. We present three scheduling policies: earliest deadline first (EDF), least laxity first (LLF), and receding horizon control (RHC). We offer a novel cost metric for RHC-based scheduling that explicitly accounts for reserve costs. We study the performance of these algorithms in the metrics of reserve energy and capacity through simulation studies. We conclude that the benefits of coordinated aggregation can be realized from modest levels of both deferrable load participation and flexibility.10aCERTS10adistributed energy resources (der)10aload modeling10aoptimization10areliability and markets10arenewables integration10aRM11-0061 aSubramanian, Anand1 aGarcia, Manuel, J.1 aCallaway, Duncan, S.1 aPoolla, Kameshwar1 aVaraiya, Pravin uhttps://certs.lbl.gov/publications/real-time-scheduling-distributed01902nas a2200241 4500008003900000022001300039245005900052210005800111260001200169300001400181490000700195520121500202653001001417653002801427653002701455653002001482653001301502100001901515700001801534700002001552700001401572856007401586 2013 d a0142061500aRisk-limiting dispatch for integrating renewable power0 aRisklimiting dispatch for integrating renewable power c01/2013 a615 - 6280 v443 aRisk-limiting dispatch or RLD is formulated as the optimal solution to a multi-stage, stochastic decision problem. At each stage, the system operator (SO) purchases forward energy and reserve capacity over a block or interval of time. The blocks get shorter as operations approach real time. Each decision is based on the most recent available information, including demand, renewable power, weather forecasts. The accumulated energy blocks must at each time t match the net demand D(t) = L(t) − W(t). The load L and renewable power W are both random processes. The expected cost of a dispatch is the sum of the costs of the energy and reserve capacity and the penalty or risk from mismatch between net demand and energy supply. The paper derives computable ‘closed-form’ formulas for RLD. Numerical examples demonstrate that the minimum expected cost can be substantially reduced by recognizing that risk from current decisions can be mitigated by future decisions; by additional intra-day energy and reserve capacity markets; and by better forecasts. These reductions are quantified and can be used to explore changes in the SO’s decision structure, forecasting technology, and renewable penetration.10aCERTS10areliability and markets10arenewables integration10areserve markets10aRM11-0061 aRajagopal, Ram1 aBitar, Eilyan1 aVaraiya, Pravin1 aWu, Felix uhttps://certs.lbl.gov/publications/risk-limiting-dispatch-integrating02310nas a2200253 4500008003900000020002200039245005400061210005300115260003200168300001600200520149400216653003901710653000901749653002701758653001301785653003801798100002301836700002301859700003601882700002501918700002201943700002001965856007101985 2012 d a978-1-4577-1095-700aReal-time scheduling of deferrable electric loads0 aRealtime scheduling of deferrable electric loads aMontreal, QCbIEEEc06/2012 a3643 - 36503 aWe consider a collection of distributed energy resources [DERs] such as electric vehicles and thermostatically controlled loads. These resources are flexible: they require delivery of a certain total energy over a specified service interval. This flexibility can facilitate the integration of renewable generation by absorbing variability, and reducing the reserve capacity and reserve energy requirements. We first model the energy needs of these resources as tasks, parameterized by arrival time, departure time, energy requirement, and maximum allowable servicing power. We consider the problem of servicing these resources by allocating available power using real-time scheduling policies. The available generation consists of a mix of renewable energy [from utility-scale wind-farms or distributed rooftop photovoltaics], and load-following reserves. Reserve capacity is purchased in advance, but reserve energy use must be scheduled in real-time to meet the energy requirements of the resources. We show that there does not exist a causal optimal scheduling policy that respects servicing power constraints. We then present three heuristic causal scheduling policies: Earliest Deadline First [EDF], Least Laxity First [LLF], and Receding Horizon Control [RHC]. We show that EDF is optimal in the absence of power constraints. We explore, via simulation studies, the performance of these three scheduling policies in the metrics of required reserve energy and reserve capacity.

10adistributed energy resources (der)10aPEVs10arenewables integration10aRM11-00610aThermostatically controlled loads1 aSubramanian, Anand1 aGarcia, Manuel, J.1 aDominguez-Garcia, Alejandro, D.1 aCallaway, Duncan, S.1 aPoolla, Kameshwar1 aVaraiya, Pravin uhttps://certs.lbl.gov/publications/real-time-scheduling-deferrable01487nas a2200241 4500008003900000020002200039245004100061210004100102260003200143300001600175520079400191653001000985653002800995653002301023653002701046653001301073653001501086100001901101700001801120700001401138700002001152856007301172 2012 d a978-1-4577-1095-700aRisk limiting dispatch of wind power0 aRisk limiting dispatch of wind power aMontreal, QCbIEEEc06/2012 a4417 - 44223 aIntegrating wind and solar power into the grid requires dispatching various types of reserve generation to compensate for the randomness of renewable power. The dispatch is usually determined by a system operator (SO) or an aggregator who `firms' variable energy by bundling it with conventional power. The optimal dispatch is formulated as the solution to a stochastic control problem and shown to have a closed form that can be quickly computed. Different objectives and risk constraints can be included in the formulation and trade-offs can be evaluated. In particular one can quantify the influence of sequential forecasts on the total integration cost and the choice of dispatched generation. When the forecast error is Gaussian, the optimal dispatch policy can be precomputed.

10aCERTS10areliability and markets10areserve generation10arisk-limiting dispatch10aRM11-00610awind power1 aRajagopal, Ram1 aBitar, Eilyan1 aWu, Felix1 aVaraiya, Pravin uhttps://certs.lbl.gov/publications/risk-limiting-dispatch-wind-power01309nas a2200229 4500008003900000245006300039210006300102260001200165300000700177520057900184653006900763653002300832653002800855653001000883100001800893700001600911700001900927700001900946700002100965700002000986856007301006 1999 d00aReal Time Security Monitoring and Control of Power Systems0 aReal Time Security Monitoring and Control of Power Systems c12/1999 a483 aThis white paper outlines the scope of issues, challenges and opportunities in the area of real-time security monitoring and control (RTSMC) of power systems in the restructured electricity industry. The counterpart of power system reliability in real-time operations is *security* – the ability of the power system to withstand contingencies. This White Paper is part of a set of six papers on reliability aspects of the electric power system prepared for the U.S. Department of Energy by the Consortium of Electric Reliability Technology Solutions (CERTS).