01593nas a2200193 4500008003900000022001400039245007800053210006900131260001200200300001100212520098400223653001001207653002701217653002801244653001301272100002201285700002101307856007101328 2015 d a0885-895000aCapacity Controlled Demand Side Management: A Stochastic Pricing Analysis0 aCapacity Controlled Demand Side Management A Stochastic Pricing c03/2015 a1 - 123 aWe consider a novel paradigm for demand side management, assuming that an aggregator communicates with a household only at the meter, imposing a capacity constraint, i.e., a restriction on the total power consumption level within a given time frame. Consumers are then responsible to adjust the set-points of the individual household devices accordingly to meet the imposed constraint. We formulate the problem as a stochastic household energy management program, with stochasticity arising due to local photovoltaic generation. We show how a demand bidding curve for capacity increments can be constructed as a by-product of the developed problem and provide a rigorous pricing analysis that results in a probabilistic “shadow” price envelope. To evaluate the efficacy of the proposed approach, we compare it with an idealized real-time market price set-up and show how our analysis can provide guidelines to consumers when selecting a service contract for load curtailment.10aCERTS10ademand-side management10areliability and markets10aRM12-0011 aMargellos, Kostas1 aOren, Shmuel, S. uhttps://certs.lbl.gov/publications/capacity-controlled-demand-side01916nas a2200217 4500008003900000022001400039245009800053210006900151260001200220300001600232490000700248520121000255653002801465653001301493100002101506700002401527700002501551700003001576700002101606856007101627 2010 d a0885-895000aCo-Optimization of Generation Unit Commitment and Transmission Switching With N-1 Reliability0 aCoOptimization of Generation Unit Commitment and Transmission Sw c05/2010 a1052 - 10630 v253 aCurrently, there is a national push for a smarter electric grid, one that is more controllable and flexible. The full control of transmission assets are not currently built into electric network optimization models. Optimal transmission switching is a straightforward way to leverage grid controllability: to make better use of the existing system and meet growing demand with existing infrastructure. Previous papers have shown that optimizing the network topology improves the dispatch of electrical networks. Such optimal topology dispatch can be categorized as a smart grid application where there is a co-optimization of both generators and transmission topology. In this paper we present a co-optimization formulation of the generation unit commitment and transmission switching problem while ensuring N-1 reliability. We show that the optimal topology of the network can vary from hour to hour. We also show that optimizing the topology can change the optimal unit commitment schedule. This problem is large and computationally complex even for medium sized systems. We present decomposition and computational approaches to solving this problem. Results are presented for the IEEE RTS 96 test case.10areliability and markets10aRM08-0011 aHedman, Kory, W.1 aFerris, Michael, C.1 aO'Neill, Richard, P.1 aFisher, Emily, Bartholome1 aOren, Shmuel, S. uhttps://certs.lbl.gov/publications/co-optimization-generation-unit01531nas a2200205 4500008003900000020002200039245005100061210005100112260003600163300001000199520088100209653002101090653002401111653002801135653002701163653001301190100002601203700002101229856007501250 2008 d a978-1-4244-2850-200aCoupling Wind Generators with Deferrable Loads0 aCoupling Wind Generators with Deferrable Loads aAtlanta, GA, USAbIEEEc11/2008 a1 - 73 aWe explore the possibility of directly coupling deferrable loads with wind generators in order to mitigate the variability and randomness of wind power generation. Loads engage in a contractual agreement of deferring their demand for power by a fixed amount of time and wind generators optimally allocate available wind power with the objective of minimizing the cost of unscheduled and variable supply. We simulate the performance of the proposed coupling in a market environment and we demonstrate its compatibility with existing technology, grid operations and economic incentives. The results indicate that the combination of existing deregulated power markets and demand side flexibility could support large scale integration of wind power without significant impacts on grid operations and without the requirement for prohibitive investments in backup generation.

10adeferrable loads10aelectricity markets10areliability and markets10arenewables integration10aRM10-0011 aPapavasiliou, Anthony1 aOren, Shmuel, S. uhttps://certs.lbl.gov/publications/coupling-wind-generators-deferrable01645nas a2200253 4500008003900000245013200039210006900171260001200240300000700252520076300259653006901022653002301091653001101114653002601125100002001151700002201171700002501193700001401218700002501232700001801257700001801275700002101293856007701314 2003 d00aCalifornia's Electricity System of the Future: Scenario Analysis in Support of Public-Interest Transmission System R&D Planning0 aCalifornias Electricity System of the Future Scenario Analysis i c04/2003 a613 aThe California Energy Commission directed the Consortium for Electric Reliability Technology Solutions to analyze possible future scenarios for the California electricity system and assess transmission research and development (R&D) needs, with special emphasis on prioritizing *public interest* R&D needs, using criteria developed by the Energy Commission. The scenarios analyzed in this report are not predictions, nor do they express policy preferences of the project participants or the Energy Commission. The public-interest R&D needs that are identified as a result of the analysis are one input that will be considered by the Energy Commission's Public Interest Energy Research staff in preparing a transmission R&D plan.

10aconsortium for electric reliability technology solutions (certs)10aGrid of the Future10aRT-00410atransmission planning1 aEto, Joseph, H.1 aStovall, John, P.1 aBudhraja, Vikram, S.1 aDyer, Jim1 aGoldman, Charles, A.1 aMarnay, Chris1 aGross, George1 aOren, Shmuel, S. uhttps://certs.lbl.gov/publications/californias-electricity-system-future