Showing papers by "Shahin Nazarian published in 2012"

Concurrent optimization of consumer's electrical energy bill and producer's power generation cost under a dynamic pricing model

Abstract: Demand response is a key element of the smart grid technologies. This is a particularly interesting problem with the use of dynamic energy pricing schemes which incentivize electricity consumers to consume electricity more prudently in order to minimize their electric bill. On the other hand optimizing the number and production time of power generation facilities is a key challenge. In this paper, three models are presented for consumers, utility companies, and a third-part arbiter to optimize the cost to the parties individually and in combination. Our models have high quality and exhibit superior performance, by realistic consideration of non-cooperative energy buyers and sellers and getting real-time feedback from their interactions. Simulation results show that the energy consumption distribution becomes very stable during the day utilizing our models, while consumers and utility companies pay lower cost.

Profit maximization for utility companies in an oligopolistic energy market with dynamic prices

Abstract: Dynamic pricing and demand response are the key elements of the smart grid technologies. Utility companies can incentivize electricity customers to schedule their power hungry tasks during off-peak times of the day whereas demand response manages customers' electricity consumption in response to supply conditions or market prices. The reaction of consumers to dynamic prices creates a feedback system in the smart grid that motivates the utility companies to model the consumers' behavior in the process of determining the price. Letting the consumers select their provider of choice among multiple utility companies, may be modeled as a non-cooperative game. In this paper, we consider the process of determining dynamic electricity prices for electricity based on a modified Bertrand Competition Model of consumer behavior and in view of competition among multiple non-cooperative utility companies in an oligopolistic energy market. The proposed method maximizes the conservative estimate on the profit for each utility company. Results also demonstrate the effectiveness of the oligopolistic electrical market in decreasing the electricity cost to consumers.

Theory of redundancy for logic circuits to maximize yield/area

Abstract: The down scaling of feature sizes and higher process variations in future CMOS nano-technologies are anticipated to introduce higher manufacturing anomalies. On the other hand designs are getting more complicated due to more innovative applications where they need higher numbers of transistors. These phenomena significantly reduce the functional yield. Redundancy has been used for a long time in regular structures such as memory to tolerate defects; however, for typical irregular logic circuits this would be very challenging. In this paper we introduce a theory that justifies the necessity of using redundancy at sub-chip level of granularity to maximize yield/area (number of healthy dies) for future technologies with higher defect rates. In addition, redundancy at finer levels of granularity, aggravates the overheads of interconnect (steering logics, i.e., forks, joins and switches) such as yield, area, and testing overheads. These overheads limit the level of granularity for logic replication. Current yield estimators are generally pessimistic for interconnects because they do not take circuit and logic context into consideration, and/or they assume all defects are killer-defects, i.e., always result in unacceptable circuit behavior. In this paper we propose a CAD tool to compute the functional yield of the configurable and testable steering logics using (i) actual layout geometries, and (ii) factory data related to density and size of opens (missing metal), shorts (extra metal) and open vias. The experimental results show that our theory of redundancy considering the overheads of steering logics can improve the yield/area by 2.8 times for a real highly-defected circuit (OpenSparc T2 core).