Capacity payments and the pricing of reliability in competitive generation markets

In restructured electric power industries around the world, power pool designers have enabled generators to earn revenues consisting of energy and capacity payments. This paper discusses uses and abuses of capacity payments, and links provision of these payments to the issue of pricing reliability. A general formula for determining the ideal capacity price in a generation supply system is presented and the theoretical basis discussed. Methods of achieving an ideal level of system reliability through price-setting of capacity payments (in more regulated markets) and through price discovery (in more competitive markets) are contrasted. The paper concludes with market design recommendations that could better realize customer preference for reliability at prices customers are willing to pay.published_or_final_versio

Designing B-ISDN network topologies using the genetic algorithm

In this paper, the topology design of B-ISDN networks is addressed. We model the topological planning as a non-linear mixed-integer programming problem. The genetic algorithm, an effective optimization method, is applied to this problem. Since the randomness of the genetic algorithm cannot guarantee the biconnectivity requirement in the topologies generated by the genetic algorithm, we propose an algorithm to make all topologies at least biconnected while increasing the overall cost of the topologies the least. The result for a 20-node test case is presented in the paper and it is shown that the algorithm we propose has a very good convergence property.published_or_final_versio

Parallel and distributed state estimation

The need in recent years for higher frequency in state estimation execution covering larger supervised networks has led to the investigation of faster and numerically more stable state estimation algorithms. However, technical developments in distributed Energy Management Systems, based on fast data communication networks, open up the possibility of parallel or distributed state estimation implementation. In this paper, this possibility is exploited to derive a solution methodology based on conventional state estimation algorithms and a coupling constraints optimization technique. Numerical experiments show suitable performance of the proposed method with regard to estimation accuracy, convergence robustness and computational efficiency. The results of these experiments also indicate the decoupled nature of the state estimation problem.published_or_final_versio

Dynamic bandwidth allocation using infinitesimal perturbation analysis

Advances in network management and switching technologies make dynamic bandwidth allocation of logical networks built on top of a physical network possible. Previous proposed dynamic bandwidth allocation algorithms are based on simplified network model. The analytical model is valid only under restrictive assumptions. Infinitesimal Perturbation Analysis, a technique which estimates the gradients of the functions in discrete event dynamic systems by passively observing the system, is used to estimate delay sensitivities under general traffic patterns. A new dynamic bandwidth allocation algorithm using on-line sensitivity estimation is proposed. Simulation results show that the approach further improves network performance. Implementation of the proposed algorithm in operational networks is also discussed.published_or_final_versio

Pricing for system security

Security in power systems refers to the ability of the system to withstand imminent disturbances (contingencies). Maintaining security is an issue which must be addressed at the system level. It is shown in this paper, however, that it is possible to maintain system security in an operating environment with many participants (power companies, independent power producers, co-generators, consumers) each attempting to optimize their own benefit, through pricing incentives and appropriate information exchange. Rates for power generation/consumption and for an offer to use during a contingency, as well as information on the probability distribution of contingency need for each participant, are derived so that individual optimization will lead to the socially optimal solution in which system security is optimized and the aggregate benefit is maximized.published_or_final_versio

Bifurcation, chaos, and voltage collapse in power systems

A model of a power system with load dynamics is studied by investigating qualitative changes in its behavior as the reactive power demand at a load bus is increased. In addition to the saddle node bifurcation often associated with voltage collapse, the system exhibits sub- and supercritical Hopf bifurcations, cyclic fold bifurcation, and period doubling bifurcation. Cascades of period doubling bifurcations terminate in chaotic invariant sets. The presence of these new bifurcations motivates a reexamination of the saddle-node bifurcation as the boundary of the feasible set of power injections.published_or_final_versio

Decentralized congestion management for multilateral transactions based on optimal resource allocation

This paper proposes a decentralized model for dc load flow based congestion management for the forward markets via Optimal Resource Allocation (ORA). The available thermal capacities of possible congested transmission lines are considered as commonly shared resources for all bilateral and multilateral transactions in the market. In our model, each transaction maximizes its profit under the limits of transmission line capacities allocated by the ISO. The ISO searches the optimal allocation of line capacities to each transaction. Finally, the same market efficiency (social welfare) as centralized optimization can be reached. The ORA-based decentralized approach is more suitable for power market environment, since it always keeps the intermediate solution feasible during the iterations and does not require each transaction to submit their private and sensitive information. The mathematical model, computation procedure and relevant proof are presented. The computer test results from the IEEE 30 bus system illustrate the effectiveness of proposed approach. © 2007 IEEE.published_or_final_versio

Safety, Immunogenicity, and Efficacy of Intramuscular and Oral Delivery of ERA-G333 Recombinant Rabies Virus Vaccine to Big Brown Bats (\u3ci\u3eEptesicus fuscus\u3c/i\u3e)

Attenuated strains of rabies virus (RABV) have been used for oral vaccination of wild carnivores in Europe and North America. However, some RABV vaccines caused clinical rabies in target animals. To improve the safety of attenuated RABV as an oral vaccine for field use, strategies using selection of escape mutants under monoclonal antibody neutralization pressure and reverse genetics–defined mutations have been used. We tested the safety, immunogenicity, and efficacy of one RABV construct, ERA-g333, developed with reverse genetics by intramuscular (IM) or oral (PO) routes in big brown bats (Eptesicus fuscus). Twenty-five bats received 5×106 mouse intracerebral median lethal doses (MICLD50) of ERA-g333 by IM route, 10 received 5×106 MICLD50 of ERA-g333 by PO route, and 22 bats served as unvaccinated controls. Twenty-one days after vaccination, 44 bats were infected by IM route with 102.9 MICLD50 of E. fuscus RABV. We report both the immunogenicity and efficacy of ERA-g333 delivered by the IM route; no induction of humoral immunity was detected in bats vaccinated by the PO route. Two subsets of bats vaccinated IM (n=5) and PO (n=3) were not challenged, and none developed clinical rabies from ERA-g333. Scarce reports exist on the evaluation of oral rabies vaccines in insectivorous bats, although the strategy evaluated here may be feasible for future application to these important RABV reservoirs

Inferring cell cycle feedback regulation from gene expression data

AbstractFeedback control is an important regulatory process in biological systems, which confers robustness against external and internal disturbances. Genes involved in feedback structures are therefore likely to have a major role in regulating cellular processes.Here we rely on a dynamic Bayesian network approach to identify feedback loops in cell cycle regulation. We analyzed the transcriptional profile of the cell cycle in HeLa cancer cells and identified a feedback loop structure composed of 10 genes. In silico analyses showed that these genes hold important roles in system’s dynamics. The results of published experimental assays confirmed the central role of 8 of the identified feedback loop genes in cell cycle regulation.In conclusion, we provide a novel approach to identify critical genes for the dynamics of biological processes. This may lead to the identification of therapeutic targets in diseases that involve perturbations of these dynamics

Multi‐Channel Lanthanide Nanocomposites for Customized Synergistic Treatment of Orthotopic Multi‐Tumor Cases

Simultaneous photothermal ablation of multiple tumors is limited by unpredictable photo-induced apoptosis, caused by individual intratumoral differences. Here, a multi-channel lanthanide nanocomposite was used to achieve tailored synergistic treatment of multiple subcutaneous orthotopic tumors under non-uniform whole-body infrared irradiation prescription. The nanocomposite reduces intratumoral glutathione by simultaneously activating the fluorescence and photothermal channels. The fluorescence provides individual information on different tumors, allowing customized prescriptions to be made. This enables optimal induction of hyperthermia and dosage of chemo drugs, to ensure treatment efficacy, while avoiding overtherapy. With an accessional therapeutic laser system, customized synergistic treatment of subcutaneous orthotopic cancer cases with multiple tumors is possible with both high efficacy and minimized side effects