Bidding strategies in dynamic electricity markets

In this paper the problem of developing bidding strategies for the participants of dynamic oligopolistic electricity markets is studied. Attention is given to strategic bidding of load serving entities (LSE) in these markets. We model oligopolistic electricity markets as non-linear dynamical systems and use discrete-time Nash bidding strategies. We assume a Cournot model for our game, where the LSEs decide on demand quantities and the market price is the marginal cost of producing electricity.Attention is given to a problem, where the objective functions are quadratic in the deviations of trajectories from desired trajectories and quadratic in the control deviations from the nominal controls. It is assumed that each power marketer can estimate his/her competitors' benefit function coefficients.The optimal bidding strategies are developed mathematically using dynamic game theory. We deal with games that are non-linear in the state equations. We linearize these equations for complex non-linear oligopolistic electricity multi-markets and use discrete-time Nash strategies. We show that the actual dynamic excursions from the operating point where we linearize are small so that the linearization is valid. The developed algorithm is applied to an IEEE 14-bus power system. We show that the LSEs' expected profits are higher for our method than those for other methods in the literature (F. Wen, A.K. David, Optimal bidding strategies and modeling of imperfect information among competitive generators. IEEE Transactions on Power Systems, Vol. 16, No. 1, pp.15–21, Feb. 2001.     

Evolving artificial neural network and imperialist competitive algorithm for prediction oil flow rate of the reservoir

Multiphase flow meters (MPFMs) are utilized to provide quick and accurate well test data in numerous numbers of oil production applications like those in remote or unmanned locations topside exploitations that minimize platform space and subsea applications. Flow rates of phases (oil, gas and water) are most important parameter which is detected by MPFMs. Conventional MPFM data collecting is done in long periods; because of radioactive sources usage as detector and unmanned location due to wells far distance. In this paper, based on a real case of MPFM, a new method for oil rate prediction of wells base on Fuzzy logic, Artificial Neural Networks (ANN) and Imperialist Competitive Algorithm is presented. Temperatures and pressures of lines have been set as input variable of network and oil flow rate as output. In this case a 1600 data set of 50 wells in one of the northern Persian Gulf oil fields of Iran were used to build a database. ICA-ANN can be used as a reliable alternative way without personal and environmental problems. The performance of the ICA-ANN model has also been compared with ANN model and Fuzzy model. The results prove the effectiveness, robustness and compatibility of the ICA-ANN model.     

A population game approach for dynamic resource allocation problems

We consider a water distribution system as an example of resource allocation, and investigate the use of a population game for its control. We use a game-theoretic approach based on two evolutionary dynamics, the Brown–von Neumann–Nash and the Smith dynamics. We show that the closed-loop feedback interconnection of the water distribution system and the game-theoretic-based controller has a Nash equilibrium as an asymptotically stable equilibrium point. The stability analysis is performed based on passivity concepts and the Lyapunov stability theorem. An additional control subsystem is considered for disturbance rejection. We verify the effectiveness of the method by simulations under different scenarios.     

A DASH-based HEVC multi-view video streaming system

Recent advancement in cameras and image processing technology has generated a paradigm shift from traditional 2D and 3D video to multi-view video (MVV) technology, while at the same time improving video quality and compression through standards such as high efficiency video coding (HEVC). In multi-view, cameras are placed in predetermined positions to capture the video from various views. Delivering such views with high quality over the Internet is a challenging prospect, as MVV traffic is several times larger than traditional video, since it consists of multiple video sequences, each captured from a different angle, requiring more bandwidth than single-view video to transmit MVV. In addition, the Internet is known to be prone to packet loss, delay, and bandwidth variation, which adversely affect MVV transmission. Another challenge is that end users’ devices have different capabilities in terms of computing power, display, and access link capacity, requiring MVV to be adapted to each user’s context. In this paper, we propose an HEVC multi-view system using Dynamic Adaptive Streaming over HTTP to overcome the above-mentioned challenges. Our system uses an adaptive mechanism to adjust the video bit rate to the variations of bandwidth in best effort networks. We also propose a novel scalable way for the multi-view video and depth content for 3D video in terms of the number of transmitted views. Our objective measurements show that our method of transmitting MVV content can maximize the perceptual quality of virtual views after the rendering and hence increase the user’s quality of experience.     

Mathematical models for preemptive shop scheduling problems

More than half a century has passed since Bowman and Dantzig (1959) [13] and [14] introduced their models for preemptive shop scheduling problems. A more efficient model seems to be needed to address all the aspects involved in the problem. We introduce a new Integer Linear Programming (ILP) formulation as a new method for solving the preemptive Job Shop Scheduling Problem (pJSSP). The dimension of the new model, unlike those of the existing ones, depends solely on the number of jobs and machines irrespective of processing times. The proposed model is used as an optimal, two-phase approach. In phase one, the model is solved to obtain the start and completion times of each operation on each machine. In phase two, a simple algorithm in O(mn log n) steps is used to turn these times into a complete and optimal schedule. Different preemptive flow shop problems are studied as special cases of the pJSSP while some related properties are also discussed. Finally, the higher efficiency of the proposed model is verified both theoretically and computationally through its comparison with conventional methods commonly in use.     

Purification and characterization of metallothionein and its activation of pyridoxal phosphokinase in trout (Salmo gairdneri) brain

1. Brain metallothionein was isolated and purified for the first time from rainbow trout. 2. Brain metallothionein exhibited an elution volume (Ve/Vo) of 2.0, had a molecular weight of 6762 Daltons, and contained a zinc content of 9 micrograms/mg protein. 3. Brain pyridoxal phosphokinase was isolated and assayed for the first time in rainbow trout. 4. Zinc (0.20 microM) or zinc metallothionein (6-30 microM) stimulated the activity of brain pyridoxal kinase in a linear fashion. 5. The results of these studies are interpreted to suggest that in trout brain zinc metallothionein may participate in metabolism of vitamin B6 and formation of pyridoxal phosphate, the active coenzyme.     

Trans-free Iranian vanaspati through enzymatic and chemical transesterification of triple blends of fully hydrogenated soybean,rapeseed and sunflower oils

Production of trans-free Iranian vanaspati through enzymatic and chemical transesterification of triple blends of fully hydrogenated soybean (FHSBO), rapeseed (RSO) and sunflower (SFO) oils was investigated. The slip melting point (SMP), solid fat content (SFC) at 10–40 °C and induction period of oxidation at 120 °C (IP₁₂₀) of the transesterified and initial blends were evaluated. Results indicated that all the enzymatically and chemically transesterified blends had lower SMP, SFC and IP₁₂₀ than their initial blends. No significant differences (P < 0.05) were observed between the SMP of enzymatically and chemically transesterified blends. Some enzyme treated blends had higher SFC at some temperatures than chemically transesterified ones. Enzymatically transesterified blends had higher IP₁₂₀ than those prepared by chemical transesterification. Correlation between SFC at 20 °C and saturated fatty acid (SFA) content, and between SMP and SFA of transesterified blends indicated that the SFA must be between 27.2% and 36.6% for enzymatic and 28.4% and 37.8% for chemical transesterification to obtain transesterified fats suitable for use as vanaspati.     

Behaviors of capacitive and Pirani vacuum gauges

Knowing the exact pressure of the process has a great impact on the validity of the results, product quality, energy efficiency, and in some processes, on the security of work with the system. Hence, the calibration of the barometers and the accuracy of the readings should be taken seriously. Choosing the appropriate time interval for re-calibration is done according to the extent and conditions of use, uncertainty, and the inaccuracy allowed in measurement, constructive suggestion, and some other things. Failure to pay attention to the importance of periodic calibration in vacuum gauges leads to some irreparable losses in the research project and the vacuum generator system. In this study, using McLeod's barometer, the deviation of capacitive and Pirani vacuum gauges is investigated at different time intervals in the middle vacuum range, and it is determined that the vacuum gauge faces a serious deviation from the actual calibrated amount for upper and lower ranges of middle vacuum in the same working pressure range over time.     

Application of Complex Networks Theory in Urban Traffic Network Researches

Networks and Spatial Economics - Complex network theory is a multidisciplinary research direction of complexity science which has experienced a rapid surge of interest over the last two decades....