A Server Placement Algorithm for Reducing Risk and Improving Power Utilization in Data Centers

As the power demand in data centers is increasing,the power capacity of the power supply system has become an essential resource to be optimized.Although many data centers use power oversubscription to make full use of the power capacity,there are unavoidable power supply risks associated with it.Therefore,how to improve the data center power capacity utilization while ensuring power supply security has become an important issue.To solve this problem,we first define it and propose a risk evaluation metric called Weighted Power Supply Risk(WPSRisk).Then,a method,named Hybrid Genetic Algorithm with Ant Colony System(HGAACS),is proposed to improve power capacity utilization and reduce power supply risks by optimizing the server placement in the power supply system.HGAACS uses historical power data of each server to find a better placement solution by population iteration.HGAACS possesses not only the remarkable local search ability of Ant Colony System(ACS),but also enhances the global search capability by incorporating genetic operators from Genetic Algorithm(GA).To verify the performance of HGAACS,we experimentally compare it with five other placement algorithms.The experimental results show that HGAACS can perform better than other algorithms in both improving power utilization and reducing the riskof powersupply system.

An Optimized Oxygen System Scheduling With Electricity Cost Consideration in Steel Industry

As an essential energy resource in steel industry, oxygen is widely utilized in many production procedures. With different demands of the oxygen amount, a gap between the generation and consumption always occurs. Therefore, its related optimization and scheduling work along with the electricity cost to fill the gap has a great impact on daily production and efficient energy utilization in steel plant. Considering an oxygen system in a steel plant in China, a nonlinear programming model for oxygen system scheduling is proposed in this study, which concerns not only the practical characteristics of the energy pipeline network, but also the electricity cost acquired by a fitting regression modeling between the load of air separation units U+0028 ASU U+0029 and its corresponding electricity consumption. A set of constraints is formulated for restricting the practical adjusting capacity and filling the imbalance gap of oxygen. To solve the proposed scheduling model with electricity cost consideration, a particle swarm optimization U+0028 PSO U+0029 algorithm is then adopted. To verify the effectiveness of the proposed approach, a large number of experiments employing the real data from this plant are carried out, both for the fitting regression and the scheduling optimization phases. And the results demonstrate that such a practice-based solution successfully resolves the oxygen scheduling problem and simultaneously minimizes the electricity cost, which will be beneficial for the enterprise. © 2017 Chinese Association of Automation.

Power Utility Maximization in an Exponential Levy Model Without a Risk-free Asset

We consider the problem of maximizing the expected power utility fromterminal wealth in a market where logarithmic securities prices follow a Lévy process. By Girsanovstheorem, we give explicit solutions for power utility of undiscounted terminal wealth in terms ofthe Lévy-Khintchine triplet.

Tie-line Power Flow Control Method for Gridconnected Microgrids with SMES Based on Optimization and Fuzzy Logic

In an active distribution grid,renewable energy sources(RESs)such as photovoltaic(PV)and energy storage systems(e.g.,superconducting magnetic energy storage(SMES))can be combined with consumers to compose a microgrid(MG).The high penetration of PV causes high fluctuations of tie-line power flow and highly affects power system operations.This can lead to several technical problems such as voltage fluctuations and excessive power losses.In this paper,a fuzzy logic control based SMES method(FSM)and an optimized fuzzy logic control based SMES method(OFSM)are proposed for minimizing the tie-line power flow.Consequently,the fluctuations and transmission power losses are decreased.In FSM,SMES is used with a robust fuzzy logic controller(FLC)for controlling the tie-line power flow.An optimization model is employed in OFSM to simultaneously optimize the input parameters of the FLC and the reactive power of the voltage source converter(VSC)of SMES.The objective function of minimizing the tieline power flow is incorporated into the optimization model.Particle swarm optimization(PSO)algorithm is utilized to solve the optimization problem while the constraints of the utility power grid,VSC,and SMES are considered.The simulation results demonstrate the effectiveness and robustness of the proposed methods.

A cubic triboelectric generator as a self-powered orientation sensor

Recently, triboelectric generator(TEG) has attracted a lot of attention due to its high output voltage and low-cost fabrication process. Here, a novel cubic TEG box is designed, which has separated electrodes on different surfaces. Thanks to the specially designed structure, it can scavenge vibration energy from all directions. Firstly the device is investigated through finite element method(FEM) simulation. Then the device is evaluated by experiments. The measuremental results show that this device can generate an amount of 25 n C charge during once shake by charging a 10 n F capacitor. Besides, an output voltage about 100 V is obtained, which is able to directly light up several light-emitting diodes(LEDs) simultaneously. At last, the device is utilized as a self-powered orientation sensor, which shows explicit directivity. This work extends the applications of TEG for ambient vibration energy harvesting techniques and the self-powered orientation sensor.

Experimental study on the new type of electrical storage heater based on flat micro-heat pipe arrays

A new type of electrical storage heater that utilizes latent heat storage and flat micro-heat pipe arrays （FMHPAs） was developed. The thermal characteristics of the heater were tested through experimentation. The structure and operating principle of the storage heater were expounded. Three rows of FMHPAs were applied （three rows with five assemblies each） with a mass of 28 kg of phase change material （PCM） in the heat storage tank. Electric power was supplied to the PCM in the range of 0.2-2.04 kW, and air was used as heat transfer fluid, with the volume flow rate ranging from 40-120 m3/h. The inlet temperature was in the range of 15-24~C. The effects of heating power, air volume flow rate, and inlet temperature were investigated. The electrical storage heater exhibited efficiencies of 97% and 87% with 1.98 and 1.30 kW of power during charging and discharging, respectively. Application of the proposed storage heater can transfer electricity from peak periods to off-peak periods, and the excess energy generated by wind farms can be stored as heat and released when needed. Good economic and environmental benefits can be obtained.

Homotopy Analysis Method for Portfolio Optimization Problem Under the 3/2 Model

This paper considers the Merton portfolio optimization problem for an investor that aims at maximizing the expected power utility of the terminal wealth and intermediate consumption.Applying the homotopy analysis method,an analytical solution for value function as well as optimal strategy under the 3/2 model is derived,respectively.Compared with the existing explicit solutions for Merton problem under the 3/2 model,the formulas provide certain parameters with less requirement since the homotopy analysis method does not depend on the existence of small parameters in the equation.Finally,numerical examples are examined with the approach,and the proposed solution provides more accurate approximation as the number of terms in infinite series increases.

Non-blocking four-port optical router based on thermooptic silicon microrings

By using silicon-on-insulator(SOI) platform, 12 channel waveguides, and four parallel-coupling one-microring resonator routing elements, a non-blocking four-port optical router is proposed. Structure design and optimization are performed on the routing elements at 1 550 nm. At drop state with a power consumption of 0 m W, the insertion loss of the drop port is less than 1.12 d B, and the crosstalk between the two output ports is less than-28 d B; at through state with a power consumption of 22 m W, the insertion loss of the through port is less than 0.45 d B, and the crosstalk between the two output ports is below-21 d B. Routing topology and function are demonstrated for the four-port optical router. The router can work at nine non-blocking routing states using the thermo-optic(TO) effect of silicon for tuning the resonance of each switching element. Detailed characterizations are presented, including output spectrum, insertion loss, and crosstalk. According to the analysis on all the data links of the router, the insertion loss is within the range of 0.13—3.36 d B, and the crosstalk is less than-19.46 d B. The router can meet the need of large-scale optical network-on-chip(ONo C).

Theoretical analysis and experimental verification of a cost-effective chromatic dispersion monitoring method in a 40-Gb/s optical fiber communication system

A cost-effective technique for in-service chromatic dispersion monitoring in a 40-Gb/s optical communication system is proposed. Microwave devices are adopted to detect the electrical power of a specific frequency band. A simplified theoretical model is proposed and discussed focusing on the relationship between electrical power and chromatic dispersion at different frequency bands. The dynamic monitoring of chromatic dispersion is achieved using devices such as PIN detector, microwave amplifier, narrow-band microwave filter, and electrical power detector. The maximum detectable chromatic dispersion is 130 ps/nm and a resolution of 5.2 ps/nm/dB has been achieved in the frequency band centered at 12 GHz.