Effective utilization of renewable energy sources and efficient management of electric energy are essential for any developing countries like India. This can be envisioned through the implementation of concepts of smart grid (SG). One of the key requisites for SG implementation is that the grid should be completely observable. Renovation of conventional Indian power grid to a SG necessitates incorporation of the phasor measurement units (PMUs) in the present power grid measurement and monitoring system. Since the cost of PMU is high and any bus containing a PMU makes the neighboring connected buses observable, optimal placement of PMUs is very important for complete observability of the grid. This paper proposes optimal redundant geographical locations in the northern, eastern and north-eastern regions of Indian power grid for PMU placement. The PMUs installed in these geographical locations will make the grid completely observable and maintain the observability under the conditions of failure of some PMUs or branch outages. Integer linear programming has been used for finding the optimal PMU locations. The results proposed in this paper can be a stepping stone for revamping the Indian power grid to a SG ensuring complete observability during different contingency conditions.
This paper presents an efficient interactive differential evolution (IDE) to solve the multi-objective security environmental/economic dispatch (SEED) problem considering multi shunt flexible AC transmission system (FACTS) devices. Two sub problems are proposed.The first one is related to the active power planning to minimize the combined total fuel cost and emissions, while the second is a reactive power planning (RPP) using multi shunt FACTS device based static VAR compensator (SVC) installed at specified buses to make fine corrections to the voltage deviation, voltage phase profiles and reactive power violation. The migration operation inspired from biogeography-based optimization (BBO) algorithm is newly introduced in the proposed approach, thereby effectively exploring and exploiting promising regions in a space search by creating dynamically new efficient partitions. This new mechanism based migration between individuals from different subsystems makes the initial partitions to react more by changing experiences. To validate the robustness of the proposed approach, the proposed algorithm is tested on the Algerian 59-bus electrical network and on a large system, 40 generating units considering valve-point loading effect. Comparison of the results with recent global optimization methods show the superiority of the proposed IDE approach and confirm its potential for solving practical optimal power flow in terms of solution quality and convergence characteristics.
In power system studies, congestion in transmission lines and utilization of flexible alternating current transmission system (FACTS) devices are closely associated. These devices are very important due to their role in power delivery system enhancement. It is to be noted that the generation companies can exercise their market power which depends on the line flows, line constraints, generators’ location and its share to the individual loads. This issue cannot be overlooked as it creates monopoliness which is against the deregulated market policy. The objective of this paper is to study the impact of market power when FACTS devices like thyristor controlled switching capacitor (TCSC) and thyristor controlled phase angle regulator (TCPAR) are used under steady state operation. The market power is determined using nodal must-run share (NMRS) index for the standard IEEE 14-bus system with and without the above FACTS devices and the results obtained are compared. All the above simulations are conducted in a MATLAB 7.9-R2009b environment.
In this paper, three intelligent approaches were proposed, applied to direct torque control (DTC) of induction motor drive to replace conventional hysteresis comparators and selection table, namely fuzzy logic, artificial neural network and adaptive neuro-fuzzy inference system (ANFIS). The simulated results obtained demonstrate the feasibility of the adaptive network-based fuzzy inference system based direct torque control (ANFIS-DTC). Compared with the classical direct torque control, fuzzy logic based direct torque control (FL-DTC), and neural networks based direct torque control (NN-DTC), the proposed ANFIS-based scheme optimizes the electromagnetic torque and stator flux ripples, and incurs much shorter execution times and hence the errors caused by control time delays are minimized. The validity of the proposed methods is confirmed by simulation results.
In a competitive and deregulated power scenario, the utilities try to maintain their real electric power generation in balance with the load demand, which creates a need for the precise real time generation scheduling (GS). In this paper, the GS problem is solved to perform the unit commitment (UC) based on frequency prediction by using artificial neural network (ANN) with the objective to minimize the overall system cost of the state utility. The introduction of availability-based tariff (ABT) signifies the importance of frequency in GS. Under-prediction or over-prediction will result in an unnecessary commitment of generating units or buying power from central generating units at a higher cost. Therefore, an accurate frequency prediction is the first step toward optimal GS. The dependency of frequency on various parameters such as actual generation, load demand, wind power and power deficit has been considered in this paper. The proposed technique provides a reliable solution for the input parameter different from the one presented in the training data. The performance of the frequency predictor model has been evaluated based on the absolute percentage error (APE) and the mean absolute percentage error (MAPE). The proposed predicted frequency sensitive GS model is applied to the system of Indian state of Tamilnadu, which reduces the overall system cost of the state utility by keeping off the dearer units selected based on the predicted frequency.
There is currently a growing demand for developing efficient techniques for cooling integrated electronic devices with ever increasing heat generation power. To better tackle the high-density heat dissipation difficulty within the limited space, this paper is dedicated to clarify the heat transfer behaviors of the liquid metal flowing in mini-channel exchangers with different geometric configurations. A series of comparative experiments using liquid metal alloy Ga68%In20%Sn12% as coolant were conducted under prescribed mass flow rates in three kinds of heat exchangers with varied geometric sizes. Meanwhile, numerical simulations for the heat exchangers under the same working conditions were also performed which well interpreted the experimental measurements. The simulated heat sources were all cooled down by these three heat dissipation apparatuses and the exchanger with the smallest channel width was found to have the largest mean heat transfer coefficient at all conditions due to its much larger heat transfer area. Further, the present work has also developed a correlation equation for characterizing the Nusselt number depending on Peclet number, which is applicable to the low Peclet number case with constant heat flux in the hydrodynamically developed and thermally developing region in the rectangular channel. This study is expected to provide valuable reference for designing future liquid metal based mini-channel heat exchanger.
Unit commitment (UC) is one of the most important aspect of power generation in the world today. Though, there is no method to find the exact optimized solution, there exists several meta-heuristic algorithms to determine the close to exact solution. This paper proposes a novel solution to effectively determine UC and generation cost using the technique of invasive weed optimization (IWO). The existing technique distributes the load demand among all the generating units. The method proposed here utilizes the output of UC obtained by using the Lagrangian relaxation (LR) method and calculates the required generation from only the plants that are ON discarding the OFF generator units and thereby giving a faster and more accurate response. Moreover, the results show the comparison between the LR-particle swarm optimization (PSO) and LR-IWO, and prove that the cost of generation for a 4 unit, 8 hour schedule is much less in the case of IWO when compared to PSO.
This paper described the production of karanja biodiesel using response surface methodology (RSM) and genetic algorithm (GA). The optimum combination of reaction variables were analyzed for maximizing the biodiesel yield. The yield obtained by the RSM was 65% whereas the predicted value was 70%. The mathematical regression model proposed from the RSM was coupled with the GA. By using this technique, 90% of the yield was obtained at a molar ratio of 38, a reaction time of 8 hours, a reaction temperature of 40 oC, a catalyst concentration of 2% oil, and a mixing speed of 707 r/min. The yield produced was closer to the predicted value of 94.2093%. Hence, 25% of the improvement in the biodiesel yield was reported. Moreover the different properties of karanja biodiesel were found closer to the American Society for Testing & Materials (ASTM) standard of biodiesel.
The collision frequency function for aerosol particles has already been calculated for the free molecule regime and for the continuum range. The present work, taking into account the influence of internal force fields such as magnetic force, electric force and molecular forces, created by particles themselves, recalculated the collision frequency in the case of particles much smaller than the mean free path of the gas (free molecule regime). Attractive forces increase naturally the collision frequency, while repulsive forces decrease it. The calculation was performed for all types of central forces deriving from a potential, including Coulomb forces and Van der Waals forces.
“Partial pressure” in humid air is a question very much concerned by scientists and no satisfactory answer has been found to date. This paper proposes a novel method to obtain the “partial pressures” of the water vapor and dry air in humid air. The results obtained by the proposed method are quite different from that obtained by Dalton’s partial pressure law. The fundamental behaviors of water vapor and dry air are studied in depth in wide pressure and temperature ranges. Semi-permeable membrane models are proposed and applied for both saturated and unsaturated humid air. “Improvement factors” are developed to quantitatively describe the magnitude of the interaction between dissimilar molecules. One discovery is that the “partial pressure” of the water vapor in saturated humid air equals Ps, rather than (f·Ps) which was formerly believed. The other is that the interaction between dissimilar molecules may be omitted when temperature is above “cutting-off temperature” for unsaturated humid air. This paper satisfactorily answers the quest of “partial pressures” in humid air from a new perspective.
This paper investigated the variation of building heating energy consumption caused by global warming in Tianjin, China. Based on the hourly historical and monthly projected future (B1/A1B emissions scenarios) meteorological data, the variation of those relevant meteorological parameters was first analyzed. A TRNSYS simulation model for a reference building was introduced to investigate historical variation of office building energy consumption. The results showed that the 10-year-average heating energy consumption of 2001–2010 had reduced by 16.1% compared to that of 1961–1970. By conducting principal component analysis and regression analysis, future variation of building heating load was studied. For B1/A1B emissions scenarios, the multi-year-average heating load was found to decrease by 9.7% (18.1%)/10.2% (22.7%) compared to that of 1971–2010 by 2011–2050 (2051–2100).
If the heat of road surface can be stored in summer, the road surface temperature will be decreased to prevent permanent deformation of pavement. Besides, if the heat stored is released, it can supply heat for buildings or raise the road surface temperature for snow melting in winter. A road-solar energy system was built in this study, and the heat transfer mechanism and effect of the system were analyzed according to the monitored solar radiant heat, the solar energy absorbed by road and the heat stored by soil. The results showed that the road surface temperature was mainly affected by solar radiation, but the effect is hysteretic in nature. The temperature of the solar road surface was 3°C–6°C lower than that of the ordinary road surface. The temperature of the solar road along the vertical direction was 2°C–5°C lower than that of the ordinary road. The temperature difference increased as the distance to the heat transfer tubes decreased. The average solar collector efficiency of the system was 14.4%, and the average solar absorptivity of road surface was 36%.
In estimating emissions reductions brought about by renewables in China, much of existing research assumes that renewables displace coal power. In this paper, this assumption is challenged and the potential environmental effects of photovoltaic (PV) power in North-west China are reevaluated when the marginal generator actually being displaced is taken into account. The annual PV power generation in the North-west Grid is estimated, in this paper, to be as high as 17900 GW·h in 2015, roughly equaling to the output of 1.5 nuclear power plants in the US today. The total associated emission reduction in 2015 will at most be 0.36 percent of SO2 and 0.25 percent of NOx emissions from their 2010 levels in China. Further, PV power may render no emissions reduction at all if it displaces hydropower, which is often used to meet peak demand in the North-west Grid in China. These results imply that a more cost-effective area of focus in the short-term may be on desulfurization and denitrification technologies for coal plants.