Ashu Verma

Angle Dispersive X-ray Diffraction Beamline on Indus-2 Synchrotron Radiation Source: Commissioning and First Results

Angle dispersive x-ray diffraction (ADXRD) is a basic non destructive tool for the determination of crystal structure. Energy tunability and high flux are added advantages in using synchrotron radiation (SR) source for ADXRD technique. We have installed an ADXRD beamline (BL-12) on Indus-2, the Indian synchrotron source. Indus-2 is a 2.5GeV, 300mA SR source. The beamline consists of a Si (311) crystal pair based double crystal monochromator with bendable focusing optics. The experimental station consists of a six circle diffractometer with scintillation detector and an image plate area detector. The beamline has been used for wide range of experiments like powder and single crystal diffraction; grazing incidence diffraction, x-ray absorption near edge structure, Anomalous XRD, high pressure XRD etc. The beamline is being utilized by users from Indian universities and research institutions.

Transmission network expansion planning with adaptive particle swarm optimization

Transmission network expansion planning is a very important problem to power system. The problem is very complex due to its mixed integer, non linear, non convex nature. Meta heuristic techniques are known to provide good/ optimal solutions for such type of combinatorial problems. In light of above, this paper presents an adaptive particle swarm optimization algorithm for transmission network expansion planning Results for IEEE 24 bus system are taken to confirm the potential of the proposed algorithm.

Binary Grey Wolf Optimizer for large scale unit commitment problem

Abstract The unit commitment problem belongs to the class of complex large scale, hard bound and constrained optimization problem involving operational planning of power system generation assets. This paper presents a heuristic binary approach to solve unit commitment problem (UC). The proposed approach applies Binary Grey Wolf Optimizer (BGWO) to determine the commitment schedule of UC problem. The grey wolf optimizer belongs to the class of bio-inspired heuristic optimization approaches and mimics the hierarchical and hunting principles of grey wolves. The binarization of GWO is owing to the UC problem characteristic binary/discrete search space. The binary string representation of BGWO is analogous to the commitment and de-committed status of thermal units constrained by minimum up/down times. Two models of Binary Grey Wolf Optimizer are presented to solve UC problem. The first approach includes upfront binarization of wolf update process towards the global best solution (s) followed by crossover operation. While, the second approach estimates continuous valued update of wolves towards global best solution(s) followed by sigmoid transformation. The Lambda-Iteration method to solve the convex economic load dispatch (ELD) problem. The constraint handling is carried out using the heuristic adjustment procedure. The BGWO models are experimented extensively using various well known illustrations from literature. In addition, the numerical experiments are also carried out for different circumstances of power system operation. The solution quality of BGWO are compared to existing classical as well as heuristic approaches to solve UC problem. The simulation results demonstrate the superior performance of BGWO in solving UC problem for small, medium and large scale systems successfully compared to other well established heuristic and binary approaches.

Obesity and thyrotropinemia.

ObjectiveTo study the relation between body mass index (BMI) and TSH in euthyroid and subclinical hypothyroid obese children and compared serum TSH level among obese and overweight children.MethodsFifty consecutive children (aged 2–18 yr) presenting for obesity were studied. All cases with TSH > 10, low T3/T4, organic and syndromic obesity were excluded. Patients were divided into Group 1: Overweight (n=20) (BMI between 85th to 95th centile) and Group 2: Obesity (n=30) (BMI > 95th centile). Fisher’s exact test, Mann-Whitney U test and Pearson’s correlation were used for statistical analysis. P value < 0.05 was considered significant.ResultsElevated TSH level (between 4.5–10 mIU/L) with normal T3, T4 was seen in 4/20 overweight and 9/30 of obese children (P=0.5219). The mean TSH was comparable in both the groups (3.22 ± 3.1 mIU/L vs. 3.63 ± 2.2 mIU/L, P=0.3491). Overall TSH showed no correlation with BMI (r= 0.0014, P=0.9924).ConclusionThe preliminary data did not show any relation between severity of obesity and TSH level. Further large scale data from population are required to confirm these findings.

Small signal stability analysis of grid connected distributed PV and wind energy system

Reliability and sustainability are the real problems of todays complex power systems. These challenges are met by increasing the renewable generation. With increase in penetration of renewable resources, mostly solar and wind generation, power systems are expected to experience changes in operational and dynamic characteristic. This work investigates the impact of penetration of distributed solar photovoltaic generation and DFIG based wind generation on small signal stability of power systems. In this paper, the eigenvalue analysis of proposed grid connected distributed photovoltaic generation and wind energy system is carried out to allocate the different modes (local mode, inter-area mode and critical mode) of the system. The simulation results with different cases demonstrate the effectiveness of the proposed approach.

A combination of heuristic and bacteria foraging-differential evolution algorithm for transmission network expansion planning with security constraints

Transmission network expansion planning (TNEP) is an important component of power system planning. Its task is to determine the optimal set of transmission lines to be constructed such that the cost of expansion plan is minimum and no network constraints are violated during the planning horizon. The problem is very complex due to large number of options to be analysed and the discrete nature of the optimization variables. Hence, more efficient and robust techniques are required to solve this complex problem. This paper presents a new hybrid approach for TNEP with security constraints, where first the solution is obtained very quickly with a new promising heuristic method, which is used as a starting point for the proposed metaheuristic approach known as bacteria foraging differential evolution algorithm (BF-DEA). The heuristic method used for generating the initial solution is based on a DC power flow based compensation approach to simulate single/double line modifications arising out of a candidate line addition and an outage of other line. This method can be used to quickly obtain a suboptimal/optimal transmission network expansion plan. One of the difficulties with metaheuristic methods is the possibility of premature convergence to a nonoptimal solution. The worst part is that in many situations we do not even know as to how close/far the optimal solution obtained is from the global optimum one. The plan obtained with the heuristic method provides an upper bound on the solution obtained with BF-DEA. The hybrid method thus ensures that BF-DEA will provide a solution which is much closer to the global optimum. Results for two sample systems demonstrate the potential of the proposed scheme.

Comparative study of IHS and BF-DE algorithm for optimal DG placement

With the introduction of renewable based distributed generation, optimal siting and sizing of Distributed Generators (DGs) has become an important problem. This paper attempts a comparative study of two meta-heuristic algorithms named as Improved Harmony Search (IHS) and bacterial foraging-differential evolution (BF-DE), for optimal DG placement. The effect of various levels of DG penetration is also studied. Results for four test systems 10 bus, 15 bus, 33 bus and 69 bus are presented.

Study the effect of system parameters on controller gains for discrete AGC of hydro-thermal system

This paper investigates the effect of system parameters on optimum controller gains for discrete data automatic generation control of an interconnected power system. The optimum gains of the system have been analyzed for different values of sampling periods in discrete mode of operation. The effect of different loading conditions on the optimum gains is also investigated. As we know that load varies widely throughout the day. The optimum gains calculated for the nominal loading may not be optimum at other loading condition. Therefore the system has been analyzed for different loading conditions. The load variation of 30-100% has been considered for the investigation. This paper also deals with the proper selection of speed regulation parameter R for the design of speed governor. The hydro-thermal system has been taken for investigation. The dynamic responses are obtained for 1% load perturbation in thermal area system. The Matlab/simulink software is used for the simulation work.

An efficient approach to tune modern power system stabilizers using harmony search

A multiband power system stabilizer tuning method, in which objective is to enhance the damping of the rotor oscillations and system stability is proposed in this paper. This tuning approach is based on an efficient search algorithm known as harmony search algorithm. Robust design problem of PSS4B is considered as an optimization problem with nonlinear simulation based objective function. A single machine infinite bus (SMIB) system is evaluated under large range of loading conditions and disturbances for performance investigation of the proposed design. In order to demonstrate the effectiveness of designed PSS4B stabilizers, time domain simulations are carried out for SMIB system. Superiority of the proposed PSS4B design is proved by comparative study of transient responses with existing model of PSS4B.

Reactive power planning with uncertainties in load/generation specifications

Reactive power planning is an important problem in power systems. It determines the optimal location and size of reactive power resources such that the overall cost of expansion plan is lesser and the system is secure. Uncertainties are always present in any data. These uncertainties are even more pronounced in power system due to its geographical spread, size and complexity. Most of the literature deals with reactive power planning considering certainty in data. This paper presents an approach for reactive power planning considering uncertainties in load/generation specifications. Results for two sample test systems have been obtained to demonstrate the importance of the problem.