Sourav Paul

Transient Stability Constrained Optimal Power Flow Using Teaching Learning-Based Optimization

Transient stability constrained optimal power flow (TSC-OPF) is a non-linear optimization problem which is not easy to deal directly because of its huge dimension. In order to solve the TSC-OPF problem efficiently, a relatively new optimization technique named teaching learning based optimization (TLBO) is proposed in this paper. TLBO algorithm simulates the teaching–learning phenomenon of a classroom to solve multi-dimensional, linear and nonlinear problems with appreciable efficiency. Like other nature-inspired algorithms, TLBO is also a population-based method and uses a population of solutions to proceed to the global solution. The authors have explained in detail, the basic philosophy of this method. In this paper, the authors deal with the comparison of other optimization problems with TLBO in solving TSC-OPF problem. Case studies on IEEE 30-bus system WSCC 3-generator, 9-bus system and New England 10-generator, 39-bus system indicate that the proposed TLBO approach is much more computationally efficient than the other popular methods and is promising to solve TSC-OPF problem.

Automatic Generation Control of Interconnected Power System using Cuckoo Optimization Algorithm

Automatic generation control (AGC) is added in power system to ensure constancy in frequency and tie-line power of an interconnected multi-area power system. In this article, proportional integral (PI) controlled based AGC of two-area hydrothermal system is solved by cuckoo optimization algorithm (COA). It is one of the most powerful stochastic real parameter optimization in current use. The design objective is to improve the dynamic performance of the interconnected system following a disturbance. System performance is examined considering 1% step load perturbation in thermal area with generation rate constraints. The results are compared with BBO, GA and DE to show the effectiveness of the proposed method. Computed results shows that the proposed method effectively improve the performance of the objective function with corresponding minimization of the overshoot, undershoot and settling time to reach steady state.

Optimal Design of Power System Stabilizer Using a Novel Evolutionary Algorithm

Inthisarticle,anOppositionalDifferentialsearchalgorithm(ODSA)iscomprehensivelydeveloped andsuccessfullyappliedfortheoptimaldesignofpowersystemstabilizer(PSS)parameterswhich areaddedtotheexcitationsystemtodampenlowfrequencyoscillationasitpertainstolargepower system.Theeffectivenessoftheproposedmethodisexaminedandvalidatedonasinglemachine infinitebus(SMIB)usingtheHeffron-Phillipsmodel.Themostimportantadvantageoftheproposed methodisasitreachestowardtheoptimalsolutionwithouttheoptimaltuningofinputparameters oftheODSAalgorithm.Inordertoverifytheeffectiveness,thesimulationwasmadeforawide rangeofloadingconditions.ThesimulationresultsoftheproposedODSAarecomparedwiththose obtainedbyothertechniquesavailableintherecentliteraturetodemonstratethefeasibilityofthe proposedalgorithm. KEywORDS Damping Ratio, Differential Search Algorithm, Eigen-Value Analysis, Evolutionary Algorithm, Oppositional Based Learning, Power System Stabilizer, Single Machine Infinite Bus

Optimal design of power system stabiliser using hybrid biogeography-based predator-prey optimisation technique

Biogeography-based optimisation (BBO) is a relatively new bio-inspired and population-based optimisation algorithm. It is proved itself a worthy optimisation technique to solve various nonlinear optimisation problem. In this paper, the concept of predator-prey optimisation is incorporated in BBO to increase the diversity of the population. The proposed biogeography-based predator-prey optimisation (BPPO) technique is implemented on both single-input and dual-input power system stabilisers (PSSs). The effectiveness of the proposed algorithm is demonstrated on single machine infinite bus (SMIB) system using four different types of single and dual input PSS. From the simulation study, it is revealed that the transient performance of dual-input PSS is better than single-input PSS. The performance of the proposed algorithm is evaluated over a wide range of operating condition and the simulation results of the proposed method are compared with those obtained by BBO, seeker optimisation algorithm (SOA) and bacteria foraging optimisation (BFO). The results confirm the potential and effectiveness of the proposed BPPO algorithm over SOA, BFO and BBO.

Optimal Design of Single Machine Power System Stabilizer using Chemical Reaction Optimization Technique

PSSs are added to excitation systems to enhance the damping during low frequency oscillations. The non-linear model of a machine is linearized at different operating points. Chemical Reaction optimization (CRO), a new population based search algorithm is been proposed in this paper to damp the power system low-frequency oscillations and enhance power system stability. Computation results demonstrate that the proposed algorithm is effective in damping low frequency oscillations as well as improving system dynamic stability. The performance of the proposed algorithm is evaluated for different loading conditions. In addition, the proposed algorithm is more effective and provides superior performance when compared other population based optimization algorithms like differential evolution (DE) and particle swarm optimization (PSO).

Accumulation of Cu at different concentration of tea plant (camellia saneness (L.) O. Kountze)

Tea is the most popular beverage in the world. Tea is considered a beneficial drink as it contains many essential nutrients. But the intake of heavy metals even in a small amount causes adverse action in human health along with the plants. The heavy metals are present in the nutrient media itself which are required for plant growth, other important sources are pesticides and fertilizers used in the field for better production. In the present study the tea cultivars (S3A3) were collected from the Rosekandy tea estate, Silchar, Assam and were analyzed for the accumulation of Cu at different level on the different organs of the plants. The accumulation of Cu had a strong positive correlation with the Cu concentration. The order of deposition of Cu are in following manner roots>leaves>stems with the exposure of treatment days. From the present study we have concluded that even low amount of deposition of Cu at higher concentration causes adverse affect by retarding the growth of a plant with many other physiological characters. And this may lead to the adverse action of biological characters.