Ranking of hydropower projects based on sustainability criteria in India using multicriteria decision making methods

Assessment of hydropower projects with respect to sustainability criteria is a multidimensional and complex issue. It requires considering technical, environmental, and social parameters instead of purely economic ones in decision making for energy planning. The flexibility to consider several criteria and objectives simultaneously leads to the use of multicriteria decision making (MCDM) methods which are well accepted in the field of energy planning. This paper aims at applying MCDM methods in facilitating the decision makers to select the most sustainable hydropower projects in the Indian region by making real and logical choices based on eight important criteria selected from the literature that are compatible with sustainable development. To comprehensively rank hydropower projects three MCDM methods are applied i.e., the technique for order of preference by similarity to ideal solution (TOPSIS), preference ranking organization method for enrichment evaluations (PROMETHEE II), and elimination and choice translating reality (ELECTRE III). Analytic hierarchy process (AHP) is used to calculate the weights of criteria. All three methods are well adapted for sustainability assessment and ranked Sharavathi (A9), Bhakra (A2), and Upper Indravati (A13) to be the most sustainable hydropower projects in India under the selected criteria. The study will be helpful in sustainable energy planning of hydropower projects with similar geographical conditions

Voltage stability maximization based optimal network reconfiguration in distribution networks using integrated particle swarm optimization for marine power applications

1949-1956This paper addresses a novel method to optimize network reconfiguration problem in radial distribution network considering voltage stability maximization and power loss reduction without violating the system constraints. In nature inspired population based standard particle swarm optimization (PSO) technique, the flight path of current particle depends upon global best and particle best position. However, if the particle flies nearby to either of these positions, the guiding rule highly decreases and even vanishes. To resolve this problem and to find the global best position, integrated particle swarm optimization (IPSO) is utilized for finding the optimal reconfiguration in the radial distribution network. The performance and effectiveness of the method are validated through IEEE 33 and 69 buses distribution networks and is compared with other optimization techniques published in recent literature for optimizing network reconfiguration problem. The simulated results simulate the fact that to attain the global optima, IPSO requires less numbers of iterations as compared to the simple PSO. The present method facilitates the optimization of modern electric power systems by empowering them with voltage stability

Constant Voltage Operation of Self Excited Induction Generator using Optimization Tools

Abstract-In this paper MATLAB/ TOOLS such as Genetic Algorithm (GA), Pattern Search (PS) and Quasi-Newton optimization tools have been used to predict the behavior of self excited induction generator (SEIG). GA is used to predict the value of excitation capacitance to maintain the rated terminal voltage for any value of load on the machine terminals. Further analysis is extended to predict the behavior of this generator with voltage fluctuations across the load

COMPARISON OF NODAL ADMITTANCE AND LOOP IMPEDANCE METHODS FOR SELF EXCITED INDUCTION GENERATOR

ABSTRACT The steady-state analysis of self-excited induction generator (SEIG) is done by either of the two methods i.e. nodal admittance and loop impedance. In this paper the mathematical modeling and iterative processes of the two methods have been compared in order to predict the values of the capacitive reactance required for a self-excitation at different operating conditions of load, speed, and frequency. The performance characteristics of SEIG have been studied in Matlab environment