Y V Krishna Reddy’s scientific contributions

Open Access | Rapid and quality publishing Research Article | Volume 12, Issue 3 | Pages 926-933 | e-ISSN: 2347-470X 926 Website: www.ijeer.forexjournal.co.in Economic load dispatch of Thermal-Solar-Wind system using ░ ABSTRACT-The growing demand for electrical energy, coupled with the uneven distribution of natural resources, necessitates the integration of power plants. Coordinating the operation of interconnected generating units is crucial to meet the fluctuating load demand efficiently. This research focuses on the Economic Load Dispatch (ELD) problem in hybrid power systems that incorporate solar thermal and wind energy. Renewable energy resources, such as wind and solar thermal energy, depend on atmospheric conditions like wind speed, solar radiation, and temperature. This study addresses the ELD problem using a Modified Grey Wolf Optimization (MGWO) approach to obtain the most optimal solution for generator fuel costs. The Grey Wolf Optimization (GWO) approach, inspired by natural processes, is utilized but may exhibit both exploratory and exploitative behavior. To enhance its performance, we propose a novel version called MGWO, integrating memory, evolutionary operators, and a stochastic local search approach. The suggested MGWO approach is applied to two distinct test systems comprising 13 and 26 units, respectively, to solve the ELD with variable load requirements. Comparative analyses with other strategies demonstrate the effectiveness of MGWO in addressing the ELD problem. This modification enhances the GWO method, making it more robust and efficient for optimizing ELD in hybrid power systems.

The growing demand for electrical energy, coupled with the uneven distribution of natural resources, necessitates the integration of power plants. Coordinating the operation of interconnected generating units is crucial to meet the fluctuating load demand efficiently. This research focuses on the Economic Load Dispatch (ELD) problem in hybrid power systems that incorporate solar thermal and wind energy. Renewable energy resources, such as wind and solar thermal energy, depend on atmospheric conditions like wind speed, solar radiation, and temperature. This study addresses the ELD problem using a Modified Grey Wolf Optimization (MGWO) approach to obtain the most optimal solution for generator fuel costs. The Grey Wolf Optimization (GWO) approach, inspired by natural processes, is utilized but may exhibit both exploratory and exploitative behavior. To enhance its performance, we propose a novel version called MGWO, integrating memory, evolutionary operators, and a stochastic local search approach. The suggested MGWO approach is applied to two distinct test systems comprising 13 and 26 units, respectively, to solve the ELD with variable load requirements. Comparative analyses with other strategies demonstrate the effectiveness of MGWO in addressing the ELD problem. This modification enhances the GWO method, making it more robust and efficient for optimizing ELD in hybrid power systems.

Now a day’s power demand keep on increasing due to rapid changes occurs in power industry. For that purpose establishing new generating is costlier rather than effectively utilize the available generating stations. In order to properly planning of power system generation sharing Economic Dispatch (ED) plays vital role. In this paper, Equilibrium Optimizer (EO) is used to solve the ED problem with effect of valve-point, prohibited operating zones (POZs), ramp rate up/down limits and pollution like practical constraints. In order to analyze the capability of the EO algorithm, the algorithm is applied to four test systems with 6 unit systems and the results are compared with other optimization algorithms. The comparative results proven that EO is better optimization technique to solve ED problem with practical constraints.

Economical load dispatch (ELD) and combined economic emission dispatch (CEED) problems are solved using optimization approaches. In order to handle ELD and CEED problems, a novel metaheuristic optimization technique based on human intelligence called the mountaineering team based optimization (MTBO) algorithm is projected in this paper. The MTBO method implemented based on the human cooperation and social behaviour taking into account the usual occurrences to reach a mountain top, this represents the finest overall solution. The projected MTBO method is utilised to address optimisation problems. This approach involves analysing the stages of regular and climbing movements, which are based on the leader's experience, the obstacles encountered during the ascent, and the risk of being trapped in local optimum performance. Additionally, the group's coordination and social support are considered to safeguard members from common catastrophes. To evaluate the efficiency of the suggested method, considered six cases for the ELD problem and four cases for a CEED problem. Along with the MTBO, other optimization techniques like flower pollination algorithm (FPA), ant lion optimization (ALO) and grey wolf optimization (GWO) methods are used to solve ELD and CEED problem. The MTBO method outperforms the competition in terms of robustness, ease of implementation, effective optimization performance for a optimal global solutions.

A bus bar in an electrical power distribution refers to bulky segments of copper or aluminum that carry out electricity within a switchboard, distribution panel and substation. In this task, bus bar can be protected from the over current condition. Mechanical instruments disappointments have numerous causes and one of the primary causes is over burden. The crucial of the distribution transformer is anticipated to work at assured particular current, if that current passing through that feeder is more than the rated then instantaneously the feeder may damaged because of over load, through this projected work we are departing to defend the bus bar from heavy load condition. In this work, more loads are applied to the circuit to produce high current. So that the current will be increased. At whatever point the over current happened the circuit will be tripped. Here, one relay is utilized which will control through our microcontroller to trip the circuit. Whenever over load is occurred relay will trip the whole circuit and buzzer will on control through our microcontroller to indicate over load. Whenever over load occurs micro controller automatically triggers the load to OFF and data will alert through IoT.

Abstract— This manuscript explores the novel Ant Lion Optimization (ALO) to resolve the load dispatch problem optimally. The primary role of Optimal Economic Load Dispatch (OELD) is to obtain an efficient and economical operation of a power system network. The main aim of performing the OELD is for minimizing the fuel cost of the real power generation when the losses are neglected. Ant lion optimization (ALO) is a narrative nature-inspired algorithm and apes the tracking mechanism of ant lions in life. The random walk of ants, building traps, entrapment of ants in traps, catching preys, and re-building traps are the five main steps involved in the hunting process. The principal objective of OELD is to minimize total cost of generation while honoring effective constraints of available generation resources. The anticipated ALO technique is utilized on three and six unit test system to various load demands for solving the load dispatch problem economically. A statistical result illustrates that the anticipated method has lowest fuel cost and superior in quality of solution than other optimization techniques accounted in most latest literature.