No abstract

De-carbonization of the electric power system, reduction in greenhouse gas emissions and the enhancement of environmental security have emphasized the need for the optimal utilization of renewable/cleaner energy in power system operation. However, unpredictability and intermittency are the major barriers that limit the penetration of renewable power generation (RPG). In this context, large-scale energy storage (LSES) facilities may prove to be an effective means for mitigating the long-term volatility and vulnerability of RPG and subsequently reduce the power dependence on fossil fuel-based generation systems. Thus, the possibility of increasing the penetration of cleaner power may be achieved by simultaneously implementing LSES and an intelligent scheduling strategy so that the hybrid power system may be operated with lower power loss, more cost-effective operation, and an enhanced voltage security.Previous researchers in multiple works have demonstrated the operational analysis and optimization of hybrid configurations with and without storage in stand-alone, islanded and remote operations. In contrast, attempts have been made in this work to incorporate, analyse and validate the impact of LSES facilities (ie, pumped hydroelectric storage (PHS) and compressed air energy storage (CAES)) with benchmark power grid configuration (ie, New-England-39 bus).In this work, a comparative analysis among different hybrid configurations, particularly wind-solar-thermal, wind-solar-hydro-thermal, wind-solarhydro-thermal-PHS and wind-solar-hydro-thermal-CAES is conducted within a multi-objective optimization environment. The proposed design problem is analysed with the inclusion of real-time constrictions in the form of stochastic variation in renewable power output and random disruptions. The modified bacteria foraging algorithm is used to evaluate the optimum generation schedule for which the operational objectives will be achieved for the design problem. Further, using fuzzy membership function, the trade-off between conflicting objectives is portrayed in Pareto optimal domain. Among different hybrid configurations considered, the HPS which incorporates the CAES system exhibits the most superior performance.

No abstract

No abstract

A centralizing method in the area of IIoT (Industrial Internet of Things) contrived for understanding agriculture which is preceding the arrangements low-power devices [5]. This paper yields a monitoring procedure for farm safety against animal attacks and climate change conditions. IIoT advances are frequently used in smart farming to emphasize the standard of agriculture[6]. It contains types of sensors, controllers. On behalf of WSN, the ARM Cortex-A board which consumes 3W is the foremost essence of the procedure [9]. Different sensors like DHT 11 Humidity & Temperature Sensor, PIR Sensor, LDR sensor, HC-SR04 Ultrasonic Sensor, and camera are mounted on the ARM Cortex-A board. The PIR goes high on noticing the movement within the scope, the camera starts to record, and the data will be reserved on-board and in the IoT cloud, instantaneously information will be generated automatically towards the recorded quantity using a SIM900A unit to notify about the interference with the information of the weather conditions attained by DHt11[14]. If a variance happens, the announcement of the threshold rate will be sent to the cell number or to the website. The result will be generated on a catalog of the mobile of the person to take the necessary action [7].