Peningkatan Prestasi Belajar PKn dengan Model Sumbang Saran (Brain Storming) pada Konsep Demokrasi Kelas VIII di SMP 1 Bakongan Timur

Banda Ace

PENGARUH DOSIS KUNING TELUR TERHADAP DAYA TAHAN HIDUP SPERMATOZOA AYAM KAMPUNG (GALLUS DOMESTICUS) DALAM PENGENCER NACL FISIOLOGIS

Banda Ace

Simulation of DC/DC converter for DC nano-grid integrated with solar PV generation

Distributed energy resources (DER) based micro grid and Nano-grid framework is most technically viable bottom-top approach to sustainably meet ever-increasing demand of rural and urban communities. Recently the growth of DC operative home appliances like mobile and lap top chargers, ovens and hair dryer's etc. are increasing and therefore a DC/DC converter is an efficient way to meet the electricity need from the local DER and helps in improving the system efficiency. This paper presents simulation results of a buck boost converter, MPPT algorithm (P & O method) for solar PV module and closed loop PI control system for obtaining constant 12 V and 24 V DC output voltage at DC bus. The proposed methodology is to extract maximum DC power from solar PV system and it is directly fed to DC load or DC Nano grid.by Rajesh M. Pindoriya, Naran Pindoriya and S. Rajendra

Simulation and experimental study of single phase PWM AC/DC converter for Microgrid application

by Gundabathini Rakesh and Naran Pindoriy

Impact assessment of distributed solar PV integration in low-voltage unbalanced distribution network: a case study

by Balveer Singh and Naran Pindoriy

Residential demand response algorithms: state-of-the-art, key issues and challenges

Demand Response (DR) in residential sector is considered to play a key role in the smart grid framework because of its disproportionate amount of peak energy use and massive integration of distributed local renewable energy generation in conjunction with battery storage devices. In this paper, first a quick overview about residential demand response and its optimization model at single home and multi-home level is presented. Then a description of state-of-the-art optimization methods addressing different aspects of residential DR algorithms such as optimization of schedules for local RE based generation dispatch, battery storage utilization and appliances consumption by considering both cost and comfort, parameters uncertainty modeling, physical based dynamic consumption modeling of various appliances power consumption at single home and aggregated homes/community level are presented. The key issues along with their challenges and opportunities for residential demand response implementation and further research directions are highlighted.by Rajasekhar Batchu and Naran M. Pindoriy

Reactive resource reallocation in DG integrated secondary distribution networks with time-series distribution power flow

by Kalpesh Joshi & Naran Pindoriy

A SARIMA-RVFL hybrid model assisted by wavelet decomposition for very short-term solar PV power generation forecast

A very short-term solar PV power generation forecast can be extremely helpful for real-time balancing operation in an electricity market which in turn will profit both energy suppliers as well as customers. However, the intermittency of solar PV power introduces inaccuracies in its forecast. To address this challenge, the research paper has studied the effect of wavelet decomposition of solar PV power time series on its forecast. A novel and time adaptive, Seasonal Autoregressive Integrated Moving Average (SARIMA)-Random Vector Functional Link (RVFL) neural network hybrid model assisted by Maximum Overlap Discrete Wavelet Transform (MODWT) has been proposed. The solar PV power generation data obtained from roof-top solar PV plants installed at IIT Gandhinagar is used to develop and validate the forecast models. Various numerical forecast accuracy measures have been calculated which show an improvement in accuracy and adaptability of proposed forecast model over constituent models.by Vishal Kushwaha and Naran M. Pindoriy