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The expanding commercial building sector and urbanization in India leads to an increase in demand of energy many folds. Consequently, it is the need of the current scenario to define some regulatory regime or policy to harness the enormous potential of energy savings. Under the Energy Conservation Act 2001, the Government of India under the Bureau of Energy Efficiency launched the Energy Conservation Building Code (ECBC) on a voluntary basis. ECBC sets the standards of minimum energy performance for “large commercial buildings. These norms were for both new and existing buildings. Retrofitting of existing buildings offers noteworthy opportunities for reducing global energy consumption and greenhouse gas emissions. This paper provides a systematic approach to review the application of energy conservation building codes in existing buildings and identification of the best retrofit strategies to stimulate the implementation of ECBC in the country.

The expanding commercial building sector and urbanization in India leads to an increase in demand of energy many folds. Consequently, it is the need of the current scenario to define some regulatory regime or policy to harness the enormous potential of energy savings. Under the Energy Conservation Act 2001, the Government of India under the Bureau of Energy Efficiency launched the Energy Conservation Building Code (ECBC) on a voluntary basis. ECBC sets the standards of minimum energy performance for “large commercial buildings. These norms were for both new and existing buildings. Retrofitting of existing buildings offers noteworthy opportunities for reducing global energy consumption and greenhouse gas emissions. This paper provides a systematic approach to review the application of energy conservation building codes in existing buildings and identification of the best retrofit strategies to stimulate the implementation of ECBC in the country.

In an advanced industrial effort, the role of vapour absorption refrigeration system plays a major role. However, the significant eco-friendly and the required cooling capacity rate are the major c...

The paper illustrate the development and validation of two regression models i.e., poisson and artificial neural network employed to predict the significance of different climatic variables for an institutional building in composite climate. For prediction of outer wall temperature using five input parameters (ambient temperature, relative humidity, global radiation, wind speed and wind direction), two modeling approaches: poisson and artificial neural network were used. The results of both the model were validated through test data analysis in terms of three statistical measures namely, R-squared, root mean square error and mean absolute error. The performances of both the models are comparable in terms of train and test data. Comparative statistical analysis of both the model shows a better fit for the artificial neural network model as it was capable of adjusting themselves to the unpredicted changes in the input data. For the current study where weather parameters are continuously fluctuating poisson model was preferred as it generates the estimation coefficient values for the variables while neural model is not mathematically defined. The study demonstrates that neural model should be used as an alternative method for temperature prediction. The content and format of the paper has been widely used for designing and retrofitting of buildings by considering the most significant climatic variables for future work. Also, it helps the architects and engineers to find the relevant insulating material for the building envelope as per the requirement and subsequently improves its thermal behavior.

The growing need for energy by the human society, climate change and depletion of conventional energy sources demands a renewable, safe, illimitable and low-price energy source. One of the best applicable means to break the accountable world’s activity crisis is to use the authority of the sun. Solar activity is clean, great and environment-amicable abeyant ability amid renewable activity options. Solar Photovoltaic (SPV) cells/ modules are composed of silicon or other semi-conductive materials. Semiconductor materials have negative temperature coefficient. The photovoltaic module power output/efficiency depends linearly on the operating temperature while operating temperature of photovoltaic module is depends on the meteorological parameters such as: wind speed, humidity, sky condition etc. In order to predict the energy production of photovoltaic (PV) modules, it’s far compulsory to presage the PV module temperature as a function of ambient temperature, wind speed, wind direction, total irradiance, and relative humidity. This paper presents a statistical model to evaluate the effect of meteorological parameters on the performance of PV cell/module and predict the modules efficiency & module temperature. How to cite this article: Sanjay, Berwal AK. Development of Statistical Model to Evaluate the Effect of Meteorological Parameters on the Performance of PV-Cell/ Module. J Adv Res Alt Energ Env Eco 2020; 7(1): 1-7. DOI: https://doi.org/10.24321/2455.3093.202001

Renewable energy is a viable alternative to meet growing energy demand of the country. Realizing this fact, Indian government has recently expressed an intention towards achieving 100 GW of solar capacity by 2022; out of which 40% is being expected through decentralized and roof top scale solar projects. One such Photovoltaic (PV) plant of 50 kW capacity installed at the roof top of Saraswati library building of Deenbandhu Chhotu Ram University of Science & Technology has been analyzed for its technical and financial viability. We have also analyzed the mix of technicalities involved in this PV plant. This PV plant is generating more than 5200 kWh/month of electricity and reducing 4070 kg/month of GHG emissions. Further, this plant is installed with govt. subsidy and found that the subsidy amount makes it lucrative by reducing pay back duration to 5.7 years and increasing the IRR to 16.97%. But even without subsidy, the pay back duration comes out to be 10.3 years and IRR equals to 8.22% to make it financially viable. Thus it is observe that if govt continued to provide subsidy up to 30% to such projects for next 2 to 3 years, then it will help to attract the domestic sector to get install more and more PV plant on their rooftop. Further attempt have been made to present a generic framework for providing SPV power system.