Scope and Options of Solar Energy Use in Agriculture in Eastern region of India

Groundwater abstraction to meet irrigation demand and application of water and energy efficient irrigation technologies is becoming a difficult affair due to significant energy poverty and pervasive electricity deficits in Eastern region of India. This undermines the production and productivity of small holders. This paper discusses the energy scarcity and possible remedy by the use of solar energy as this region receives abundance solar radiation due to its geographical location and 250 -300 bright sunny days per year which can be year round source of energy for agricultural use.

Download Full-text

PERFORMANCE OF SMALL CAPACITY SOLAR PUMP IN EASTERN REGION OF INDIA

Journal of AgriSearch ◽

10.21921/jas.v7i01.17631 ◽

2020 ◽

Vol 7 (01) ◽

Author(s):

ATIQUR RAHMAN

Keyword(s):

Energy Use ◽

Pressure Head ◽

Eastern Region ◽

Groundwater Abstraction ◽

Annual Fluctuation ◽

Fuel Prices ◽

Delivery Pressure ◽

Current Scenario ◽

Use Efficiency ◽

Solar Pump

Solar energy use for groundwater abstraction is one of the most viable options for smallholders’ irrigation in current scenario of increasing fuel prices. Therefore, the dissemination and adoption of solar pumps of low capacities among these farmers is in demand. In this paper a case study was in eastern region to assess the performance of 3horsepower solar pump, as this capacity pump is currently being promoted by the governments to small farmers at subsidised rates. In eastern region where groundwater regime in most of the area is ranging5-10 m bgl with annual fluctuation of ±2 to ±4 m, and abstracted groundwater by a 3 horsepower solar pumpis rangedfrom 100-173 m3/day, depending upon the months on a bright day. Thispump also offers a delivery pressure head 1.0- 1.5 kg/cm2, and therefore facilitates pressured irrigation for improved water use efficiency.

Download Full-text

Solar Pumps and Water-Energy Nexus in Gujarat, India: First Assessment of the World’s Largest Pilot on Grid-connected Solar Irrigation Pumps

10.21203/rs.3.rs-658617/v1 ◽

2021 ◽

Author(s):

Tushaar Shah ◽

Gyan Rai

Keyword(s):

Solar Energy ◽

Energy Use ◽

Ghg Emissions ◽

Pilot Project ◽

Groundwater Depletion ◽

Groundwater Abstraction ◽

Large State ◽

Groundwater Overdraft ◽

Water Energy Nexus ◽

Water Accounting

Abstract The epicentre of Gujarat’s perverse nexus between electricity subsidy and groundwater depletion lies in its legacy of 485,000 unmetered tubewell owners who have fiercely resisted metering for 20 years. These comprise 40 percent of Gujarat’s irrigation connections but account for 49 percent of agricultural load, 71 percent of energy use in groundwater abstraction and 90 percent of farm power subsidies. Suryashakti Kisan Yojana (SKY), a large, state-wide pilot project which solarised and net-metered 4215 tubewells and began paying farmers for evacuating surplus solar energy, has been enthusiastically embraced by unmetered and metered farmers alike. SKY promises politically acceptable resolution of a wicked energy-water conundrum that afflicts much of India and west Asia. Mainstreaming SKY can significantly reduce groundwater overdraft, GHG emissions and subsidy burden. It will increase farm incomes while radically improving energy-water accounting and management. Gujarat government should invest in compulsory, free-of-cost solarisation of tubewells. We show that doing so is profitable for government and beneficial for farmers, climate and environment.

Download Full-text

Buildings

10.1093/oso/9780198802297.003.0003 ◽

2017 ◽

Author(s):

Peter Rez

Keyword(s):

Heat Transfer ◽

Heat Pump ◽

Energy Efficient ◽

Energy Use ◽

Fossil Fuel ◽

Local Climate ◽

Heating And Cooling ◽

The Difference ◽

As If

Most of the energy used by buildings goes into heating and cooling. For small buildings, such as houses, heat transfer by conduction through the sides is as much as, if not greater than, the heat transfer from air exchanges with the outside. For large buildings, such as offices and factories, the greater volume-to-surface ratio means that air exchanges are more significant. Lights, people and equipment can make significant contributions. Since the energy used depends on the difference in temperature between the inside and the outside, local climate is the most important factor that determines energy use. If heating is required, it is usually more efficient to use a heat pump than to directly burn a fossil fuel. Using diffuse daylight is always more energy efficient than lighting up a room with artificial lights, although this will set a limit on the size of buildings.

Download Full-text

Prediction of Fuel Poverty Potential Risk Index Using Six Regression Algorithms: A Case-Study of Chilean Social Dwellings

Sustainability ◽

10.3390/su13052426 ◽

2021 ◽

Vol 13 (5) ◽

pp. 2426

Author(s):

David Bienvenido-Huertas ◽

Jesús A. Pulido-Arcas ◽

Carlos Rubio-Bellido ◽

Alexis Pérez-Fargallo

Keyword(s):

Low Income ◽

Potential Risk ◽

Energy Use ◽

Risk Index ◽

Computing Time ◽

Simulated Data ◽

Real Data ◽

Support Vector ◽

Energy Poverty ◽

Regression Algorithms

In recent times, studies about the accuracy of algorithms to predict different aspects of energy use in the building sector have flourished, being energy poverty one of the issues that has received considerable critical attention. Previous studies in this field have characterized it using different indicators, but they have failed to develop instruments to predict the risk of low-income households falling into energy poverty. This research explores the way in which six regression algorithms can accurately forecast the risk of energy poverty by means of the fuel poverty potential risk index. Using data from the national survey of socioeconomic conditions of Chilean households and generating data for different typologies of social dwellings (e.g., form ratio or roof surface area), this study simulated 38,880 cases and compared the accuracy of six algorithms. Multilayer perceptron, M5P and support vector regression delivered the best accuracy, with correlation coefficients over 99.5%. In terms of computing time, M5P outperforms the rest. Although these results suggest that energy poverty can be accurately predicted using simulated data, it remains necessary to test the algorithms against real data. These results can be useful in devising policies to tackle energy poverty in advance.

Download Full-text

Implementation of BIM Modelling and Simulation Tools in Reducing Annual Energy Consumption of Multifamily Dwellings

E3S Web of Conferences ◽

10.1051/e3sconf/202017001002 ◽

2020 ◽

Vol 170 ◽

pp. 01002

Author(s):

Subbarao Yarramsetty ◽

MVN Siva Kumar ◽

P Anand Raj

Keyword(s):

Energy Efficient ◽

Energy Use ◽

Construction Materials ◽

Residential Building ◽

Energy Simulation ◽

Point Of View ◽

Rotational Angle ◽

Existing Building ◽

Simulation Tools ◽

Efficient Option

In current research, building modelling and energy simulation tools were used to analyse and estimate the energy use of dwellings in order to reduce the annual energy use in multifamily dwellings. A three-story residential building located in Kabul city was modelled in Revit and all required parameters for running energy simulation were set. A Total of 126 experiments were conducted to estimate annual energy loads of the building. Different combinations from various components such as walls, roofs, floors, doors, and windows were created and simulated. Ultimately, the most energy efficient option in the context of Afghan dwellings was figured out. The building components consist of different locally available construction materials currently used in buildings in Afghanistan. Furthermore, the best energy efficient option was simulated by varying, building orientation in 15-degree increments and glazing area from 10% to 60% to find the most energy efficient combination. It was found that combination No. 48 was best option from energy conservation point of view and 120-degree rotational angle from north to east, of the existing building was the most energy-efficient option. Also, it was observed that 60% glazing area model consumed 24549 kWh more electricity compared to the one with 10% glazing area.

Download Full-text