The electricity consumption patterns of food vendors within the University of Lagos 2001 Cafeteria complex on daily and seasonal bases as function of users' behavioral and load demands are characterized. This paper investigates the capability of using multivariable linear regression (MLR) and condition demand analysis (CDA) as methodologies to determine the consumption patterns of unmetered food vendors in a deregulated power system. These approaches can help in developing a unique sustainability model, based on food vendor's behaviour from the use of appliances in the cafeteria. It is anticipated that this model would enable automatic allocation of electricity consumption to unmetered food vendors. The profiles for individual food vendors, which contribute towards the aggregate load profile for the cafeteria complex, are characterized. The integration of this load-shape allocation model with the ongoing development of an alternative renewable power generation from food waste is capable of reducing peak-demand from the local grid.

The Stirling engine is a simple type of external-combustion engine that uses a compressible fluid as a working fluid. The Stirling engine can theoretically be very efficient to convert heat into mechanical work at Carnot efficiency. It is an environmental friendly heat engine which could reduce CO2 emission through combustion process. Various parameters could affect the performance of the addressed Stirling engine which is considered in its optimization for designing purpose. Through addressed factors, torque and power have the highest effect on the robustness of the Stirling engines. Due to this fact, determination of the two referred parameters with low uncertainty and high precision are needed. In this communication, the distribution of torque and power are represented based on experimental evidence. A new polynomial model is suggested to calculate torque and power, based on experimental data. This study addresses the question of whether GMDH-type neural networks could be used to estimate the torque and power based on specified variables.

The present study deals with the economic and environmental assessment of energy conservation in residential buildings. In this approach, the heating and cooling loads of a typical residential building in Tehran with micro gas turbine units have been considered. This 8000 m2 area building possesses 10 floors with 4 units per floor. Five distinguished scenarios, wall insulation, roof insulation, shading, triple glazing and all of the four energy conversation methods have been proposed concerning the decrease in the energy usage. Each of the energy conservation methods was studied separately in four former scenarios and all of these methods were investigated simultaneously in the fifth latter scenario. To achieve the heating, cooling and electrical loads, a number of 30 kW combined heat and power (CHP) micro gas turbine units have been taken into consideration without energy conversation methods. The results show that the best scenario concerning the minimum value of energy loss is that for which the mean heating and cooling loads were 514.58 and 519.08 kW, respectively. Also the number of CHP micro gas turbine units reduces from 30 to 11 and also the total electricity cost decrease from 0.32 to 0.16 US$/kWh with consideration social cost of air pollution.

Emitted gasses from the landfills are one of thesignificant sources of air pollution in Iran. Meanwhile, the reduction, controland recycling of such gasses is of great importance from hygienic and globalperspectives. Kahrizak landfill site has been a dumping place for the past 40years. The average amount of wastes disposed at the site is approximately 7000 Tons per day. The purpose of this study iscalculation CH4 (Methane) and CO2 (Dioxide carbon) emissionsand estimate the carbon reduction potential using the Land GEM 3.02 model. Validationof this model was tested by comparing the model estimates with the methane andCO2 recovery rate compiled from the experimental results of Kahrizak landfill between 1994 and 2004. Based on the model results, theCH4 and CO2 emissions between 1992 and 2012 were determinedand sensitivity analysis was performed for various quantities of the decay rate. Through gas-recovery and extracting energy fromlandfills with 75 percent efficiency, the generation rate of greenhouse gaseswill reduce to around 557,633 tons of CO2 equivalent in Iran.

During a period of 6 months, 15 previously homeless male participants from a small town in the UK were encouraged to adopt an intrinsic and environmentally responsible attitude. The aim was to specifically reduce the participants' energy consumption. This was done through self- awareness sessions in parallel with traditional environmental educational sessions. Self-awareness was in this study used as a tool to help guide the participants towards a positive sense of self through the engagement of energy saving behaviours. The self-awareness sessions took place in the form of a series of small group sessions. Focus groups were conducted prior to the group sessions taking place and after they had been completed, in order to measure whether their environmentally held beliefs had changed. Each focus group was structured around their environmentally held beliefs and took around 1 hour. Thematic analysis was used to analyse the focus groups. The analysis revealed that at the onset the participants lacked interest in energy reduction behaviours. However, after having taken part in the self-awareness sessions it became evident that a shift in attitudes had occurred. This investigation was part of a bigger project with the participants in which their social housing underwent retrofitting with air-source heat pumps, to make the houses more energy efficient. Consequently, participants' energy usage was monitored using smart meters. Such monitoring supported the results from the thematic analysis in that it showed a decrease in energy use during the 6 months period the participants attended self-awareness sessions.

A complete hybrid system including a photocelland a wind turbine with battery storage is modeled, and the best approach forsizing the system to meet the electrical energy needs of a residential buildingis investigated. In evaluating system performance, the city of Tehran is usedas a case study. Matlab software is used for analyzing the data and optimizingthe system for the given application. Further, the price of the system design isinvestigated, and shows that the electrical cost of the hybrid system in Tehranis 0.62 US$/kWh, which is 78% less expensive than a wind turbine system and 34%less expensive than a photovoltaic system.

In the current century, energy is become as one of the most critical issues in human's life. Due to global warming, air pollution and the other problems caused by fossil fuels, one of the appropriate sources which is renewable and is invested is wind energy. Iran has a good potential for using wind energy based on its geographical features. Therefore, to have the best productivity for employing wind energy, locating farm winds in a suitable site is a delicate issue. This research applied a hybrid MCDM method for prioritizing potential cities in Iran to install wind farms. In this regard, Step-wise Weight Assessment Ratio Analysis (SWARA) is employed to rank criteria and Weighted Aggregates Sum Product Assessment (WASPAS) applied for evaluating alternatives. In this study 10 cities are detected as high potential places for this aim. Eventually, the most appropriate city is identified as the best place to set up farm winds, and a comprehensive GIS map depicts the results. The results of this research can be used in decision making and planning of energy management in top level of managing requirements of countries in all respects.

Prediction of wind and solar energy is deemed one of the most important contributory factors towards sustainability. Along the same lines, to harvest energy and guarantee the safety of a place, accurate information about the future of the region is needed. To achieve the target, this paper predicts solar irradiation and wind velocity time series by two robust artificial intelligence algorithms which are called Wavelet and ANFIS (Adaptive Network Fuzzy Inference System). The data used for the predictor system are obtained from a meteorological station in Tehran, Iran.  The results show that a) robustness of both algorithms for prediction of wind velocities and solar irradiation b) superior strength of Wavelet to ANFIS for prediction of solar irradiation c) ANFIS makes a better prediction of Wavelet for wind velocities.

The State of Vermont, USA seeks to expand the generation and use of renewable electricity over the coming decades. I apply a social-ecological-technical systems framework to investigate the resource potential and land use tradeoffs of development of in-state commercial-scale solar photovoltaic and wind electricity generation facilities in Vermont. Based on existing policy goals, I calculate number of facilities required and use spatial modeling and simulation to assess solar photovoltaic and wind resource potential, suitable siting patterns and tradeoffs between resource productivity and biodiversity. This assessment finds that Vermont will require from 178 to 1,527 - 2.2 MW solar photovoltaic facilities and an additional 9 to 76 - 20 MW wind facilities by 2032. Vermont's solar photovoltaic resource potential is equivalent to 18.9 percent of the state's total land area, and wind resource potential is equivalent to 3.1 percent of the state's total land area. Vermont holds sufficient solar and wind resource potential to support the state's renewable electricity policy goals. Renewable electricity development in Vermont will require confronting a tradeoff between use of areas with either lower resource potential or moderate biodiversity value. The conceptualization of Vermont's emerging renewable energy system as a social-ecological-technical system can guide future research and decision making.

Water pumping systems powered by solar and wind energy are a clean, decentralized and economic alternative for the irrigation of crops. The intense droughts experienced in the last years in Northern Colombia due to particularly strong Niño Phenomena have reactivated the need of reliable water pumping irrigation systems in that region. This study aims to assess the techno economic feasibility of solar and wind based pumping irrigation system, taking as case study the Municipality of Piojó in the Atlántico department. In the first stage of the study the irrigation water requirements were determined by using the software CROPWAT based on two different crop patterns that represent existing feasible alternatives for small farmers of the region: i) a common crop pattern, which represent the current average distribution of crops for subsistence farming and ii) a fruit cash crop pattern that comprises crops for which well established markets in the region exist. Solar wind and diesel based pumping systems were sized based on the crop water demands for 1 ha. The unit irrigation costs of the three technologies, the two crop patterns and the three irrigation methods (surface, sprinkler and drip) were calculated and compared. The economical analysis was complemented with a cost-benefit analysis over 20 years. Our results show that both renewable energy based pumping systems (wind and solar) can cover the irrigation water demands of small farmers in the region. The economical analysis shows that windmills are the most cost effective solution followed by the solar pumping system. Diesel pumping system was the less cost effective, even though it does not comprise investment in water storage tank. The cost benefit analysis demonstrates that any irrigation system is financially unfeasible when providing water to a common crop pattern. In case of the fruit cash crop scenario the highest dividends were obtained by the wind pumping system and the lowest dividends by the diesel pumping system. The lowest payback period was obtained by the windmill after 7 years and could be even feasible after the fifth year if the surplus water would be used to irrigate larger areas. Dividends obtained in a fruit cash crop scenario with irrigation after 20 years were in the range of €5200 and €11200 higher than dividends obtained by the same crop pattern but without irrigation.