The overarching goal of the 2015 United Nations Sustainable Development Agenda is global poverty eradication. There is general international agreement that a necessary prerequisite for alleviating poverty is universal access to clean and affordable energy, which is also an Agenda goal. Affording clean energy requires consumers to have the financial means to purchase sufficient amounts for the intended purpose. In the case of the general population, this means heating or cooling their living space, providing some lighting after sunset, and cooking food. Therefore, energy affordability and poverty are closely associated, in a similar fashion to the relationships between general poverty and income, and between affordability and cost. But, for some people, affordable energy may not be clean, while clean energy may not be affordable. Presently, unclean energy sources supply at least three-quarters of global energy consumption. Is it economically and technically plausible that they can be wholly replaced by clean sources by 2030?

Moreover, even if the colossal amount of capital investment required for this energy source transition were forthcoming, could the necessary clean energy infrastructure be built in a few short years? Could such investments ensure that the somewhat hyped promise of cheap, clean energy is accessible for all future consumers sooner, rather than later? Is mitigating anthropogenic climate change compatible with sustainable development? If not, what is more important: the cleanliness of energy or its cost, or the temperature of a household or the surface temperature of the planet? Exactly what is meant by eliminating energy poverty, and providing access to clean and affordable energy, is discussed in this chapter, along with the plausibility of ensuring that both are achieved. The discussions are focused largely on household energy needs and the impacts of poverty, population growth, energy costs, and energy source transitions, with particular regard to access to electricity.

Solar power has a lot of significance among renewable power resources. Electric production from solar power has become a priority for many nations around the world in the last few years. It is very important to choose the right solar panel when it comes to producing electricity through sunlight. If the selected solar panel is not suitable for the system, there may be many different disadvantages, such as waste of energy and capital.

In this study, it is attempted to determine the best solar panel in terms of technical features and cost in a solar facility planned to be used to enable widespread use of solar energy for low-income communities.

While determining the solar panels studied worldwide among the alternative brands, the evaluation of some characteristics of the brands for low-income communities was taken into consideration simultaneously. Such characteristics include, long "product warranty length," minimum "warranted yearly efficiency reduction," and maximum "warranted energy output," etc. For the case study, 415 W monocrystalline solar panel brands were analyzed. The results were evaluated using Analytic Hierarchy Process (AHP) among Multi-Criteria Decision Making (MCDM) techniques.

Addressing the simultaneous provision of electricity, heat, and water to rural areas is a pervasive global challenge. This study focuses on optimizing a poly-generation hybrid system that integrates PV, wind turbine, Combined Heat and Power (CHP) unit, battery, and brackish water reverse osmosis desalination, designed for warm climates, to meet the essential energy needs of Sar Goli village and a health clinic in Khuzestan province, Iran. Unlike previous studies, this research conducts sensitivity analyses considering diverse economic and climate conditions, evaluating the grid breakeven distance, environmental impact, and technical performance. The proposed 51.2 kW PV/10 kW WT/10 kW CHP/96 kWh BT/23.8 kW CNV system with reverse osmosis desalination demonstrates a cost of electricity (COE) and net present cost (NPC) of $0.161/kWh and $107,203, respectively. The study highlights that increased solar irradiation and wind speed contribute to cost efficiencies in renewable energy, resulting in lower NPC and COE values. However, rising diesel prices pose economic challenges for diesel-dependent systems, emphasizing the importance of strategic planning for resilient energy solutions. Additionally, improving boiler efficiency significantly reduces fuel consumption and CO₂ emissions, emphasizing the interconnected nature of thermal load levels and environmental impact, guiding the path toward enhanced sustainability.

A controlled environment greenhouse requires a large amount of heating during the winter months, which is conventionally supplied by environmentally damaging fossil fuels. To lessen the detrimental effect of fossil fuels on the environment, it is beneficial to use clean solar energy for heating these greenhouses. This paper aims to enhance solar insolation in a greenhouse located in Toronto, Ontario by manipulating greenhouse orientations, roof inclinations, and greenhouse shapes. Different greenhouse models were designed on SketchUp software and then simulated in TRNSYS software to determine the pattern of solar insolation available on different greenhouse models. Greenhouse orientation considered for this study included east-west orientation, north-south orientation, and distinct angles between these orientations. Different roof inclinations of 15°, 30°, 45°, and 60° were examined to observe the pattern of solar insolation availability on the greenhouse roofs. Further to this, typical shapes of a greenhouse (i.e., even, uneven, vinery, semi-circular, elliptical or arch, single span, and quonset) were also investigated to determine solar insolation on greenhouse surfaces.

The simulation results indicated that a 30° North of East greenhouse orientation maximizes solar radiation availability. Changing greenhouse orientation has a negligible impact on solar insolation availability, and the maximum percentage increase in solar insolation that can be achieved by changing the greenhouse orientation is only 0.6%. Solar insolation availability on the south roof and the south wall is the highest as compared to the other greenhouse roofs and walls. It can be further improved by changing the south-roof inclination of an even-span greenhouse from 15° to 60°. Furthermore, an east-west-oriented single-span greenhouse receives the maximum solar radiation, followed by an uneven-span greenhouse for a complete year. This investigation will benefit by capturing more solar insolation falling on a greenhouse surface, which can be harnessed to increase the inside air temperature of a greenhouse.

There exists a global trend characterized by the increasing adoption of renewable energy sources to overcome climate problems. This research attempts to construct a scenario-based model to undertake a quantitative analysis of the prevailing state of electricity generation and forecast the future composition of the generation mix. There is variability in future electricity demand. To account for these uncertainties, nine scenarios were developed using the Long Emissions Analysis Platform (LEAP) tool: the Low Demand case following a business-as-usual (Low-Demand-BAU), a scenario involving the implementation of a renewable plan (Low-Demand-Renewable), a scenario combining renewable and nuclear energy plans (Low-Demand-Renewable-Nuclear), the Base-Demand case, business-as-usual scenario (Base-Demand-BAU), a scenario implementing a renewable plan (Base-Demand-Renewable), a scenario integrating renewable and nuclear energy plans (Base-Demand-Renewable-Nuclear), the High Demand case business-as-usual scenario (High-Demand-BAU), a scenario adopting a renewable plan (High-Demand-Renewable), and a scenario involving a renewable and nuclear energy plan for meeting high demand. The business-as-usual scenarios are predicated on the current generation mix to meet demands. The renewable and nuclear plans aim to leverage both nuclear power and renewable energy potential. Comparative evaluations of these scenarios are conducted to assess their environmental impact, and ultimately, the results are analyzed.