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The purpose of this paper is to focus on life cycle cost analysis (LCCA) of 1 MW roof-top Solar Photovoltaic (PV) panels installed in warm and humid climatic region in Southern India. The effect of actual power generated from solar PV panels on financial indicators is evaluated.

LCCA is done using the actual power generated from solar PV panels for one year. The net present value (NPV), internal rate of return (IRR), simple payback period (SPP) and discounted payback period (DPP) are determined for a base case scenario. The effect of service life and the differences between the ideal power expected and the actual power generated is evaluated.

A base case scenario is evaluated using the actual power generation data, 25-year service life and 6 percent discount rate. The NPV, IRR, SPP and DPP are found to be INR 13m, 8 percent, 10.9 years and 18.8 years respectively. It is found that the actual power generated is about one-third less than the ideal power estimated by consultants prior to project bidding. The payback period increases by 70–120 percent when the actual power generated from solar PV panels is considered.

The return on investment calculated based on ideal power generation data without considering the operation and maintenance related aspects may lead to incorrect financial assessment. Hence, strategies toward solar power generation should also focus on the actual system performance during operation.

This study aims to estimate the electric power production of the 20 MWp solar photovoltaic (PV) plant installed in the Adrar region, South of Algeria using minimal knowledge about weather conditions.

In this study, simulation models based on linear and nonlinear approaches were used to estimate accurate energy production from minimum radiometric and meteorological data. Simulations have been carried out by using multiple linear regression (MLR) and artificial neural network (ANN) models with three basic types of neuron connection architectures, namely, feed-forward neural network, cascade-forward neural network (CNN) and Elman neural network. The performance is measured based on evaluation indexes, namely, mean absolute percentage error, normalized mean absolute error and normalized root mean square error.

A comparison of the proposed ANN models has been made with MLR models. The performance analysis indicates that all the ANN-based models are superior in prediction accuracy and stability, and among these models, the most accurate results are obtained with the use of CNN-based models.

The considered model will be adopted in solar PV forecasting areas as part of the operational forecasting chain based on numerical weather prediction. It can be an effective and powerful forecasting approach for solar power generation for large-scale PV plants.

The operational forecasting system can be used to generate an effective schedule for national grid electricity system operators to ensure the sustainability as well as favourable trading performance in the electricity, such as adjusting the scheduling plan, ensuring power quality, reducing depletion of fossil fuel resources and consequently decreasing the environmental pollution.

The proposed method uses the instantaneous radiometric and meteorological data in 15-min time interval recorded over the two years of operation, which made the result exploits a fact that the energy production estimation of PV power generation station is comparatively more accurate.

The chapter will explore the growth and opportunities of small-scale local power generation and the implications for internet access for rural communities. Solar power has grown exponentially in the last decade across the world and has provided opportunities for the development of local energy communities and on microgrids across the world and in Europe.

The huge cost reductions experienced in solar and its relative mobile and flexible nature have made it a technology perfect for rural areas to develop their own sustainable source of electricity supply. The increasing rise of digital tools has coupled nicely with the advent of mass use of solar in rural areas and thus the connection between smart solar and smart villages has become increasingly a norm.

Rural communities in Europe have embraced solar technology, with many farmers using solar as a means to reduce their electricity costs and also generate new streams of income to improve their overall livelihoods. Some case studies from India, Germany, and Africa will be examined. Other experiences will also be considered, especially where double land use between solar technology and livestock has empowered rural communities.

Outside of Europe, Africa and Asia have also seen solar as a means to electrify remote rural villages. This has lead to the development of microgrids and new technologies that are less deployed in Europe, which are being rolled out for rural communities in the rest of the world. This has been particularly successful in creating smart rural communities as often digital communications have already reached these communities and thus power and telecoms are combining to provide clean and controlled power for millions in Africa. This chapter will also assess the growth of smart energy communities in non-traditional energy markets and determine what lessons we can learn from their experiences.

This chapter will examine other sources of renewable energy and the role that biogas, biomass, and others are playing in the creation of smart villages in Europe and beyond. Biomass has been the traditional tool for many rural communities to generate power and heat and thus an examination of how it now plays a role in smart villages is vital to understanding the energy transition we are experiencing in rural communities.

The purpose of this paper is to present the development of an optimal design framework for high altitude long endurance solar unmanned aerial vehicle. The proposed solar aircraft design framework provides a simple method to design solar aircraft for users of all levels of experience.

This design framework consists of algorithms and user interfaces for the design of experiments, optimization and mission analysis that includes aerodynamics, performance, solar energy, weight and flight distances.

The proposed sizing method produces the optimal solar aircraft that yields the minimum weight and satisfies the constraints such as the power balance, the night time energy balance and the lift coefficient limit.

The design conditions for the sizing process are given in terms of mission altitudes, flight dates, flight latitudes/longitudes and design factors for the aircraft configuration.

The framework environment is light and easily accessible as it is implemented using open programs without the use of any expensive commercial tools or in-house programs. In addition, this study presents a sizing method for solar aircraft as traditional sizing methods fail to reflect their unique features.

Solar aircraft can be used in place of a satellite and introduce many advantages. The solar aircraft is much cheaper than the conventional satellite, which costs approximately $200-300m. It operates at a closer altitude to the ground and allows for a better visual inspection. It also provides greater flexibility of missions and covers a wider range of applications.

This study presents the implementation of a function that yields optimized flight performance under the given mission conditions, such as climb, cruise and descent for a solar aircraft.

Renewable energy sources such as solar photovoltaic (PV) and wind are ubiquitous because of their lower environmental impact. Output from solar PV and wind turbines is unstable; hence, this article aims to propose an effective controller to extract maximum available power.

By focusing on the varying nature of solar irradiance and wind speed, the paper presents the maximum power point tracking (MPPT) technique for renewable energy sources, and power regulation is made by the novel inverter design. Moreover, a DC–DC boost converter is adopted with solar PV, and a doubly fed induction generator is connected with the wind turbine. The proposed MPPT technique is used with the help of a rain optimization algorithm (ROA) based on bi-directional long short-term memory (Bi-LSTM) (ROA_Bi-LSTM). In addition, the sinusoidal pulse width modulation inverter is used for DC–AC power conversion.

The proposed MPPT technique has jointly tracked the maximum power from solar PV and wind under varying climatic conditions. The power flow to the transmission line is stabilized to protect the load devices from unregulated frequency and voltage deviations. The power to the smart grid is regulated by three-level sinusoidal pulse width modulation inverter.

The methodology and concept of the paper are taken by the author on their own. They have not taken a duplicate copy of any other research article.

Despite the abundant renewable energy potential in the Nigeria, the power-sector stakeholder has not paid attention to the prospect of the natural resources that can be accrued when it is properly harnessed. Although a very negligible fraction of the population has invested in solar photovoltaics (PVs) for home solution, the initiative was only made public commercialised under the public-private partnership (PPP) and the objectives of the Power Sector Reform Act. 2005. It is, therefore, aimed to investigate the causes and insight of the barriers that are responsible for the slow implementation of the solar energy initiative in the Nigeria.

An empirical study was performed in the Nigeria. The study was conducted qualitatively, through semi-structured face-to-face interviews of 25 participants. The interviews were recorded, transcribed, interpreted, coded, categorised into themes and analysed by content analysis.

The study reveals technological, financial, political and social barriers have been the reason for slowing down solar energy development in Nigeria. While the technical barrier is a challenge to the solar energy implementation, socio-cultural issues have also been an obstacle to the implementation process. It is suggested that, the stakeholders of the initiative endeavour to proffer sustainable policies to enable public and private promoters to be able to generate and distribute electricity through solar PV and to complement the inadequate conventional electricity sources from the grids.

The paper provides a richer insight into the understanding and awareness of barriers for implementing solar energy strategies in Nigeria.

This chapter provides an overview of the current status of renewable energy projects and identifies the key success factors of well-performing public–private partnerships (PPPs). To this end, this study analyses around 1,700 renewable projects on the World Bank’s Private Participation in Renewable Energy (PPRE) database. We then follow an inductive approach for a case review and examine a 5-MW rooftop solar PPP in Gujarat, India, that had been implemented in 2012. In spite of the rapid growth of renewable PPPs, regional disparity is distinct and most PPPs have been undertaken in Latin America and the Caribbean or a few selective countries such as China or South Africa. The case study informs that the successful PPPs may be attributed to such factors as policy coordination in multi-governance systems to attract project investments, the handling of land constraints in a project planning stage, and Green Incentive given to project participants. It offers a valuable insight into the significance of well-designed PPPs for enhanced energy access in developing countries, while accelerating the global transition to renewable-based energy supply to promote sustainable development.

Power management of a wireless sensor node is important and needs to be designed efficiently without wasting excessive energy. The purpose of this paper is to report on the improvement of the power management of a wireless sensor node.

The design involves the implementation of solar recharging technology with single‐ended primary inductance converter (SEPIC) on a wireless sensor node in order to achieve the improvement in power management.

The combination of the solar recharging technology with SEPIC converter shows promising results for efficiently supplying the power to the wireless sensor node.

The design idea can be extended for many other electronic sensor applications, which can help to ensure an efficient power management of the sensor nodes.

The proposed design model demonstrates a new idea towards reduction of energy usage for wireless sensor nodes.

This study aims to examine the farmers’ awareness level and explores the factors, which may influence their adoption intention regarding solar powered pumps.

The study consist of a sample of 510 respondents selected from the rural region of Punjab (India) by using convenience sampling. Descriptive analysis, exploratory factor analysis, confirmatory factor analysis and multiple regression analysis techniques have been used for the analytical purpose.

The study reveals that dimensions such as perceived benefit, perceived compatibility and government incentives have a significant impact on intention to use solar powered pumps, whereas high investment cost and lack of awareness regarding government subsidies are the main reason for non-adoption of the same.

The sample size has been selected on the basis of convenience sampling and has been taken from the rural area, which may affect its generalizability.

The present research is expected to be useful for the manufacturers, regulators, customers, commercial banks, product and service providers, and other environmental institutions.

The study has acknowledged various intentional factors, which influence the adoption decision of solar powered pumps. Therefore, the present study will be useful to formulate action plans to improve the environmental quality.