Within the United States solar energy industry, there is a general motto of “set it and forget it” with solar energy. This notion is derived from much of the research and reliability studies around the photovoltaic (PV) panels themselves, not necessarily the PV system as a whole (including the inverter and other components). This implies that maintenance and regular monitoring is not needed. Yet many things can go wrong to cause the actual performance to deviate from the expected performance. If failures and/or unanticipated degradation issues go undetected, they will lead to reduced energy generation (and associated electricity credits) and/or potential loss of component warranty because of manufacturer turnover. Given the size of the problem and gaps with current solutions, the authors propose that PV system owners need an unbiased third-party off-the-shelf system-level predictive maintenance tool to optimize return-on-investment and minimize time to warranty claim in PV installations. This paper reviews the literature highlighting challenges, current approaches, and opportunities for PV predictive maintenance. The paper concludes with a call to action for establishing a collaborative agenda toward prioritizing PV predictive maintenance.

Developing and underdeveloped countries face innumerable problems related to the accessibility and quality of energy that put the lives of patients, health-care infrastructures, and health workers at risk. Current approaches, such as grid power, unsustainable energy sources such as diesel or gas, and mobile health clinics, have proven insufficient to address this issue. In response, access to reliable health care and electricity has undergone multiple transformations in the last decade, especially in remote and rural areas. Good health and clean energy are two of the 17 United Nations Sustainable Development Goals, originally designed to be a “shared blueprint for peace and prosperity for people and the planet, now and into the future.” Unfortunately, little is known about the interaction between health-care access and energy access in developing and underdeveloped countries, mainly in remote or rural areas. For this reason, this study conducts a review of the literature, including current approaches, challenges, and opportunities for the implementation of solar energy in health centers. As a result, several challenges and opportunities in three impact areas are presented: (1) operational, (2) environmental, and (3) economic. This study delivers detailed information that allows the implementation of solar energy in the health-care sector (in a more effective manner) by sharing best practices.

Solar generation has increased rapidly worldwide in recent years and it is projected to continue to grow exponentially. A problem exists in that the increase in solar energy generation will increase the probability of grid disturbances. This study focuses on analyzing the grid disturbances caused by the massive integration to the transmission line of utility-scale solar energy loaded to the balancing authority high-voltage transmission lines in four regions of the United States electrical system: (1) California, (2) Southwest, (3) New England, and (4) New York. Statistical analysis of equality of means was carried out to detect changes in the energy balance and peak power. Results show that when comparing the difference between hourly net generation and demand, energy imbalance occurs in the regions with the highest solar generation: California and Southwest. No significant difference was found in any of the four regions in relation to the energy peaks. The results imply that regions with greater utility-level solar energy adoption must conduct greater energy exchanges with other regions to reduce potential disturbances to the grid. It is essential to bear in mind that as the installed solar generation capacity increases, the potential energy imbalances created in the grid increase.

As photovoltaics (PV), also known as solar electricity, has been growing over the years, the energy markets have been gradually moving toward decentralization. However, recent media accusations suggest that decentralized renewable energy is slowly becoming unpopular because of the hidden fees being charged to owners of installed PV systems. In response, this paper investigates the potential for alternative approaches to incentivize owners using peer-to-peer (P2P) sharing. This study provides an analytical comparison between the use of the P2P mechanism, the net-metering mechanism, and a combination of these in the commercial sector. Through the use of a simulation, this case study presents the possible outcomes of the implementation of these models in a microgrid. Using technical and economic indexes the comparison was made by looking at the following indexes: peak power, energy balance, economic benefit, and transaction index. Based on a microgrid of 28 commercial buildings, readings of consumption were taken at intervals of one hour, and a Python model was made to find PV size and compare trading mechanisms. It was found that the combination of P2P and net-metering had the best overall performance, followed by net-metering itself, with the best season being all for both, and summer for net-metering by itself. This shows that a P2P model implemented in a microgrid helps create more energy balance, although the combination would achieve the highest performance. This study can be used by policymakers for proposing renewable energy policies and regulations that are more beneficial to all prosumers and consumers.

Solar power generation has increased exponentially in the last decade. It is expected to play an essential role in generating renewable energy in the United States and the world in the future. One of the critical points for the return on investment of photovoltaic systems is to maximize energy generation. Yet, a problem exists in that solar energy systems do not have a monitoring system for all components, so there is no way to know, in real-time, if the solar energy system is performing as expected. This study proposes to evaluate the effectiveness of the PVWatts prediction calculator compared to actual real-world data obtained from the Solar Energy Research Institute (Keshena, WI). The results show that the PVWatts prediction of solar energy generation is statistically significantly different from the actual solar energy generation. Moreover, the actual solar energy generation varies year by year, and the theoretical vs. actual analysis demonstrates that this system is not working according to warranty expectations. Therefore, there is a need for a real-time monitoring system or another type of real-time preventive maintenance to know the performance of solar systems.