Developments in Solar Energy Resource Assessment and Economics

Dear Colleagues,

In this Special Issue, we attend to the fundamentals of measuring of light for solar photovoltaic energy conversion, or solar energy resource assessment (SERA). Sunlight surrounds us, and we are affected by that light as a part of our environment, engaged in the energy transformations that are ultimately optocaloric (sensible/latent drivers influencing electricity demand in buildings), optoelectronic (solar photovoltaics), and photochemical (agriculture, vision, and vitamin D production in our skin). We hope to draw in contributions that will emphasize the importance of light measurement as an essential tool in understanding the spatiotemporal factors that affect our rapidly growing fleet of new electricity coming from solar photovoltaics.

Everything in solar assessment is meteorological and climatological in nature. SERA can include radiometry, forecasted irradiance, and the applications of those data for power performance estimation and financial performance estimation. As solar industries evolve, we have seen stronger SERA teams emerge to deliver values of variance and uncertainty for solar power production all over the globe. Radiometry is big business in the expanding field of solar power.

Investing in local terrestrial SERA can be an effective choice in an increasingly competitive solar electric market, particularly for high performance O&M of solar farms. Why do we invest in research to measure light? I would say we measure those factors that we value for energy stability and economic returns and, in turn, we value what we measure by giving increasing attention to the data that emerge. We value the insights and patterns observed from a dynamic energy resource strongly coupled to meteorological regimes of time and space. More directly, we value these measurements because quarterly firm earnings depend on it, because performance-based risk assessment depends on it, and because we expect many new, profitable solar services to emerge in the wake of a dramatic expansion of radiometric data, from a world full of terrestrial and satellite radiometers.

A great number of adaptive models have emerged to address the challenge of estimating direct normal irradiance (DNI) in tandem with global irradiance for a given plane of array (POA), especially given the increase in bifacial solar photovoltaic systems and tracking systems for ground mounted photovoltaics. For years, the challenge has been a financial tradeoff in measurement investments, between high temporal fidelity for isolated ground monitoring stations, or high spatial fidelity across large regions from satellite remote sensing. Alternatively, cost reductions in materials, computing, and data storage have caused a push for innovative techniques to directly monitor cloud dynamics and DNI to ground-truth satellite data in ways that were just not available 15 years ago.

SERA can be useful in predicting intermittent patterns of power production from sunlight across a portfolio of sites in a given region of a nation. Forecasting has advanced dramatically in the past 5–7 years, particularly to address the need for component-based measures of shortwave light and to assess the intermittent responses of power ramping and microclimate change in grid-tied (e.g., utility scale) photovoltaic farms. Keep in mind that the majority of meteorological forecasting work of the past decade was developed to addresses the industries of aerospace (visibility) and agriculture (rainfall), as well as for catastrophic events. Thus, one major emerging challenge is the need to open up and share new discriminatory tool developments and technological adaptations that specifically fit the need of solar power producers.

As the world of solar photovoltaics continues its geometric expansion into electricity production for all forms of demand, so too does the demand increase for even cheaper, faster, more distributed, and data-rich resource frameworks. There are challenges on the horizon for data management, transparency of irradiance data sharing among nations and industries, and introducing low-cost measurement technologies that can and will penetrate into developing nations and, in particular, among the nations of the Global South.

Solar production at utility scales consumes large parcels of landscape. Those expansions have also added a dynamic of land management through native seed mixtures and pastoral animal integration. SERA may thus play a future role in providing new solar services to address water cycle dynamics in soils, associated microclimate behaviors, and the reduction in performance uncertainty in modeled quarterly returns for a portfolio of PV arrays across a climate regime. Thus, we envision a shift in acquiring energy from a “power plants” to energy from “power parks” or “solar farms”, drawing together new economic benefits of ground-based local light measurement.

In this Special Issue, we focus on the innovative developments and synergies occurring in radiometry, forecasted irradiance, data management, and the diverse technoeconomic applications of solar resource datasets.

Potential topics include, but are not limited to:

• Radiometry (spectral, components, networked)
• Solar resource assessment for developing nations
• Data management, e.g., processing, storage, transparency;
• Light/power forecasting and machine learning;
• Light-coupled technoeconomic performance modeling
• Solar services for power producers or land management
• Economics of radiant energy datasets

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• photovoltaics
• solar energy
• radiometry
• forecasting
• policy, economics, regulation
• solar performance modeling and simulation