Solar Energy

The Solar Energy section of New Energy Research provides data and information on solar energy assessment and PV performance modeling.  Chapter topics are illustrated in the process poster and subject links below.

Process Poster

SolarEnergy-Assessment-c
Click to enlarge

Section Chapters

Solar resource and engineering performance assessment have several distinct modeling steps.  Section chapters represent different steps in the modeling and due diligence process:

  1. Sunlight & Weather: Solar resource data drives the solar energy assessment process and defines gross energy potential prior to accounting for technology performance, design engineering decisions, and system losses.  Understanding extraterrestrial irradiance, optical air mass, and the dynamics of the atmospheric boundary layer are the key to understanding terrestrial irradiance.  Data used in solar energy assessments include ground sensor and satellite irradiance data, and gridded atmospheric weather data.  
  2. Incident Irradiance: Irradiance on the plane of array is calculated using sun position and array orientation.  Incident irradiance is also understood by assessing sunlight components, including direct beam, diffuse and global irradiance;
  3. Pre-Conversion Losses: Shading, soiling and reflection losses impact incident irradiance and the sunlight available to solar cells for power conversion;
  4. Solar Cell Temperature: The calculation of cell temperature is based on ambient air temperature, irradiance, wind speed and direction, and heat fluxes from the ground surface and system materials;
  5. PV Module Output: The photovoltaic power curve is defined by a single diode model, which defines power output given variations in irradiance and temperature profiles.  Numerical simulation of the power curve is supported with R code to define the current-voltage profile of PV systems.  The code makes clear how the power curve change with variations in climate conditions.  The code is presented to support production estimates for project feasibility studies, design engineering, and real-time performance monitoring.  
  6. Array and DC String Losses: Module performance must account for mismatches in module production across the array and the impact on DC wiring losses.  Basic calculations are defined to estimate array and DC string losses;
  7. DC Maximum Power Point (MPP): DC voltage is adjusted to ensure maximum power output from the array.  Pre-inverter losses must account for variation around the MPP in order to understand net energy output;
  8. DC to AC Conversion: Inverter performance and efficiency will also impact conversion from gross to net power production;
  9. AC Losses: Balance of plant collection system losses between the inverter and the interconnect transformer are also accounted for and explained with basic calculations;
  10. Outage and Curtailments: Unplanned system or component outages, planned maintenance outages, and grid curtailments can significantly impact net power production and project returns;
  11. SCADA Data Analytics: Solar energy yields can be improved with data processing that compares system performance to project KPIs.  The objective is to refine O&M procedures, to increase project reliability, and to better manage the leveled cost of energy (LCOE).

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