Home Solar Batteries: 2.1c Charging - Daily PV Model

Home Solar Batteries - Modelling Performance

Introduction

This post specifically addresses the charging of domestic battery systems using solar PV and forms part of a series of entries looking to establish a reasonable view as to how the combination of solar PV and battery storage system should be modelled to ensure that information available to consumers should be considered accurate enough to establish a reasonable justification for investment in storage technologies.

If this is the first time you've accessed this information it is recommended that all of the relevant posts are considered in order through accessing the 'relevant posts' links

Daily PV Model

In simple terms there is little difference between the Monthly & Daily models. Effectively all that would tend to happen is that the estimated energy generation over a month is divided by the number of available days. Although there is a (debatable) advantage to be derived from being able to build a usage model matching some form of variance in daily household energy demand, the issue remains that the daily generation is assumed to be constant throughout the period.

1. Derived from Annual figure via Monthly

The most basic form of estimating the amount of energy which is potentially available to charge the battery system would be by estimating annual generation & apportioning relative to monthly generation, before further sub-allocating the figures to a daily resolution.

Apportionment is necessary due to the variability of monthly generation throughout the year. To provide an idea as to the asymmetry of the monthly generation pattern, here we have a representation of the generation by month for a typical SW facing UK system (with minor Winter shading) over a 6 year basis, along with the period average.

Solar PV - % of Annual Generation by Month (6Yr Av)

Apportioning the monthly energy genertation to daily data for onward modelling is simply a matter of dividing the monthly totals by the number of days in that month.

Basing the apportionment on percentages derived from the above (amongst many other sources of a fixed percentage) to a 3400kWh annual generation would result in gross generation of around 14.7kWh/day ((3400x13%)/30) in June and 2.2kWh/day ((3400x2%)/31) in December.

2. PV Generation Estimation Tool

The Daily derived method effectively employs a standard percentage for each day within the month and applies this across all energy apportionment assessments.

As with the Monthly derived approach discussed earlier, accuracy can be improved by utilising tools such as PVGIS-4 (or the later PVGIS-5) to create site specific generation estimates which take location, orientation and actual panel inclinations into account.

In the example here we see that a specific location 4kWp system would be expected to generate a total of 3560kWh per year, in which an average of 15.30kWh/day would be expected to be generated in June and 3.24kWh/day in December.

3. Historical Site Data

In the case where a PV system already exists it may be possible to use actual site generation data either from records kept by the homeowner, such as FiT (feed in Tariff) submission records etc, or through downloading daily generation figure directly from the inverter or accumulated data systems such as PVOutput. It is important to note that unless the recorded data is available on a daily basis, there is no real advantage in attempting to calculate to a level of detail which doesn't exist.

3. Daily Modelling

Home Solar Battery - Daily Generation Model

The above chart represents daily demand & generation for a UK household having average annual electricity consumption with solar PV generation being estimated using PVGIS-4.

As alluded to earlier, other than the energy scale changing to show daily generation and consumption there is really no appreciable advantage of looking at the position on a daily basis over doing so monthly.

Summary

In reality, unless the ability exists to accurately match daily generation & consumption patterns, there is little advantage in addressing solar PV generation on a daily basis over doing so as monthly totals, with this being the case for all generation estimation options described above.

Where battery storage options are planned to be installed in households where demand is monitored by smart meters, there may be an advantage from employing or analysing historical data, however, any results would still effectively be based on average monthly generation totals unless definite daily repeatable patterns exist on the demand side.