Page 144 - Applied Photovoltaics

Costing may be done purely on an initial cost basis, or else a lifetime cost basis,
depending on consumer preference. For the latter, battery life, which varies
significantly with temperature and depth-of-discharge (DOD), must be considered.
The battery life for flooded lead-acid batteries can be estimated from

CL ( 89 . 59 194 . 29 T e ) . 1 75 DOD (7.2)

where CL is the battery life (in cycles), T is the battery temperature and DOD is the
depth-of-discharge.

In a PV-storage system, the DOD varies from cycle to cycle. We define each cycle as
one day, and DOD as the maximum DOD for that day. It has been shown statistically
that the distribution of DODs for all battery cycles can be generalised as a function of
the LOLP and the days of storage, thus enabling Eqn. (7.2) to be used to give a close
estimate of actual battery life.

A complete design example using this approach is provided in Appendix E. In
principal, it has a great deal of merit, overcoming many of the limitations associated
with the procedures used in the simplified method given in Section 7.4. However, it
also has two significant limitations:
1. It is difficult to check the system design unless the designer is given more
details regarding the derivation of the various graphs (nomograms) on which
the design procedures are based.

2. By optimising the design for the worst winter month, there is no checking
procedure to ensure that summer months are not excessively disadvantaged.

7.6 AUSTRALIAN STANDARD AS4509.2
This Australian Standard (Standards Australia, 2002) provides some guidelines, a
worked example and blank worksheets for system design. It includes sections on
electrical load assessment and the design procedure explicitly considers incorporation
of other renewable energy generators and backup (fossil fuel) generation, considering
in detail their interconnection. The worked example in its appendices is not
prescriptive, explicitly stating that “other methods may be equally applicable”.
The main PV-related design steps are:
1. Estimation of DC and AC electrical loads and their seasonal variation.

2. Scale up of the load by an oversupply coefficient in the range 1.3–2.0,
depending on reliability of insolation data and load criticality, if the available
insolation data is only annual average, monthly or ‘worst month’.
3. Energy resource assessment, from on-site measurements or available data.
4. Determination of the worst and best months, based on the smallest and largest
ratio of solar energy to load energy.
5. System configuration, including range of accessible energy sources and
genset, if required. Inclusion of a genset allows the specification of a smaller
array and smaller battery for equivalent system availability.

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