--- jupytext: text_representation: extension: .md format_name: myst format_version: 0.13 jupytext_version: 1.10.3 kernelspec: display_name: Python 3 language: python name: python3 ---
### Calculation All the equations below are valid for any realization and are therefore implicitly indexed by test case. Let be $x_{n, e}$ the value returned by this KPI for a given node $n$ and energy $e$ and $A_{n,e}^{lol}$ the set of loss of load assets producing energy $e$ at node $n$. We can then express $x_{n, e}$ as : $$ x_{n, e} = \frac{\sum_t{f_{n, e}(t)}}{N_h} $$ with: - $f_{n, e}(t) = \begin{cases} \quad 1 \text{ if} \sum\limits_{a \in A_{n,e}^{lol}} p_{a, n, e}(t) \geq 10^{-3}\\ \quad 0 \text{ otherwise} \end{cases}$ A threshold of one kw is set to avoid taking into account hours when demand peak shaving is insignificant. *Global variables and parameters notations definitions can be consulted [here](../notations.md).* ### Indexing - The energy index of this KPI refers to the produced energy of Loss of load assets - The node index of this KPI refers to the node consuming the energy produced by Loss of load assets - The test case index corresponds the test case of the realization variables and parameters are taken fromModelling hint
The usual threshold for determining whether a system is undersized in terms of production is around 3 hours. If, for example, a country has 40 hours of Loss of Load for a given energy, it is undersized for that energy. It considers the fact that if the LOL is “too large”, then additional capacities (power plants or batteries) need to be built to ensure adequacy in the system.