Use Case
When formulating an optimization problem, it would be nice to allow the flexibility metrics from the LVOF paper to be optimized for instead of just constraints.
Solution
Add functions that output the flexibility metrics (i.e., RTE, power capacity, and energy capacity) as Pyomo or CVXPY variables. A user could then use these optimization variables in an objective function if desired.
Alternatives
The existing functions in metrics.py calculate metrics for an electricity time series (i.e., after the optimization has been run). For the time being, a user could use heuristic optimization to solve the problem, check if they have met the required flexibility metrics, and if not re-solve the problem iteratively.
Use Case
When formulating an optimization problem, it would be nice to allow the flexibility metrics from the LVOF paper to be optimized for instead of just constraints.
Solution
Add functions that output the flexibility metrics (i.e., RTE, power capacity, and energy capacity) as Pyomo or CVXPY variables. A user could then use these optimization variables in an objective function if desired.
Alternatives
The existing functions in metrics.py calculate metrics for an electricity time series (i.e., after the optimization has been run). For the time being, a user could use heuristic optimization to solve the problem, check if they have met the required flexibility metrics, and if not re-solve the problem iteratively.