load_flattening

Solve the load flattening V2G problem

Description

load_flattening solves the load flattening optimization problem under a given scenario using either a centralized or distributed algorithm.

Syntax

[cost,u,lam,result_option] = load_flattening(scenario,algorithm_type)
[cost,u,lam,result_option] = load_flattening(scenario,algorithm_type,Name=Value)

Input Arguments

Name	Type	Description
`scenario`	Scenario object	Scenario object that specifies the optimization problem
`algorithm_type`	“cent” \| “dist”	Type of algorithm, either “cent” for centralized or “dist” for distributed algorithm

Name-Value Arguments

Name	Type	Description
`rho`	5000 (default) \| nonnegative scalar	Penalty parameter
`Lf_kP`	1 (default) \| positive scalar	Coupling gain (proportional) for distributed PI algorithm (Only for “dist”)
`Lf_kI`	1 (default) \| positive scalar	Coupling gain (integral) for distributed PI algorithm (Only for “dist”)
`Lf_time`	400 (default) \| positive scalar	Length of time interval on which PI dynamics is executed (Only for “dist”)
`Lf_dt`	0.0005 (default) \| positive scalar	Stepsize for the Euler discritization of PI dynamics (Only for “dist”)
`Lf_scale`	0.05 (default) \| positive scalar	Cost function scaling factor for PI dynamics (Only for “dist”)
`quiet`	false (default) \| logical	On/off solver messages

Output Arguments

Name	Type	Description
`cost`	scalar	Optimal cost
`u`	T×N_c matrix	Optimal charging/discharging schedule
`lam`	T×1 vector	Lagrange multiplier for balance constraint
`result_option`	struct	Specification of the options used for solver