From 3ee7f5bf82033c72e449bf754278f06fecbf20ea Mon Sep 17 00:00:00 2001
From: "Mads M. Pedersen" <mmpe@dtu.dk>
Date: Tue, 15 Feb 2022 07:36:38 +0000
Subject: [PATCH] add dAEP_dxy as cost_gradient_function in
PyWakeAEPCostModelComponent
---
examples/docs/example_2_wake_comparison.py | 3 ++-
topfarm/cost_models/py_wake_wrapper.py | 30 +++++++++++++++++-----
2 files changed, 25 insertions(+), 8 deletions(-)
diff --git a/examples/docs/example_2_wake_comparison.py b/examples/docs/example_2_wake_comparison.py
index 631f25d9..5de212f4 100644
--- a/examples/docs/example_2_wake_comparison.py
+++ b/examples/docs/example_2_wake_comparison.py
@@ -58,7 +58,8 @@ def main():
def get_tf(windFarmModel):
return TopFarmProblem(
design_vars=dict(zip('xy', init_pos.T)),
- cost_comp=PyWakeAEPCostModelComponent(windFarmModel, n_wt=3, ws=10, wd=np.arange(0, 360, 12)),
+ cost_comp=PyWakeAEPCostModelComponent(windFarmModel, n_wt=3, ws=10, wd=np.arange(0, 360, 12),
+ grad_method=None),
constraints=[SpacingConstraint(min_spacing),
XYBoundaryConstraint(boundary)],
driver=EasyScipyOptimizeDriver(),
diff --git a/topfarm/cost_models/py_wake_wrapper.py b/topfarm/cost_models/py_wake_wrapper.py
index 800dc0f3..9dab4842 100644
--- a/topfarm/cost_models/py_wake_wrapper.py
+++ b/topfarm/cost_models/py_wake_wrapper.py
@@ -13,6 +13,7 @@ from scipy.interpolate.interpolate import RegularGridInterpolator
import warnings
from py_wake.flow_map import HorizontalGrid
import xarray as xr
+from py_wake.utils.gradients import autograd
class PyWakeAEP(AEPCalculator):
@@ -55,17 +56,32 @@ class PyWakeAEP(AEPCalculator):
class PyWakeAEPCostModelComponent(AEPCostModelComponent):
- def __init__(self, windFarmModel, n_wt, wd=None, ws=None, max_eval=None, **kwargs):
+ def __init__(self, windFarmModel, n_wt, wd=None, ws=None, max_eval=None, grad_method=autograd, **kwargs):
self.windFarmModel = windFarmModel
+
+ def aep(**kwargs):
+ return self.windFarmModel.aep(x=kwargs[topfarm.x_key],
+ y=kwargs[topfarm.y_key],
+ h=kwargs.get(topfarm.z_key, None),
+ type=kwargs.get(topfarm.type_key, 0),
+ wd=wd, ws=ws)
+
+ if grad_method:
+ dAEPdxy = self.windFarmModel.dAEPdxy(grad_method)
+
+ def daep(**kwargs):
+ return dAEPdxy(x=kwargs[topfarm.x_key],
+ y=kwargs[topfarm.y_key],
+ h=kwargs.get(topfarm.z_key, None),
+ type=kwargs.get(topfarm.type_key, 0),
+ wd=wd, ws=ws)
+ else:
+ daep = None
AEPCostModelComponent.__init__(self,
input_keys=[topfarm.x_key, topfarm.y_key],
n_wt=n_wt,
- cost_function=lambda **kwargs: self.windFarmModel.aep(
- x=kwargs[topfarm.x_key],
- y=kwargs[topfarm.y_key],
- h=kwargs.get(topfarm.z_key, None),
- type=kwargs.get(topfarm.type_key, 0),
- wd=wd, ws=ws),
+ cost_function=aep,
+ cost_gradient_function=daep,
output_unit='GWh',
max_eval=max_eval, **kwargs)
--
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