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github.com/cvxgrp/cvxpower
/ types & classes
Types & classes
19 in github.com/cvxgrp/cvxpower
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Functions
64
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Types & classes
19
↓ 24 callers
Class
Net
r"""Connection point for device terminals. A net defines the power balance constraint ensuring that power sums to zero across all connected t
cvxpower/network.py:70
↓ 21 callers
Class
Generator
r"""Generator with quadratic cost and optional ramp constraints. A generator has range and ramp rate constraints defining the operating regio
cvxpower/devices.py:45
↓ 19 callers
Class
FixedLoad
Fixed load. A fixed load has a specified profile :math:`l \in \mathbb{R}^T`, enforced with constraint .. math:: p = l. ..
cvxpower/devices.py:135
↓ 19 callers
Class
Group
A single device composed of multiple devices and nets. The `Group` device allows for creating new devices composed of existing base devices
cvxpower/network.py:200
↓ 8 callers
Class
Terminal
Device terminal.
cvxpower/network.py:47
↓ 8 callers
Class
TransmissionLine
Transmission line. A lossless transmission line has two terminals with power schedules :math:`p_1` and :math:`p_2`. Conservation of energy ac
cvxpower/devices.py:355
↓ 4 callers
Class
Results
Network optimization results.
cvxpower/network.py:246
↓ 2 callers
Class
DeferrableLoad
r"""Deferrable load. A deferrable load must consume a certain amount of energy :math:`E` over a flexible time horizon :math:`\tau = A,\ldots,
cvxpower/devices.py:299
↓ 2 callers
Class
Storage
r"""Storage device. A storage device either takes or delivers power with charging and discharging rates specified by the constraints ..
cvxpower/devices.py:402
↓ 2 callers
Class
ThermalLoad
r"""Thermal load. A thermal load consists of a heat store (e.g. building, refrigerator), with a temperature profile :math:`\theta \in \mathbb
cvxpower/devices.py:168
↓ 1 callers
Class
CurtailableLoad
r"""Curtailable load. A curtailable load penalizes the shortfall between a desired load profile :math:`l \in \mathbb{R}^T` and delivered powe
cvxpower/devices.py:265
↓ 1 callers
Class
GeneratorWithBidCurve
Generators with cost function specified by bid curve. Cost function will have the form: max(cost0, a_1*p + b_1, ..., a_N*p + b_N), w
examples/gen_bid_curve.py:7
↓ 1 callers
Class
OptimizationError
Error due to infeasibility or numerical problems during optimization.
cvxpower/network.py:357
Class
Device
Base class for network device. Subclasses are expected to override :attr:`constraints` and/or :attr:`cost` to define the device-specific cost
cvxpower/network.py:121
Class
DeviceTest
cvxpower/network_test.py:55
Class
DynamicTest
cvxpower/devices_test.py:204
Class
ResultsTest
cvxpower/network_test.py:35
Class
ScenarioTest
cvxpower/devices_test.py:268
Class
StaticTest
cvxpower/devices_test.py:36