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Implementation of feature 720 asym_line #762

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Implementation of feature 720 asym_line #762

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49 changes: 49 additions & 0 deletions code_generation/data/attribute_classes/input.json
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Original file line number Diff line number Diff line change
Expand Up @@ -127,6 +127,55 @@
}
]
},
{
"name": "AsymLineInput",
"base": "BranchInput",
"attributes": [
{
"data_type": "double",
"names": [
"r_aa",
"r_ba",
"r_bb",
"r_ca",
"r_cb",
"r_cc",
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"r_na",
"r_nb",
"r_nc",
"r_nn",
"x_aa",
"x_ba",
"x_bb",
"x_ca",
"x_cb",
"x_cc",
"x_na",
"x_nb",
"x_nc",
"x_nn",
"c_aa",
"c_ba",
"c_bb",
"c_ca",
"c_cb",
"c_cc",
"c_na",
"c_nb",
"c_nc",
"c_nn",
"c0",
"c1"
],
"description": "Lower triangle matrix values for R, X and C matrices"
},
{
"data_type": "double",
"names": "i_n",
"description": "rated current"
}
]
},
{
"name": "GenericBranchInput",
"base": "BranchInput",
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12 changes: 10 additions & 2 deletions code_generation/data/dataset_class_maps/dataset_definitions.json
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Original file line number Diff line number Diff line change
Expand Up @@ -12,6 +12,10 @@
"names": ["line"],
"class_name": "LineInput"
},
{
"names": ["asym_line"],
"class_name": "AsymLineInput"
},
{
"names": ["link"],
"class_name": "LinkInput"
Expand Down Expand Up @@ -67,7 +71,7 @@
"class_name": "NodeOutput"
},
{
"names": ["line", "link", "transformer", "generic_branch"],
"names": ["line", "link", "transformer", "generic_branch", "asym_line"],
"class_name": "BranchOutput"
},
{
Expand Down Expand Up @@ -108,6 +112,10 @@
"names": ["line"],
"class_name": "BranchUpdate"
},
{
"names": ["asym_line"],
"class_name": "BranchUpdate"
},
{
"names": ["link"],
"class_name": "BranchUpdate"
Expand Down Expand Up @@ -159,7 +167,7 @@
"class_name": "NodeShortCircuitOutput"
},
{
"names": ["line", "link", "transformer"],
"names": ["line", "link", "transformer", "asym_line"],
"class_name": "BranchShortCircuitOutput"
},
{
Expand Down
3 changes: 2 additions & 1 deletion power_grid_model_c/power_grid_model/include/power_grid_model/all_components.hpp
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Original file line number Diff line number Diff line change
Expand Up @@ -12,6 +12,7 @@
#include "component/fault.hpp"
#include "component/generic_branch.hpp"
#include "component/line.hpp"
#include "component/asym_line.hpp"
#include "component/link.hpp"
#include "component/load_gen.hpp"
#include "component/node.hpp"
Expand All @@ -27,7 +28,7 @@
namespace power_grid_model {

using AllComponents =
ComponentList<Node, Line, Link, GenericBranch, Transformer, ThreeWindingTransformer, Shunt, Source, SymGenerator,
ComponentList<Node, Line, AsymLine, Link, GenericBranch, Transformer, ThreeWindingTransformer, Shunt, Source, SymGenerator,
AsymGenerator, SymLoad, AsymLoad, SymPowerSensor, AsymPowerSensor, SymVoltageSensor,
AsymVoltageSensor, Fault, TransformerTapRegulator>;

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49 changes: 49 additions & 0 deletions power_grid_model_c/power_grid_model/include/power_grid_model/auxiliary/input.hpp
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Original file line number Diff line number Diff line change
Expand Up @@ -98,6 +98,55 @@ struct LineInput {
operator BranchInput const&() const { return reinterpret_cast<BranchInput const&>(*this); }
};

struct AsymLineInput {
ID id{na_IntID}; // ID of the object
ID from_node{na_IntID}; // node IDs to which this branch is connected at both sides
ID to_node{na_IntID}; // node IDs to which this branch is connected at both sides
IntS from_status{na_IntS}; // whether the branch is connected at each side
IntS to_status{na_IntS}; // whether the branch is connected at each side
double r_aa{nan}; // Lower triangle matrix values for R, X and C matrices
double r_ba{nan}; // Lower triangle matrix values for R, X and C matrices
double r_bb{nan}; // Lower triangle matrix values for R, X and C matrices
double r_ca{nan}; // Lower triangle matrix values for R, X and C matrices
double r_cb{nan}; // Lower triangle matrix values for R, X and C matrices
double r_cc{nan}; // Lower triangle matrix values for R, X and C matrices
double r_na{nan}; // Lower triangle matrix values for R, X and C matrices
double r_nb{nan}; // Lower triangle matrix values for R, X and C matrices
double r_nc{nan}; // Lower triangle matrix values for R, X and C matrices
double r_nn{nan}; // Lower triangle matrix values for R, X and C matrices
double x_aa{nan}; // Lower triangle matrix values for R, X and C matrices
double x_ba{nan}; // Lower triangle matrix values for R, X and C matrices
double x_bb{nan}; // Lower triangle matrix values for R, X and C matrices
double x_ca{nan}; // Lower triangle matrix values for R, X and C matrices
double x_cb{nan}; // Lower triangle matrix values for R, X and C matrices
double x_cc{nan}; // Lower triangle matrix values for R, X and C matrices
double x_na{nan}; // Lower triangle matrix values for R, X and C matrices
double x_nb{nan}; // Lower triangle matrix values for R, X and C matrices
double x_nc{nan}; // Lower triangle matrix values for R, X and C matrices
double x_nn{nan}; // Lower triangle matrix values for R, X and C matrices
double c_aa{nan}; // Lower triangle matrix values for R, X and C matrices
double c_ba{nan}; // Lower triangle matrix values for R, X and C matrices
double c_bb{nan}; // Lower triangle matrix values for R, X and C matrices
double c_ca{nan}; // Lower triangle matrix values for R, X and C matrices
double c_cb{nan}; // Lower triangle matrix values for R, X and C matrices
double c_cc{nan}; // Lower triangle matrix values for R, X and C matrices
double c_na{nan}; // Lower triangle matrix values for R, X and C matrices
double c_nb{nan}; // Lower triangle matrix values for R, X and C matrices
double c_nc{nan}; // Lower triangle matrix values for R, X and C matrices
double c_nn{nan}; // Lower triangle matrix values for R, X and C matrices
double c0{nan}; // Lower triangle matrix values for R, X and C matrices
double c1{nan}; // Lower triangle matrix values for R, X and C matrices
double i_n{nan}; // rated current

// implicit conversions to BaseInput
operator BaseInput&() { return reinterpret_cast<BaseInput&>(*this); }
operator BaseInput const&() const { return reinterpret_cast<BaseInput const&>(*this); }

// implicit conversions to BranchInput
operator BranchInput&() { return reinterpret_cast<BranchInput&>(*this); }
operator BranchInput const&() const { return reinterpret_cast<BranchInput const&>(*this); }
};

struct GenericBranchInput {
ID id{na_IntID}; // ID of the object
ID from_node{na_IntID}; // node IDs to which this branch is connected at both sides
Expand Down
46 changes: 46 additions & 0 deletions power_grid_model_c/power_grid_model/include/power_grid_model/auxiliary/meta_gen/input.hpp
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Expand Up @@ -111,6 +111,52 @@ struct get_attributes_list<LineInput> {
};
};

template<>
struct get_attributes_list<AsymLineInput> {
static constexpr std::array<MetaAttribute, 38> value{
// all attributes including base class

meta_data_gen::get_meta_attribute<&AsymLineInput::id>(offsetof(AsymLineInput, id), "id"),
meta_data_gen::get_meta_attribute<&AsymLineInput::from_node>(offsetof(AsymLineInput, from_node), "from_node"),
meta_data_gen::get_meta_attribute<&AsymLineInput::to_node>(offsetof(AsymLineInput, to_node), "to_node"),
meta_data_gen::get_meta_attribute<&AsymLineInput::from_status>(offsetof(AsymLineInput, from_status), "from_status"),
meta_data_gen::get_meta_attribute<&AsymLineInput::to_status>(offsetof(AsymLineInput, to_status), "to_status"),
meta_data_gen::get_meta_attribute<&AsymLineInput::r_aa>(offsetof(AsymLineInput, r_aa), "r_aa"),
meta_data_gen::get_meta_attribute<&AsymLineInput::r_ba>(offsetof(AsymLineInput, r_ba), "r_ba"),
meta_data_gen::get_meta_attribute<&AsymLineInput::r_bb>(offsetof(AsymLineInput, r_bb), "r_bb"),
meta_data_gen::get_meta_attribute<&AsymLineInput::r_ca>(offsetof(AsymLineInput, r_ca), "r_ca"),
meta_data_gen::get_meta_attribute<&AsymLineInput::r_cb>(offsetof(AsymLineInput, r_cb), "r_cb"),
meta_data_gen::get_meta_attribute<&AsymLineInput::r_cc>(offsetof(AsymLineInput, r_cc), "r_cc"),
meta_data_gen::get_meta_attribute<&AsymLineInput::r_na>(offsetof(AsymLineInput, r_na), "r_na"),
meta_data_gen::get_meta_attribute<&AsymLineInput::r_nb>(offsetof(AsymLineInput, r_nb), "r_nb"),
meta_data_gen::get_meta_attribute<&AsymLineInput::r_nc>(offsetof(AsymLineInput, r_nc), "r_nc"),
meta_data_gen::get_meta_attribute<&AsymLineInput::r_nn>(offsetof(AsymLineInput, r_nn), "r_nn"),
meta_data_gen::get_meta_attribute<&AsymLineInput::x_aa>(offsetof(AsymLineInput, x_aa), "x_aa"),
meta_data_gen::get_meta_attribute<&AsymLineInput::x_ba>(offsetof(AsymLineInput, x_ba), "x_ba"),
meta_data_gen::get_meta_attribute<&AsymLineInput::x_bb>(offsetof(AsymLineInput, x_bb), "x_bb"),
meta_data_gen::get_meta_attribute<&AsymLineInput::x_ca>(offsetof(AsymLineInput, x_ca), "x_ca"),
meta_data_gen::get_meta_attribute<&AsymLineInput::x_cb>(offsetof(AsymLineInput, x_cb), "x_cb"),
meta_data_gen::get_meta_attribute<&AsymLineInput::x_cc>(offsetof(AsymLineInput, x_cc), "x_cc"),
meta_data_gen::get_meta_attribute<&AsymLineInput::x_na>(offsetof(AsymLineInput, x_na), "x_na"),
meta_data_gen::get_meta_attribute<&AsymLineInput::x_nb>(offsetof(AsymLineInput, x_nb), "x_nb"),
meta_data_gen::get_meta_attribute<&AsymLineInput::x_nc>(offsetof(AsymLineInput, x_nc), "x_nc"),
meta_data_gen::get_meta_attribute<&AsymLineInput::x_nn>(offsetof(AsymLineInput, x_nn), "x_nn"),
meta_data_gen::get_meta_attribute<&AsymLineInput::c_aa>(offsetof(AsymLineInput, c_aa), "c_aa"),
meta_data_gen::get_meta_attribute<&AsymLineInput::c_ba>(offsetof(AsymLineInput, c_ba), "c_ba"),
meta_data_gen::get_meta_attribute<&AsymLineInput::c_bb>(offsetof(AsymLineInput, c_bb), "c_bb"),
meta_data_gen::get_meta_attribute<&AsymLineInput::c_ca>(offsetof(AsymLineInput, c_ca), "c_ca"),
meta_data_gen::get_meta_attribute<&AsymLineInput::c_cb>(offsetof(AsymLineInput, c_cb), "c_cb"),
meta_data_gen::get_meta_attribute<&AsymLineInput::c_cc>(offsetof(AsymLineInput, c_cc), "c_cc"),
meta_data_gen::get_meta_attribute<&AsymLineInput::c_na>(offsetof(AsymLineInput, c_na), "c_na"),
meta_data_gen::get_meta_attribute<&AsymLineInput::c_nb>(offsetof(AsymLineInput, c_nb), "c_nb"),
meta_data_gen::get_meta_attribute<&AsymLineInput::c_nc>(offsetof(AsymLineInput, c_nc), "c_nc"),
meta_data_gen::get_meta_attribute<&AsymLineInput::c_nn>(offsetof(AsymLineInput, c_nn), "c_nn"),
meta_data_gen::get_meta_attribute<&AsymLineInput::c0>(offsetof(AsymLineInput, c0), "c0"),
meta_data_gen::get_meta_attribute<&AsymLineInput::c1>(offsetof(AsymLineInput, c1), "c1"),
meta_data_gen::get_meta_attribute<&AsymLineInput::i_n>(offsetof(AsymLineInput, i_n), "i_n"),
};
};

template<>
struct get_attributes_list<GenericBranchInput> {
static constexpr std::array<MetaAttribute, 12> value{
Expand Down
19 changes: 19 additions & 0 deletions ...grid_model_c/power_grid_model/include/power_grid_model/auxiliary/static_asserts/input.hpp
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Expand Up @@ -70,6 +70,25 @@ static_assert(offsetof(LineInput, to_node) == offsetof(BranchInput, to_node));
static_assert(offsetof(LineInput, from_status) == offsetof(BranchInput, from_status));
static_assert(offsetof(LineInput, to_status) == offsetof(BranchInput, to_status));

// static asserts for AsymLineInput
static_assert(std::is_standard_layout_v<AsymLineInput>);
// static asserts for conversion of AsymLineInput to BaseInput
static_assert(std::alignment_of_v<AsymLineInput> >= std::alignment_of_v<BranchInput>);
static_assert(std::same_as<decltype(AsymLineInput::id), decltype(BaseInput::id)>);
static_assert(offsetof(AsymLineInput, id) == offsetof(BaseInput, id));
// static asserts for conversion of AsymLineInput to BranchInput
static_assert(std::alignment_of_v<AsymLineInput> >= std::alignment_of_v<BranchInput>);
static_assert(std::same_as<decltype(AsymLineInput::id), decltype(BranchInput::id)>);
static_assert(std::same_as<decltype(AsymLineInput::from_node), decltype(BranchInput::from_node)>);
static_assert(std::same_as<decltype(AsymLineInput::to_node), decltype(BranchInput::to_node)>);
static_assert(std::same_as<decltype(AsymLineInput::from_status), decltype(BranchInput::from_status)>);
static_assert(std::same_as<decltype(AsymLineInput::to_status), decltype(BranchInput::to_status)>);
static_assert(offsetof(AsymLineInput, id) == offsetof(BranchInput, id));
static_assert(offsetof(AsymLineInput, from_node) == offsetof(BranchInput, from_node));
static_assert(offsetof(AsymLineInput, to_node) == offsetof(BranchInput, to_node));
static_assert(offsetof(AsymLineInput, from_status) == offsetof(BranchInput, from_status));
static_assert(offsetof(AsymLineInput, to_status) == offsetof(BranchInput, to_status));

// static asserts for GenericBranchInput
static_assert(std::is_standard_layout_v<GenericBranchInput>);
// static asserts for conversion of GenericBranchInput to BaseInput
Expand Down
1 change: 1 addition & 0 deletions power_grid_model_c/power_grid_model/include/power_grid_model/common/common.hpp
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Expand Up @@ -56,6 +56,7 @@ using DoubleComplex = std::complex<double>;
using std::numbers::inv_sqrt3;
using std::numbers::pi;
using std::numbers::sqrt3;
using std::numbers::e;
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with this being in the full namespace of this project, i'm a little bit hesitant to add single-letter names here. let's think about whether this is the way to go or whether it's preferable to just use std::numbers::e where it's used (since it's not that common in the code base anyways). alternatively, we can put them all in a power_grid_model::numbers namespace and expose only the longer ones outside.

namespace numbers {
using std::numbers::inv_sqrt3;
using std::numbers::pi;
using std::numbers::sqrt3;
using std::numbers::e;
} // namespace numbers

using numbers::inv_sqrt3;
using numbers::pi;
using numbers::sqrt3;


constexpr DoubleComplex a2{-0.5, -sqrt3 / 2.0};
constexpr DoubleComplex a{-0.5, sqrt3 / 2.0};
Expand Down
11 changes: 11 additions & 0 deletions power_grid_model_c/power_grid_model/include/power_grid_model/common/exception.hpp
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Expand Up @@ -59,6 +59,17 @@ class MissingCaseForEnumError : public InvalidArguments {
}
};

class UnsupportedInputDescriptionAsymLine : public PowerGridError {
public:
UnsupportedInputDescriptionAsymLine() {
append_msg("Invalid or missing parameters supplied for component asym_line. The following input specifications are allowed");
append_msg("3 phase x_matrix, 3 phase r_matrix and 3 phase c_matrix");
append_msg("3 phase + neutral x_matrix, 3 phase + neutral r_matrix and 3 phase + neutral c_matrix");
append_msg("3 phase x_matrix, 3 phase r_matrix and c1, c0");
append_msg("3 phase + neutral x_matrix, 3 phase + neutral r_matrix and c1, c0");
}
};
Comment on lines +62 to +71
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i don't think we explicitly check input parameters in any of the other components. only things like ID references to other components are checked. I would just consider this UB (undefined behavior; in this case in particular unspecified behavior). The data validator in Python can check that it is supported, but the core should not.


class ConflictVoltage : public PowerGridError {
public:
ConflictVoltage(ID id, ID id1, ID id2, double u1, double u2) {
Expand Down
20 changes: 20 additions & 0 deletions power_grid_model_c/power_grid_model/include/power_grid_model/common/three_phase_tensor.hpp
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Expand Up @@ -22,6 +22,7 @@ namespace three_phase_tensor {

template <class T> using Eigen3Vector = Eigen::Array<T, 3, 1>;
template <class T> using Eigen3Tensor = Eigen::Array<T, 3, 3, Eigen::ColMajor>;
template <class T> using Eigen4Tensor = Eigen::Array<T, 4, 4, Eigen::ColMajor>;
template <class T> using Eigen3DiagonalTensor = Eigen::DiagonalMatrix<T, 3>;

template <scalar_value T> class Vector : public Eigen3Vector<T> {
Expand Down Expand Up @@ -61,6 +62,8 @@ template <scalar_value T> class Tensor : public Eigen3Tensor<T> {
// additional constructors
explicit Tensor(T const& x) { (*this) << x, 0.0, 0.0, 0.0, x, 0.0, 0.0, 0.0, x; }
explicit Tensor(T const& s, T const& m) { (*this) << s, m, m, m, s, m, m, m, s; }
explicit Tensor(T const& x1, T const& x2, T const& x3, T const& x4, T const& x5, T const& x6) { (*this) << x1, x2, x4, x2, x3, x5, x4, x5, x6; }
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i'd go for something more explicit. It's very easy to make a mistake in the order.

A proposal is the one below (BEWARE: this changes the order, so usage needs to be adjusted)

Suggested change
explicit Tensor(T const& x1, T const& x2, T const& x3, T const& x4, T const& x5, T const& x6) { (*this) << x1, x2, x4, x2, x3, x5, x4, x5, x6; }
explicit Tensor(T const& s1, T const& s2, T const& s3, T const& m12, T const& m13, T const& m23) { (*this) << s1, m12, m13, m12, s2, m23, m13, m23, s3; }

alternatively, you can provide 2 Vector<T> as input for readability

explicit Tensor(T const& x1, T const& x2, T const& x3, T const& x4, T const& x5, T const& x6, T const& x7, T const& x8, T const& x9) { (*this) << x1, x2, x3, x4, x5, x6, x7, x8, x9; }
explicit Tensor(Vector<T> const& v) { (*this) << v(0), 0.0, 0.0, 0.0, v(1), 0.0, 0.0, 0.0, v(2); }
// eigen expression
template <typename OtherDerived> Tensor(Eigen::ArrayBase<OtherDerived> const& other) : Eigen3Tensor<T>{other} {}
Expand All @@ -70,6 +73,22 @@ template <scalar_value T> class Tensor : public Eigen3Tensor<T> {
}
};

template <scalar_value T> class Tensor4 : public Eigen4Tensor<T> {
public:
Tensor4() { (*this) = Eigen4Tensor<T>::Zero(); }
// additional constructors
explicit Tensor4(T const& x) { (*this) << x, 0.0, 0.0, 0.0, 0.0, x, 0.0, 0.0, 0.0, 0.0, x, 0.0, 0.0, 0.0, 0.0, x; }
explicit Tensor4(T const& s, T const& m) { (*this) << s, m, m, m, m, s, m, m, m, m, s, m, m, m, m, s; }
explicit Tensor4(T const& x1, T const& x2, T const& x3, T const& x4, T const& x5, T const& x6, T const& x7, T const& x8, T const& x9, T const& x10) { (*this) << x1, x2, x4, x7, x2, x3, x5, x8, x4, x5, x6, x9, x7, x8, x9, x10; }
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idem to my comment on Tensor3

explicit Tensor4(Vector<T> const& v) { (*this) << v(0), 0.0, 0.0, 0.0, 0.0, v(1), 0.0, 0.0, 0.0, 0.0, v(2), 0.0, 0.0, 0.0, 0.0, v(3); }
// eigen expression
template <typename OtherDerived> Tensor4(Eigen::ArrayBase<OtherDerived> const& other) : Eigen4Tensor<T>{other} {}
template <typename OtherDerived> Tensor4& operator=(Eigen::ArrayBase<OtherDerived> const& other) {
this->Eigen4Tensor<T>::operator=(other);
return *this;
}
};

template <scalar_value T> class DiagonalTensor : public Eigen3DiagonalTensor<T> {
public:
DiagonalTensor() { (*this).setZero(); }
Expand All @@ -92,6 +111,7 @@ template <symmetry_tag sym>
using RealTensor = std::conditional_t<is_symmetric_v<sym>, double, three_phase_tensor::Tensor<double>>;
template <symmetry_tag sym>
using ComplexTensor = std::conditional_t<is_symmetric_v<sym>, DoubleComplex, three_phase_tensor::Tensor<DoubleComplex>>;
using ComplexTensor4 = three_phase_tensor::Tensor4<DoubleComplex>;

template <symmetry_tag sym>
using RealDiagonalTensor = std::conditional_t<is_symmetric_v<sym>, double, three_phase_tensor::DiagonalTensor<double>>;
Expand Down
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