pylectra.interfaces 抽象基类¶
参考资料
前置阅读： pylectra.registry
每个插件类别对应一个 ABC，定义"必须实现什么方法"。本页只列签名；详细使用例见对应的 how-to。
GeneratorModel¶
pylectra/interfaces/generator.py
class GeneratorModel(ABC):
type_id: int = 0 # 类型 id（多机分配时用）
n_states: int = 4 # 每机状态数（统一 4 列布局）
@abstractmethod
def init(self, Pgen_rows, U_rows, gen_rows, baseMVA) -> tuple[np.ndarray, np.ndarray]:
"""从潮流解 + 多机参数算稳态。返回 (Efd0 [n,], Xgen0 [n,4])。"""
@abstractmethod
def derivative(self, Xgen_rows, Xexc_rows, Xgov_rows,
Pgen_rows, Vgen_rows, freq) -> np.ndarray:
"""dXgen/dt，形状 (n, 4)。"""
@abstractmethod
def currents(self, Xgen_rows, Pgen_rows, Ubus_rows) -> tuple[np.ndarray, np.ndarray, np.ndarray]:
"""从状态 + 母线电压算 (Id, Iq, Pe)。"""
ExciterModel¶
class ExciterModel(ABC):
type_id: int = 0
n_states: int = 1
@abstractmethod
def init(self, Efd0_rows, Xgen0_rows, Pexc_rows, Vexc_rows) -> tuple[np.ndarray, np.ndarray]:
"""返回 (Xexc0 [n, n_states], Pexc0 [n, ≥7])。"""
@abstractmethod
def derivative(self, Xexc_rows, Xgen_rows, Pexc_rows, Vexc_rows, Vpss_rows) -> np.ndarray:
"""dXexc/dt，形状 (n, n_states)。"""
GovernorModel¶
class GovernorModel(ABC):
type_id: int = 0
n_states: int = 4
@abstractmethod
def init(self, Pm0_rows, Pgov_rows, omega0_rows) -> tuple[np.ndarray, np.ndarray]:
...
@abstractmethod
def derivative(self, Xgov_rows, Pgov_rows, Vgov_rows) -> np.ndarray:
...
PSSModel¶
class PSSModel(ABC):
type_id: int = 0
n_states: int = 0
@abstractmethod
def init(self, Ppss_rows) -> tuple[np.ndarray, np.ndarray]:
...
@abstractmethod
def derivative(self, Xpss_rows, Xgen_rows, Ppss_rows) -> np.ndarray:
...
ODESolver¶
class ODESolver(ABC):
engine_kind: str # "scipy" | "torch"
legacy_method_id: int | None
uses_native_engine: bool
@abstractmethod
def integrate(self, rhs, t_span, y0, events, options) -> SimulationResult:
...
PowerFlowSolver¶
class PowerFlowSolver(ABC):
@abstractmethod
def solve(self, case: NetworkCase, options: dict) -> NetworkCase:
"""返回成功标记 + 解后的 case。"""
FaultEvent¶
class FaultEvent(ABC):
@abstractmethod
def build_arrays(self) -> tuple[np.ndarray, np.ndarray, np.ndarray]:
"""返回 (event, buschange, linechange)。"""
def to_loadevents_dict(self) -> dict:
"""便利：用 dict 形式返回。默认实现已有。"""
CaseLoader¶
class CaseLoader(ABC):
name: str = ""
@abstractmethod
def load(self, identifier: str | dict) -> NetworkCase:
...
ScenarioGenerator¶
class ScenarioGenerator(ABC):
@abstractmethod
def generate(self, base_case: NetworkCase, rng: np.random.Generator) -> Scenario:
...
@dataclass
class Scenario:
case: NetworkCase
metadata: dict
SampleFilter¶
@dataclass
class FilterDecision:
passed: bool
reason: str = ""
metric: float | None = None
class SampleFilter(ABC):
name: str
@abstractmethod
def judge(self, result, scenario, case) -> FilterDecision:
...
SmallSignalAnalyzer¶
class SmallSignalAnalyzer(ABC):
@abstractmethod
def analyze(self, rhs, y0, layout, *, t0=0.0) -> SmallSignalResult:
...
PlotPlugin¶
class PlotPlugin(ABC):
name: str
input_kind: str # "single" | "batch" | "case" | "sweep" | "small_signal"
@abstractmethod
def render(self, data, ax=None, **kwargs):
"""画图，返回 Figure / Axes。"""
def expected_inputs(self) -> dict:
"""可选：声明期望的 kwargs。默认返回空 dict。"""