Source code for amplpower.core

import logging
from pathlib import Path

import numpy as np
import pandas as pd
from amplpy import AMPL
from amplpy import add_to_path
from matpowercaseframes import CaseFrames

add_to_path(r"/opt/ampl/")


[docs] def compute(args): return max(args, key=len)
def array2dict(array): """Convert a 2D numpy array to a dictionary.""" return {(i, j): array[i, j] for i in range(array.shape[0]) for j in range(array.shape[1])}
[docs] class PowerSystem:
[docs] def __init__(self, case_file: str): print(f"=======Initializing the power system with case file: {case_file}") self.case_file = case_file self.baseMVA = None self.buses = pd.DataFrame() self.generators = pd.DataFrame() self.branches = pd.DataFrame() self.gencost = pd.DataFrame() self.nbus = 0 self.nlin = 0 self.ngen = 0 self.max_angle = np.pi / 2 self.min_angle = -np.pi / 2 # Initialize everything self._load_data() self._initialize_matrices() self.compute_admittance_matrices() self.initialize() self.summary() self.compute_initial_bigm_dc() self.compute_initial_bigm_ac()
def _load_data(self): """Load MATPOWER case data into DataFrames and convert to per unit.""" try: case = CaseFrames(self.case_file) # Load data for each component self.baseMVA = case.baseMVA self.buses = case.bus self.buses.reset_index(drop=True, inplace=True) self.buses["BUS_I"] -= 1 self.generators = case.gen self.generators.reset_index(drop=True, inplace=True) self.generators["GEN_BUS"] -= 1 self.branches = case.branch self.branches.reset_index(drop=True, inplace=True) self.branches["F_BUS"] -= 1 self.branches["T_BUS"] -= 1 self.gencost = case.gencost self.gencost.reset_index(drop=True, inplace=True) self.nbus = len(self.buses) # Number of buses self.nlin = len(self.branches) # Number of branches self.ngen = len(self.generators) # Number of generators # Minimum and maximum voltage limits self.max_voltage = self.buses["VMAX"].max() self.min_voltage = self.buses["VMIN"].min() self.buses["AMAX"] = self.max_angle self.buses["AMIN"] = self.min_angle # Convert to per unit self.buses["PD"] /= self.baseMVA self.buses["QD"] /= self.baseMVA self.buses["GS"] /= self.baseMVA self.buses["BS"] /= self.baseMVA self.generators["PG"] /= self.baseMVA self.generators["QG"] /= self.baseMVA self.generators["PMAX"] /= self.baseMVA self.generators["PMIN"] /= self.baseMVA self.generators["QMAX"] /= self.baseMVA self.generators["QMIN"] /= self.baseMVA self.branches["RATE_A"] /= self.baseMVA self.branches["RATE_B"] /= self.baseMVA self.branches["RATE_C"] /= self.baseMVA # Set default branch limit self.default_branch_limit = np.sqrt(self.buses["PD"].sum() ** 2 + self.buses["QD"].sum() ** 2) for line_index in range(self.nlin): if self.branches.loc[line_index, "RATE_A"] == 0: self.branches.loc[line_index, "RATE_A"] = self.default_branch_limit except Exception as e: logging.error(f"Error loading data from {self.case_file}: {e}") raise def _initialize_matrices(self): """Initialize matrices for admittance calculations.""" self.yff = np.zeros(self.nlin, dtype=complex) self.ytf = np.zeros(self.nlin, dtype=complex) self.yft = np.zeros(self.nlin, dtype=complex) self.ytt = np.zeros(self.nlin, dtype=complex) self.cf = np.zeros((self.nlin, self.nbus)) # Connection for F_BUS self.ct = np.zeros((self.nlin, self.nbus)) # Connection for T_BUS self.cg = np.zeros((self.ngen, self.nbus)) # Connection for generators # Update generator connection matrix for g in range(self.ngen): bus = int(self.generators.iloc[g]["GEN_BUS"]) # Ensure index is an integer self.cg[g, bus] = 1
[docs] def compute_admittance_matrices(self): """Calculate the admittance matrices (yff, ytf, yft, ytt) for the network.""" for line_index in range(self.nlin): branch = self.branches.iloc[line_index] # Access branch data r = branch["BR_R"] x = branch["BR_X"] b = branch["BR_B"] tau = branch["TAP"] if branch["TAP"] != 0 else 1 # Handle TAP=0 case theta = branch["SHIFT"] # Calculate Y series and shunt admittance ys = 1 / (r + 1j * x) # Store the admittance components self.yff[line_index] = (ys + 1j * 0.5 * b) / (tau**2) self.yft[line_index] = -ys / (tau * np.exp(-1j * theta)) self.ytf[line_index] = -ys / (tau * np.exp(1j * theta)) self.ytt[line_index] = ys + 1j * 0.5 * b # Update bus connection matrices f_bus, t_bus = int(branch["F_BUS"]), int(branch["T_BUS"]) # Ensure indices are integers self.cf[line_index, f_bus] = 1 self.ct[line_index, t_bus] = 1 # Compute additional matrices self.yf = np.dot(np.diag(self.yff), self.cf) + np.dot(np.diag(self.yft), self.ct) self.yt = np.dot(np.diag(self.ytf), self.cf) + np.dot(np.diag(self.ytt), self.ct) self.ysh = self.buses["GS"].values + 1j * self.buses["BS"].values self.yb = np.dot(np.transpose(self.cf), self.yf) + np.dot(np.transpose(self.ct), self.yt) + np.diag(self.ysh) # Include admittance values in the branch DataFrame self.branches["GFF"] = np.real(self.yff) self.branches["BFF"] = np.imag(self.yff) self.branches["GFT"] = np.real(self.yft) self.branches["BFT"] = np.imag(self.yft) self.branches["GTF"] = np.real(self.ytf) self.branches["BTF"] = np.imag(self.ytf) self.branches["GTT"] = np.real(self.ytt) self.branches["BTT"] = np.imag(self.ytt)
[docs] def initialize(self, voltages=None, angles=None): """Initialize the voltage magnitudes, angles, flows, and generation levels.""" if voltages is None: voltages = np.ones(self.nbus) if angles is None: angles = np.zeros(self.nbus) self.buses["VOL0"] = voltages self.buses["ANG0"] = angles self.buses["VOLR0"] = voltages * np.cos(angles) self.buses["VOLI0"] = voltages * np.sin(angles) # Compute flows v = voltages * np.exp(1j * angles) sf = (self.cf @ v) * np.conj(self.yf @ v) st = (self.ct @ v) * np.conj(self.yt @ v) self.branches["PF0"] = np.real(sf) self.branches["QF0"] = np.imag(sf) self.branches["PT0"] = np.real(st) self.branches["QT0"] = np.imag(st) # Compute generator outputs sd = self.buses["PD"].values + 1j * self.buses["QD"].values sb = v * np.conj(self.yb @ v) sg = sb + sd self.generators["PG0"] = np.dot(np.real(sg), self.cg.T) self.generators["QG0"] = np.dot(np.imag(sg), self.cg.T)
[docs] def summary(self): """Print summary of the network.""" print(f"Number of buses: {self.nbus}") print(f"Number of lines: {self.nlin}") print(f"Number of generators: {self.ngen}") print(f"baseMVA: {self.baseMVA}") print("\nBuses:") print(self.buses.head()) print("\nGenerators:") print(self.generators.head()) print("\nBranches:") print(self.branches.head()) print("\nGenerator Costs:") print(self.gencost.head())
[docs] def compute_initial_bigm_dc(self): print("=======Computing initial bigM values for DC power flow") """Compute Big-M values for the different lines and return them in a DataFrame.""" self.branches["PFUPDC"] = (1 / self.branches["BR_X"]) * (self.cf @ self.buses["AMAX"] - self.ct @ self.buses["AMIN"]) self.branches["PFLODC"] = (1 / self.branches["BR_X"]) * (self.cf @ self.buses["AMIN"] - self.ct @ self.buses["AMAX"])
[docs] def compute_initial_bigm_ac(self): print("=======Computing initial bigM values for AC power flow") """Compute Big-M values for the different lines and return them in a DataFrame.""" v2max = self.max_voltage**2 v2min = self.min_voltage**2 cosmax = self.max_voltage**2 cosmin = 0 sinmax = self.max_voltage**2 sinmin = -(self.max_voltage**2) self.branches["PFUPAC"] = self.branches["GFF"] * v2max + self.branches["GFT"] * cosmin + self.branches["BFT"] * sinmax self.branches["PFLOAC"] = self.branches["GFF"] * v2min + self.branches["GFT"] * cosmax + self.branches["BFT"] * sinmin self.branches["PTUPAC"] = self.branches["GTT"] * v2max + self.branches["GTF"] * cosmin + self.branches["BTF"] * sinmax self.branches["PTLOAC"] = self.branches["GTT"] * v2min + self.branches["GTF"] * cosmax + self.branches["BTF"] * sinmin self.branches["QFUPAC"] = -self.branches["BFF"] * v2max - self.branches["BFT"] * cosmin + self.branches["GFT"] * sinmin self.branches["QFLOAC"] = -self.branches["BFF"] * v2min - self.branches["BFT"] * cosmax + self.branches["GFT"] * sinmax self.branches["QTUPAC"] = -self.branches["BTT"] * v2max - self.branches["BTF"] * cosmin + self.branches["GTF"] * sinmin self.branches["QTLOAC"] = -self.branches["BTT"] * v2min - self.branches["BTF"] * cosmax + self.branches["GTF"] * sinmax
# TODO: change bigm for AC case
[docs] def solve_opf(self, opf_type="dc", switching="off", connectivity="off", solver="gurobi", options="outlev=1 timelimit=3600"): """Solve the optimal power flow problem using AMPL. Parameters: opf_type (str): Type of optimal power flow ('dc', 'acrect', 'acjabr') switching (str): Switching strategy ('off', 'nl', 'bigm') connectivity (str): Connectivity for topology solutions ('off', 'on') solver (str): Solver to use ('gurobi', 'cplex', 'cbc') options (str): Options for the solver Returns: dict: Results of the optimal power flow problem """ # set the status of the lines if isinstance(switching, np.ndarray): self.branches["BR_STATUS"] = switching elif switching == "off": self.branches["BR_STATUS"] = 1 elif switching == "nl": self.branches["BR_STATUS"] = 2 elif switching == "bigm": self.branches["BR_STATUS"] = 3 print( f"=======Solving OPF ({opf_type}) with switching {switching} and connectivity {connectivity} with solver {solver} and options {options}" ) ampl = AMPL() ampl.reset() ampl.read(Path(__file__).parent / "opf.mod") ampl.set_data(self.buses, "N") ampl.set_data(self.generators, "G") ampl.set_data(self.branches, "L") ampl.set_data(self.gencost) ampl.param["CF"] = array2dict(self.cf) ampl.param["CT"] = array2dict(self.ct) ampl.param["CG"] = array2dict(self.cg) ampl.param["OPF_TYPE"] = opf_type ampl.param["CONNECTIVITY"] = connectivity ampl.param["BASEMVA"] = self.baseMVA ampl.param["MAXVOL"] = self.max_voltage ampl.param["MINVOL"] = self.min_voltage ampl.option["mp_options"] = options ampl.solve(solver=solver) solver_status = ampl.solve_result if solver_status == "solved" or solver_status == "limit": # Get the results genp_values = ampl.get_variable("genp").get_values().to_pandas().values.flatten() genq_values = ampl.get_variable("genq").get_values().to_pandas().values.flatten() gen_df = pd.DataFrame({"Pg": genp_values, "Qg": genq_values}, index=ampl.get_variable("genp").get_values().to_pandas().index) vol_values = ampl.get_variable("vol").get_values().to_pandas().values.flatten() ang_values = ampl.get_variable("ang").get_values().to_pandas().values.flatten() bus_df = pd.DataFrame({"Vm": vol_values, "Va": ang_values}, index=ampl.get_variable("vol").get_values().to_pandas().index) status_values = ampl.get_variable("status").get_values().to_pandas().values.flatten() flowpf_values = ampl.get_variable("flowpf").get_values().to_pandas().values.flatten() flowpt_values = ampl.get_variable("flowpt").get_values().to_pandas().values.flatten() flowqf_values = ampl.get_variable("flowqf").get_values().to_pandas().values.flatten() flowqt_values = ampl.get_variable("flowqt").get_values().to_pandas().values.flatten() line_df = pd.DataFrame( {"switching": status_values, "Pf": flowpf_values, "Pt": flowpt_values, "Qf": flowqf_values, "Qt": flowqt_values}, index=ampl.get_variable("status").get_values().to_pandas().index, ) return { "obj": ampl.get_objective("total_cost").value(), "time": ampl.get_value("_solve_time"), "gen": gen_df, "bus": bus_df, "lin": line_df, "status": "solved", } else: return {"obj": None, "time": None, "gen": None, "bus": None, "lin": None, "status": solver_status}