Split Optimization

import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import datetime as dt
import eaopack as eao

def plot_results(portfolio, op, res, prices, num_imgs_per_row=2):
    out = eao.io.extract_output(portfolio, op, res, prices)
    num_nodes = len(portfolio.nodes)
    num_img_rows=int(np.ceil((num_nodes+2)/num_imgs_per_row))
    fig, ax = plt.subplots(num_img_rows, num_imgs_per_row, tight_layout = True, figsize=(18,5*num_img_rows))
    ax = ax.reshape(-1)

    # Plot the dispatch for each node:
    current_ax=0
    dispatch_per_node = {node: [] for node in portfolio.nodes}
    for mycol in out['dispatch'].columns.values:
        for node in dispatch_per_node:
            if '(' + node + ')' in mycol:
                dispatch_per_node[node].append(mycol)
    for node in dispatch_per_node:
        out['dispatch'][dispatch_per_node[node]].plot(ax=ax[current_ax], style='-x')
        ax[current_ax].set_title("Dispatch " + node)
        current_ax+=1

    # Plot internal variables:
    for v in out['internal_variables']:
        out['internal_variables'][v].plot(ax=ax[current_ax], style='-x', label=v)
    if out['internal_variables'].shape[1] == 0:
        ax[current_ax].text(0.4, 0.5, "No bool variables present")
    ax[current_ax].set_title('Bool Variables')
    ax[current_ax].legend()

    # Remove empty axes:
    for i in range(current_ax+1, len(ax)):
        fig.delaxes(ax[i])

Portfolio Definition

timegrid = eao.assets.Timegrid(dt.date(2021, 1, 1), dt.date(2021, 4, 1), freq='h', main_time_unit='h')

prices = {
    'price_gas': np.ones(timegrid.T)*2,
    'price_heat': np.cos(4*np.pi * np.arange(timegrid.T)/timegrid.T)+2,
    'price_power': np.sin(4*np.pi * np.arange(timegrid.T)/timegrid.T)+2,
}

prices = timegrid.prices_to_grid(prices)

prices.plot(title="Prices")

node_power = eao.assets.Node('node_power')
node_heat = eao.assets.Node('node_heat')
node_gas = eao.assets.Node('node_gas')

simple_contract_power = eao.assets.SimpleContract(name='SC_power', price='price_power', nodes=node_power,
                                             min_cap=-30., max_cap=20)
simple_contract_heat = eao.assets.SimpleContract(name='SC_heat', price='price_heat', nodes=node_heat,
                                             min_cap=-30., max_cap=20.)
simple_contract_gas = eao.assets.SimpleContract(name='SC_gas', price='price_gas', nodes=node_gas,
                                             min_cap=-30., max_cap=20.)


chpasset = eao.assets.CHPAsset(name='CHP',
                               nodes=[node_power, node_heat, node_gas],
                               min_cap=5.,
                               max_cap=30.,
                               ramp=10)
portfolio = eao.portfolio.Portfolio([chpasset, simple_contract_power, simple_contract_heat, simple_contract_gas])

Split Optimization

op_split = portfolio.setup_split_optim_problem(prices, timegrid, interval_size="1w")
res_split = op_split.optimize(solver="GLPK_MI")
print()

c:\Users\Anwender\miniconda3\envs\my_env\Lib\site-packages\eaopack\portfolio.py:244: FutureWarning: 'w' is deprecated and will be removed in a future version, please use 'W' instead.
  interval_timepoints = pd.date_range(start=timegrid.start, end=timegrid.end, freq=interval_size,

print("Value:", res_split.value)
plot_results(portfolio, op_split, res_split, prices)

Value: 23393.663322608252

Full Optimization

op_full = portfolio.setup_optim_problem(prices, timegrid)
res_full = op_full.optimize(solver="GLPK_MI")

print("Value:", res_full.value)
plot_results(portfolio, op_full, res_full, prices)

Value: 23464.337087301334