v1_invest_optimize_all_technologies

Complexity

Total Complexity

2

Size/Duplication

Total Lines	235
Duplicated Lines	0 %

Importance

Changes

0

1 Function

Rating	Name	Duplication	Size	Complexity
B	main()	0	152	2

# -*- coding: utf-8 -*-

"""
General description
-------------------
This example shows how to perform a capacity optimization for
an energy system with storage. The following energy system is modeled:

.. code-block:: text

                    input/output  bgas     bel
                         |          |        |
                         |          |        |
     wind(FixedSource)   |------------------>|
                         |          |        |
     pv(FixedSource)     |------------------>|
                         |          |        |
     gas_resource        |--------->|        |
     (Commodity)         |          |        |
                         |          |        |
     demand(Sink)        |<------------------|
                         |          |        |
                         |          |        |
     pp_gas(Transformer) |<---------|        |
                         |------------------>|
                         |          |        |
     storage(Storage)    |<------------------|
                         |------------------>|

The example exists in four variations. The following parameters describe
the main setting for the optimization variation 1:

    - optimize wind, pv, gas_resource and storage
    - set investment cost for wind, pv and storage
    - set gas price for kWh

    Results show an installation of wind and the use of the gas resource.
    A renewable energy share of 51% is achieved.

    Have a look at different parameter settings. There are four variations
    of this example in the same folder.

Data
----
storage_investment.csv

Installation requirements
-------------------------

This example requires oemof.solph (v0.5.x), install by:

    pip install oemof.solph[examples]


License
-------
`MIT license <https://github.com/oemof/oemof-solph/blob/dev/LICENSE>`_

"""

###############################################################################
# Imports
###############################################################################

import logging
import os
import pprint as pp
import warnings

import pandas as pd

# Default logger of oemof
from oemof.tools import economics
from oemof.tools import logger

from oemof import solph


def main():
    # Read data file
    filename = os.path.join(os.getcwd(), "storage_investmentd.csv")
    try:
        data = pd.read_csv(filename)
    except FileNotFoundError:
        msg = "Data file not found: {0}. Only one value used!"
        warnings.warn(msg.format(filename), UserWarning)
        data = pd.DataFrame(
            {"pv": [0.3, 0.5], "wind": [0.6, 0.8], "demand_el": [500, 600]}
        )

    number_timesteps = len(data)

    ##########################################################################
    # Initialize the energy system and read/calculate necessary parameters
    ##########################################################################

    logger.define_logging()
    logging.info("Initialize the energy system")
    date_time_index = solph.create_time_index(2012, number=number_timesteps)
    energysystem = solph.EnergySystem(
        timeindex=date_time_index, infer_last_interval=False
    )

    price_gas = 0.04

    # If the period is one year the equivalent periodical costs (epc) of an
    # investment are equal to the annuity. Use oemof's economic tools.
    epc_wind = economics.annuity(capex=1000, n=20, wacc=0.05)
    epc_pv = economics.annuity(capex=1000, n=20, wacc=0.05)
    epc_storage = economics.annuity(capex=1000, n=20, wacc=0.05)

    ##########################################################################
    # Create oemof objects
    ##########################################################################

    logging.info("Create oemof objects")
    # create natural gas bus
    bgas = solph.Bus(label="natural_gas")

    # create electricity bus
    bel = solph.Bus(label="electricity")

    energysystem.add(bgas, bel)

    # create excess component for the electricity bus to allow overproduction
    excess = solph.components.Sink(
        label="excess_bel", inputs={bel: solph.Flow()}
    )

    # create source object representing the gas commodity (annual limit)
    gas_resource = solph.components.Source(
        label="rgas", outputs={bgas: solph.Flow(variable_costs=price_gas)}
    )

    # create fixed source object representing wind power plants
    wind = solph.components.Source(
        label="wind",
        outputs={
            bel: solph.Flow(
                fix=data["wind"],
                investment=solph.Investment(ep_costs=epc_wind),
            )
        },
    )

    # create fixed source object representing pv power plants
    pv = solph.components.Source(
        label="pv",
        outputs={
            bel: solph.Flow(
                fix=data["pv"], investment=solph.Investment(ep_costs=epc_pv)
            )
        },
    )

    # create simple sink object representing the electrical demand
    demand = solph.components.Sink(
        label="demand",
        inputs={bel: solph.Flow(fix=data["demand_el"], nominal_value=1)},
    )

    # create simple transformer object representing a gas power plant
    pp_gas = solph.components.Transformer(
        label="pp_gas",
        inputs={bgas: solph.Flow()},
        outputs={bel: solph.Flow(nominal_value=10e10, variable_costs=0)},
        conversion_factors={bel: 0.58},
    )

    # create storage object representing a battery
    storage = solph.components.GenericStorage(
        label="storage",
        inputs={bel: solph.Flow(variable_costs=0.0001)},
        outputs={bel: solph.Flow()},
        loss_rate=0.00,
        initial_storage_level=0,
        invest_relation_input_capacity=1 / 6,
        invest_relation_output_capacity=1 / 6,
        inflow_conversion_factor=1,
        outflow_conversion_factor=0.8,
        investment=solph.Investment(ep_costs=epc_storage),
    )

    energysystem.add(excess, gas_resource, wind, pv, demand, pp_gas, storage)

    ##########################################################################
    # Optimise the energy system
    ##########################################################################

    logging.info("Optimise the energy system")

    # initialise the operational model
    om = solph.Model(energysystem)

    # if tee_switch is true solver messages will be displayed
    logging.info("Solve the optimization problem")
    om.solve(solver="cbc", solve_kwargs={"tee": True})

    ##########################################################################
    # Check and plot the results
    ##########################################################################

    # check if the new result object is working for custom components
    results = solph.processing.results(om)

    electricity_bus = solph.views.node(results, "electricity")

    meta_results = solph.processing.meta_results(om)
    pp.pprint(meta_results)

    my_results = electricity_bus["scalars"]

    # installed capacity of storage in GWh
    my_results["storage_invest_GWh"] = (
        results[(storage, None)]["scalars"]["invest"] / 1e6
    )

    # installed capacity of wind power plant in MW
    my_results["wind_invest_MW"] = (
        results[(wind, bel)]["scalars"]["invest"] / 1e3
    )

    # resulting renewable energy share
    my_results["res_share"] = (
        1
        - results[(pp_gas, bel)]["sequences"].sum()
        / results[(bel, demand)]["sequences"].sum()
    )

    pp.pprint(my_results)


if __name__ == "__main__":
    main()