MixSimulator

MixSimulator is an application with an optimization model for calculating and simulating the least cost of an energy mix under certain constraints. The optimizers used are based on the Nevergrad Python 3.6+ library.

The primary objective of the simulator is to study the relevance of an energy mix connected to each Inter-connected Grid through the coefficient of usage of each unit in the production cost.

Specifications :

Generic simulator, compatible with data from Madagascar and those from abroad (but may require data pre-processing beforehand);
Optimization of duty cycle (or usage coefficient) under constraints ;
Get the production cost and various performance indicators (CO2 emission, unsatisfied demand);
Estimate of the costs of a mix or a power plant over the long term ;
Comparison of the performance indicators on different optimizers.

Perspectives :

Add other constraints ;
Long-term Optimization ;
Pair with a transmission and distribution power grid simulator (MixSimulator can provide input data).

Suggestions are welcome!

How to install

It can be installed with :

pip install mixsimulator

MixSimulator is written in Python 3.6 and requires the following Python packages : nevergrad, prophet, typing, numpy, pandas and matplotlib.

How to run

As MixSimulator is a python package, it can be called and used as we can see in test.py.

List of classes and directories :

MixSimulator : System basis (Adaptation of the Nevergrad optimizers to the project and auto-parameterization) ;
nevergradBased/Optimizer : Instance of the optimizer (Receives the indications on the optimizer to choose and the parameters);
centrals/* : Gathers all the common specifications of the control units (central) ;
Evaluation : Class for evaluating mix based on performance indicators on several optimizers ;
data/ : Groups the available datasets.
documentation/ : documents about the project.

Official documentation will accompany the first release version.

Datasets

Power plants dataset

The dataset "dataset_RI_Toamasina_v2.csv" is for the test and it comes from the Inter-connected energy mix of Toamasina Madagascar (2017) and Some information from the dataset is estimated.

Dataset features needed:

tuneable (boolean): is the control unit controllable or not?
green (boolean): is it a renewable energy plant?
hydro (boolean): is it a hydro power plant?
fuel (boolean): is it a thermal power plant?
centrals : identification
fuel_consumption (g/MWh): fuel consumption (in the case of a fossil fuel power plant)
availability (%): plant availability
fuel_cost ($/g): price of fuel used
init_value ($): initial investment in setting up the plant
lifetime (years): plant lifetime
carbon_production (g/MWh): emission rate of CO2 from the power plant
raw_power (MW): nominal power of the plant
nb_employees: number of employees at the central level
mean_salary ($): average salary of plant employees
demand (MWh): electricity demand
lost (MWh): electrical loss at another level (ie: transport network)

Hydro specification :

height (meter): height of the stream ;
flow : flow of the stream ;
stock_available : water reservoir ;
capacity : max water reservoir.

nb_employees * mean_salary can be used as a variable cost of the plant if you want to directly use other informations as variable cost.

Demand and Variation datas

There is also "DIR-TOAMASINA_concat.csv" about Consumption data (in kwh, more details in Demand.py) and "dataset_RI_Toamasina_variation_template.csv" about limits in variation of power plants load following (WIP).

If you have datasets of any region in the world that can be used to evaluate our model, please contact us.

Contact

For questions and feedbacks related to the project, please send an email to r.andry.rasoanaivo@gmail.com or soloforahamefy@gmail.com or tokyandriaxel@gmail.com

Note

This project is a work in progress so it can not yet used in production (Many changes are on their way). Feedbacks are welcome!

zumpchke/MixSimulator