Optimization and Electricity Market

Optimization and Electricity Market#

Overview: NumPy-Pandas-LP-Basics#

Objective#

This section provides a comprehensive introduction to numerical computing and optimization using NumPy, Pandas, and Linear Programming. These three foundational tools are essential for data science, engineering, and operational research, forming the computational backbone for large-scale numerical analysis and decision-making problems. The primary goal is to equip learners with the ability to manipulate structured data efficiently, perform high-speed numerical computations, and model real-world optimization problems using Python.

  1. NumPy: Introduces array-based computing for efficient numerical operations.

  2. Pandas: Focuses on structured data manipulation and analysis.

  3. Linear Programming (LP): Explores mathematical optimization techniques using GurobiPy.

1.2 Key Components#

1. NumPy Fundamentals#

  • Creating NumPy Arrays

  • Array Attributes

  • Indexing and Slicing

  • Mathematical Operations

  • Reshaping and Transposing Arrays

  • Statistical Functions

  • Stacking and Concatenation

2. Pandas for Data Analysis#

  • Creating Data Structures

  • Reading and Writing Data

  • Data Inspection and Manipulation

  • Data Cleaning

  • Modifying Data

  • Merging and Joining Data

  • Pivot Tables and Crosstabs

3. Linear Programming basics#

  • Introduction to LP Optimization Models

  • Using Gurobi for Linear Programming

  • Solving Optimization Models

Overview: An example of a power system optimization problem#

Objective#

This module leverages cyber infrastructure to conduct a day-ahead economic dispatch on a modified PJM 5-bus system, demonstrating how cyber infrastructure can be utilized to model and solve a power system optimization problem. The cyber infrastructure leveraged in this module includes Python, Jupyter Notebook, NumPy, GurobiPy, and Matplotlib.

Key Components#

  1. Inputting system parameters and calculating the Shift Factors matrix.

  2. Formulating the optimization model and solving the optimization problem.

  3. Extracting the optimization results and displaying the outcomes.

This module provides an effective PowerCyber training, facilitating the utilization of cyber infrastructure to conduct studies and research in the power domain.

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