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Power System Economic Dispatch

Python Model & Optimization

4.8 Filled star Filled star Filled star Filled star Half star
Based on 179 ratings
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Dr S.Giannelos Quant Energy Academy

1. Use this code at Checkout for the best DEAL (remove spaces. ):  After purchase, just send me a private message here.

2. Course Overview:

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1. Use this code at Checkout for the best DEAL (remove spaces. ):  After purchase, just send me a private message here.

2. Course Overview:

  1. You will gain a clear understanding of economic dispatch in power systems, including its purpose and significance in optimizing electricity generation costs.

  2. You will develop economic dispatch models using Python (with the Pyomo package) and GAMS, two powerful tools for formulating and solving optimization problems.

  3. You will apply these models to real-world power systems, considering scenarios with and without energy storage, as well as cases with and without CO2 constraints. Through multiple case studies, you will analyze results and assess the economic value of energy storage.

  4. You will learn how to effectively solve the economic dispatch problem and interpret the results based on realistic data. You will also gain insights into cost minimization and system efficiency.

  5. You will also develop debugging skills to identify and resolve common modelling issues, ensuring your solutions are accurate and reliable.

  6. To complete this course, you will need basic knowledge of optimization and programming. This will help you get the most out of the material.

3. How to connect with me and unlock hundreds of courses.

You can unlock hundreds of online courses at the Quant Energy Academy at www [dot] quantenergyacademy [dot] com

Here to help you thrive,  Your Instructor

Dr.Spyros

Enroll now

What's inside

Learning objectives

  • To get all extras please use this code at checkout (remove spaces): 49a9c2 b375efae85b134
  • Remember: all the code, is available for you to download! plus: publications and tutorials!
  • You will learn what economic dispatch is and how to model it in python & gams. you will also model: co2, energy storage, renewables.
  • Always expanding: new videos and publications are added every 6–12 months, so be sure to check back!
  • Fast help within hours: have questions or need guidance? send a message and get a response within hours!

Syllabus

Get a high-level view of the course.

Introduction to the key topics covered in the course.

More Resources

Download a few introductory tutorials for extra study. The video lectures clearly describe what economic dispatch is. These extra study materials are just for a quick high-level view.


Read more

Introduction to the section.

How to define the input parameters. Also, a paper is available for download for extra reading (the paper is related to Economic Dispatch research. The paper is only for extra reading. It is an academic paper. The paper is not directly related to the code of this online course. It is much more advanced and the goal is to give you an idea of latest academic research in this field).

How to define our optimization model. Also, a paper is available for download for extra reading (the paper is related to Economic Dispatch research. The paper is only for extra reading. It is an academic paper. The paper is not directly related to the code of this online course. It is much more advanced and the goal is to give you an idea of latest academic research in this field).

How to read and understand the formulation. Also, a paper is available for download for extra reading (the paper is related to Economic Dispatch research. The paper is only for extra reading. It is an academic paper. The paper is not directly related to the code of this online course. It is much more advanced and the goal is to give you an idea of latest academic research in this field).

How to define the decision variables (unknowns). Also, a paper is available for download for extra reading (the paper is related to Economic Dispatch research. The paper is only for extra reading. It is an academic paper. The paper is not directly related to the code of this online course. It is much more advanced and the goal is to give you an idea of latest academic research in this field).

How to define the objective function and the constraints. Also, a paper is available for download for extra reading (the paper is related to Economic Dispatch research. The paper is only for extra reading. It is an academic paper. The paper is not directly related to the code of this online course. It is much more advanced and the goal is to give you an idea of latest academic research in this field).

How to solve the model and plot the solution.

How to model and solve the GAMS model.

Also, a paper is available for download for extra reading (the paper is related to Economic Dispatch research. The paper is only for extra reading. It is an academic paper. The paper is not directly related to the code of this online course. It is much more advanced and the goal is to give you an idea of latest academic research in this field).

How to debug in GAMS.

How to solve the optimization model in Python. We include storage and CO2 modelling.

We focus on what convexity means and how to find it. Also, a paper is available for download for extra reading (the paper is related to Economic Dispatch research. The paper is only for extra reading. It is an academic paper. The paper is not directly related to the code of this online course. It is much more advanced and the goal is to give you an idea of latest academic research in this field).

We model and solve the model.

We solve without Storage , but with CO2 modelling. Also, a paper is available for download for extra reading (the paper is related to Economic Dispatch research. The paper is only for extra reading. It is an academic paper. The paper is not directly related to the code of this online course. It is much more advanced and the goal is to give you an idea of latest academic research in this field).

We solve the previous model in GAMS.

We model in Python, with Storage, wind and CO2.

We remove Storage and conduct the previous analysis. Also, a paper is available for download for extra reading (the paper is related to Economic Dispatch research. The paper is only for extra reading. It is an academic paper. The paper is not directly related to the code of this online course. It is much more advanced and the goal is to give you an idea of latest academic research in this field).

Modelling in GAMS the system with storage, renewables (wind) and CO2.

How to send the results to Excel for further analysis.

Key messages and analyses. Also, a paper is available for download for extra reading (the paper is related to Economic Dispatch research. The paper is only for extra reading. It is an academic paper. The paper is not directly related to the code of this online course. It is much more advanced and the goal is to give you an idea of latest academic research in this field).

Important sets for download.

Introduction and the mathematical formulation.

Definition of the system topology.

Definition of the Reliability Test System. Also, a paper is available for download for extra reading (the paper is related to Economic Dispatch research. The paper is only for extra reading. It is an academic paper. The paper is not directly related to the code of this online course. It is much more advanced and the goal is to give you an idea of latest academic research in this field).

Definition of the per-unit system.

Conducting the modelling in Python.

Defining the constraints of the model. Also, a paper is available for download for extra reading (the paper is related to Economic Dispatch research. The paper is only for extra reading. It is an academic paper. The paper is not directly related to the code of this online course. It is much more advanced and the goal is to give you an idea of latest academic research in this field).

Defining the decision variables of the model.

Defining the constraints of the model.

Defining the optimal solution. Also, a paper is available for download for extra reading (the paper is related to Economic Dispatch research. The paper is only for extra reading. It is an academic paper. The paper is not directly related to the code of this online course. It is much more advanced and the goal is to give you an idea of latest academic research in this field).

Defining additional constraints.

Solving the model in GAMS. Also, a paper is available for download for extra reading (the paper is related to Economic Dispatch research. The paper is only for extra reading. It is an academic paper. The paper is not directly related to the code of this online course. It is much more advanced and the goal is to give you an idea of latest academic research in this field).

Python modelling of the analysis without Storage. Also, a paper is available for download for extra reading (the paper is related to Economic Dispatch research. The paper is only for extra reading. It is an academic paper. The paper is not directly related to the code of this online course. It is much more advanced and the goal is to give you an idea of latest academic research in this field).

Concluding remarks.

Bonus downloads!

Traffic lights

Read about what's good
what should give you pause
and possible dealbreakers
Uses Python and GAMS, which are industry-standard tools for modeling and solving optimization problems in power systems
Explores economic dispatch with considerations for CO2 emissions, energy storage, and renewable energy sources like wind power
Requires basic knowledge of optimization and programming, which may necessitate additional preparation for some learners
Includes debugging skills for identifying and resolving common modeling issues, ensuring solutions are accurate and reliable
Applies models to real-world power systems, considering scenarios with and without energy storage and CO2 constraints
Includes extra reading materials that are academic papers, which may be too advanced for some learners

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Create your own learning path. Save this course to your list so you can find it easily later.
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Reviews summary

Practical economic dispatch with python & gams

According to learners, this course provides a highly practical and code-focused approach to power system economic dispatch. Students particularly praise the downloadable Python and GAMS code examples, finding them extremely useful and applicable to real-world problems. The instructor, Dr. Spyros, is noted for his clear explanations and quick responsiveness to questions. The course covers highly relevant topics like energy storage, CO2 constraints, and renewables. While the course description suggests only basic prerequisites, some learners found that a stronger prior background in optimization and the specific software tools (Pyomo/GAMS) was beneficial to keep up with the pace.
Focuses on modern, relevant aspects.
"The focus on real-world applications, especially with storage and CO2 constraints, is highly relevant"
"The inclusion of CO2 and storage models is very timely."
"Covering renewables was a plus."
"The content itself (economic dispatch, storage, CO2) is relevant."
Clear explanations and quick responses.
"Dr. Spyros explains complex concepts clearly"
"The instructor's responsiveness to questions was also impressive."
"Dr. Spyros breaks down the modeling process step-by-step."
"The instructor is knowledgeable and responds quickly."
"Instructor feedback is quick and helpful."
"Dr. Spyros knows his stuff and delivers it effectively"
Provides useful and applicable code.
"provides practical Python and GAMS code examples."
"The Python code provided is extremely useful and directly applicable."
"The downloadable code made it easy to follow along and experiment."
"Practical, code-focused approach to economic dispatch."
"The downloadable files were crucial for learning."
Some sections have older audio/video.
"the production quality (audio/video) felt a bit dated in some sections."
"I found the initial lectures' audio quality poor. It improved later on."
"Some lectures could be more polished"
Basic optimization knowledge may not be enough.
"I think a stronger background in optimization would be beneficial, even though it says basic knowledge is enough."
"I struggled with the pace, especially without a strong prior background in optimization solvers like Pyomo/GAMS."
"It's definitely geared towards someone already comfortable with these tools."
"Requires some effort if you're new to Pyomo/GAMS."
"a strong optimization background is definitely recommended."

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Power System Economic Dispatch: Python Model & Optimization with these activities:
Review Optimization Theory
Solidify your understanding of optimization theory to better grasp the underlying principles of economic dispatch.
Show steps
  • Review linear programming concepts.
  • Study nonlinear programming techniques.
  • Practice solving optimization problems.
Brush Up on Python and Pyomo
Improve your Python and Pyomo skills to effectively implement and debug economic dispatch models.
Show steps
  • Review Python syntax and data structures.
  • Practice using the Pyomo library.
  • Work through Pyomo optimization examples.
Solve Economic Dispatch Problems
Reinforce your understanding by solving various economic dispatch problems with different constraints.
Show steps
  • Formulate economic dispatch models in Python.
  • Solve models with and without energy storage.
  • Analyze the impact of CO2 constraints.
Four other activities
Expand to see all activities and additional details
Show all seven activities
Explore Advanced Pyomo Features
Deepen your knowledge by exploring advanced Pyomo features for modeling complex power systems.
Show steps
  • Learn about piecewise linear functions in Pyomo.
  • Study stochastic programming techniques.
  • Implement advanced models using Pyomo.
Model a Real-World Power System
Apply your skills by modeling a real-world power system and optimizing its economic dispatch.
Show steps
  • Gather data on a specific power system.
  • Develop an economic dispatch model in Python.
  • Analyze the results and draw conclusions.
Create a Presentation on Economic Dispatch
Solidify your understanding by creating a presentation explaining the concepts and applications of economic dispatch.
Show steps
  • Research economic dispatch techniques.
  • Prepare slides explaining key concepts.
  • Present your findings to peers.
Read 'Power System Analysis and Design'
Expand your knowledge of power system analysis to better understand the context of economic dispatch.
View Power System Analysis and Design, SI Edition on Amazon
Show steps
  • Read chapters on power system operation.
  • Study economic dispatch algorithms.
  • Relate concepts to the course material.

Career center

Learners who complete Power System Economic Dispatch: Python Model & Optimization will develop knowledge and skills that may be useful to these careers:
Energy Storage System Engineer
An Energy Storage System Engineer designs, develops, and implements energy storage solutions for various applications, including grid-scale storage, microgrids, and electric vehicles. This course specifically addresses economic dispatch with energy storage, including modeling and analysis in both Python and GAMS. The focus on optimization, cost minimization, and real-world case studies will provide you with practical experience in evaluating the economic value of energy storage within power systems. This course helps develop skills in modeling and optimizing energy storage systems.
See salaries and explore the career path for Energy Storage System Engineer
Microgrid Designer
A Microgrid Designer plans and designs self-contained energy systems that can operate independently or in conjunction with the main grid. This involves optimizing the mix of generation sources, including renewables and energy storage. This course's coverage of economic dispatch with energy storage, renewables, and CO2 modeling, using both Python and GAMS, is particularly relevant. This course helps develop the skills to design economically efficient and environmentally sustainable microgrids.
See salaries and explore the career path for Microgrid Designer
Power System Analyst
A Power System Analyst evaluates the performance and reliability of electrical power systems. Much of this work involves using software tools to simulate and analyze power system behavior under various conditions. A course teaching the development of economic dispatch models using Python and GAMS, as well as applying these models to real-world power systems scenarios with and without energy storage and CO2 constraints, directly aligns with the responsibilities of a power systems analyst. This course helps build skills in simulating and analyzing power system operation. The course's emphasis on cost minimization and system efficiency further aids in evaluating the economic viability of power system designs and operational strategies.
See salaries and explore the career path for Power System Analyst
Power System Planning Engineer
A Power System Planning Engineer is involved in forecasting future energy needs and designing the infrastructure to meet those demands. This often involves using optimization techniques to plan for generation and transmission expansion. This course helps develop skills in economic dispatch modeling using Python and GAMS. By applying these models to real-world power systems, including scenarios with and without energy storage and CO2 constraints, you can gain insights into long-term planning strategies. The course's debugging skills component will be useful to identify and resolve common power system planning issues.
See salaries and explore the career path for Power System Planning Engineer
Grid Operations Engineer
A Grid Operations Engineer ensures the safe, reliable, and efficient operation of the electrical grid. This role often involves real-time monitoring and control, as well as planning for future grid needs. You can use this course to understand economic dispatch in power systems and model it in Python and GAMS. This course helps you master the skills to optimize grid operations. The hands-on experience with real-world power system scenarios, including energy storage and CO2 constraints, will prepare you to make informed decisions in grid management.
See salaries and explore the career path for Grid Operations Engineer
Energy Market Analyst
An Energy Market Analyst studies energy markets, forecasts prices, and advises traders on investment strategies. Much of this work involves understanding economic dispatch and how generators compete to supply electricity. A course teaching economic dispatch models using Python and GAMS, and applying these models to real-world power systems scenarios with and without energy storage and CO2 constraints, directly aligns with the responsibilities of an energy market analyst. This course helps build skills in understanding the economic drivers behind energy market behavior.
See salaries and explore the career path for Energy Market Analyst
Renewable Energy Analyst
A Renewable Energy Analyst assesses the technical and economic feasibility of renewable energy projects, such as solar, wind, and hydro. You can use this course to learn how to model renewable energy sources, such as wind, within the context of economic dispatch. The course's curriculum covers scenarios with renewable energy integration and CO2 constraints, enabling you to analyze the impact of renewable energy on system costs and emissions. This course provides valuable insights into optimizing renewable energy integration in power systems.
See salaries and explore the career path for Renewable Energy Analyst
Demand Response Analyst
A Demand Response Analyst designs and implements programs that incentivize consumers to reduce their electricity consumption during peak hours. This requires an understanding of how economic dispatch affects electricity prices and the value of demand response. This course helps build skills in modeling and optimizing power systems, including the impact of CO2 constraints and energy storage. This course provides a strong foundation for analyzing the economic benefits of demand response programs.
See salaries and explore the career path for Demand Response Analyst
Energy Consultant
An Energy Consultant advises clients on energy efficiency, renewable energy, and energy management strategies. This requires a strong understanding of power system economics and optimization. A course that provides a clear understanding of economic dispatch in power systems, including its purpose and significance in optimizing electricity generation costs, will be advantageous to any energy consultant. The hands-on experience using Python (with the Pyomo package) and GAMS to develop economic dispatch models helps any consultant develop a valuable skillset. The course helps provide insights into cost minimization and system efficiency.
See salaries and explore the career path for Energy Consultant
Quantitative Analyst
A Quantitative Analyst, often working in the energy sector, develops and implements mathematical models for pricing, hedging, and risk management purposes. This necessitates a strong foundation in optimization and programming. This course is helpful because it utilizes Python and GAMS to formulate and solve optimization problems related to economic dispatch in power systems. By learning how to model real-world scenarios, including those with energy storage and CO2 constraints, a quantitative analyst can enhance their skills in developing robust energy models. The course helps in developing practical applications of quantitative methods in the energy industry.
See salaries and explore the career path for Quantitative Analyst
Control Systems Engineer
A Control Systems Engineer designs and implements control systems for various industrial processes, including power generation and distribution. This course may be useful for understanding how to optimize the operation of power systems. The course's exploration of economic dispatch models using Python and GAMS, as well as its application to real-world scenarios involving energy storage and CO2 constraints, may provide valuable insights into the design and control of advanced power systems. This course is helpful for learning how to improve system efficiency.
See salaries and explore the career path for Control Systems Engineer
Power System Protection Engineer
A Power System Protection Engineer designs and maintains protective systems that safeguard the electrical grid from faults and disturbances. Although this course is not directly focused on protection, the understanding of power system behavior gained from this course may be useful. The course's modeling of real-world power systems, including scenarios with and without energy storage and CO2 constraints, may provide a broader perspective on system dynamics. This course may help in the design of effective protection strategies.
See salaries and explore the career path for Power System Protection Engineer
Sustainability Consultant
A Sustainability Consultant advises organizations on how to reduce their environmental impact and improve their sustainability performance. This course may be useful for understanding the economic implications of CO2 emissions and the role of renewable energy and energy storage in reducing carbon footprints. The course's modeling of power systems with CO2 constraints and renewable energy integration provide valuable insights. This course may help by providing tools to quantify the economic and environmental benefits of various sustainability initiatives.
See salaries and explore the career path for Sustainability Consultant
Data Scientist
A Data Scientist analyzes large datasets to extract meaningful insights and develop predictive models. In the energy sector, this can involve analyzing grid data to optimize operations, predict demand, and detect anomalies. This course may be useful by providing a strong foundation in power system economics and optimization. The course's hands-on experience in developing economic dispatch models using Python and GAMS will help you to apply data science techniques to real-world energy problems. This course may help develop domain expertise in the power systems area.
See salaries and explore the career path for Data Scientist
Electrical Engineer
An Electrical Engineer designs, develops, tests, and supervises the manufacturing of electrical equipment. This course enhances the skills of any electrical engineer. The course's focus on economic dispatch and modeling in Python and GAMS will provide a deeper understanding of power system optimization and real-world scenarios. This course may be useful for electrical engineers who want to specialize in power systems.
See salaries and explore the career path for Electrical Engineer

Reading list

We've selected one books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Power System Economic Dispatch: Python Model & Optimization.
Cover image
Power System Analysis and Design, SI Edition
Save
Provides a comprehensive overview of power system analysis and design, covering topics such as power flow, fault analysis, and stability. It useful reference for understanding the fundamental concepts behind economic dispatch and how it fits into the broader context of power system operation. This book can be used to supplement the course material with more detailed explanations and examples.
Power System Analysis and Design, SI Edition
Paperback
$$$
Power System Analysis and Design, SI Edition
Paperback
$$$

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Rating
4.8 Filled star Filled star Filled star Filled star Half star
Effort
4.5 total hours
Via
Udemy
Instructor
Dr S.Giannelos Quant Energy Academy
Language
English
Traffic lights
Read about what's good
what should give you pause
and possible dealbreakers
Uses Python and GAMS, which are industry-standard tools for modeling and solving optimization problems in power systems
Explores economic dispatch with considerations for CO2 emissions, energy storage, and renewable energy sources like wind power
Requires basic knowledge of optimization and programming, which may necessitate additional preparation for some learners
Includes debugging skills for identifying and resolving common modeling issues, ensuring solutions are accurate and reliable
Applies models to real-world power systems, considering scenarios with and without energy storage and CO2 constraints
Includes extra reading materials that are academic papers, which may be too advanced for some learners
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