By Prof. Eng. Christopher Maina Muriithi
POWER SYSTEMS ANALYSIS WITH METAHEURISTICS
Learn. Apply. Lead. Grow.
Master Power Systems with Classical Methods & Modern AI Techniques
This book uniquely integrates classical power system analysis with cutting‑edge metaheuristic optimisation. Whether you are a student, researcher, or practicing engineer, you will gain both a solid theoretical foundation and practical skills to solve real‑world power system problems using MATLAB and Python.
Book Overview
Power Systems Analysis with Metaheuristics bridges the gap between traditional analytical methods and modern computational intelligence. It provides clear, step‑by‑step explanations of core power system concepts and then demonstrates how metaheuristic algorithms can enhance and automate these analyses. Every technique is accompanied by fully functional code in both MATLAB and Python, allowing you to immediately apply what you learn.
What You'll learn
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Comprehensive Load Flow Methods
Master Gauss–Seidel, Newton–Raphson, and Fast Decoupled load flow techniques, including their derivation, implementation, and convergence properties.
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Voltage Stability Assessment
Implement reduced Jacobian based methods to evaluate system stability and identify weak buses.
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Economic Dispatch
Optimise generator scheduling to minimise fuel cost while meeting demand and operational constraints.
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Metaheuristic Optimisation
Dive into Particle Swarm Optimisation (PSO) , Genetic Algorithms (GA) , Simulated Annealing (SA) , and the novel Boda Boda Optimisation Algorithm – a nature inspired algorithm based on the behaviour of motorcycle taxis in East Africa.
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Integrated Frameworks
Build computational intelligence models that combine classical power system analysis with AI for improved performance, including hybrid approaches and algorithm tuning.
What Makes This Book Unique
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Dual Code in MATLAB & Python
All examples are provided in both languages, so you can work in your preferred environment.
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Novel Algorithms
Includes the Boda Boda Optimisation Algorithm, developed by the author and tested on real world power system problems.
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Step by Step Pedagogy
Each method is explained from first principles, with intermediate derivations and flowcharts to aid understanding.
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Real World Relevance
Case studies are drawn from practical scenarios, including Kenyan and East African power systems.
Technical Coverage In Detail
Load Flow Analysis
Full treatment of Gauss–Seidel, Newton–Raphson, and Fast Decoupled methods. Derivation of power flow equations, Jacobian matrix formulation, handling of PV and PQ buses, and convergence acceleration.
Voltage Stability
Reduced Jacobian method, modal analysis, participation factors, and voltage stability indices. Practical examples on IEEE test systems.
Economic Dispatch
Problem formulation, lambda‑iteration method, inclusion of transmission losses (B‑coefficients), and integration with metaheuristics for constrained optimisation.
Particle Swarm Optimisation
Algorithm fundamentals, inertia weight, constriction factors, and applications to economic dispatch, reactive power planning, and optimal power flow.
Genetic Algorithms
Selection, crossover, mutation, constraint handling, and power‑system‑specific encoding. Case studies on network reconfiguration, unit commitment, and capacitor placement.
Simulated Annealing
Annealing schedule, neighbourhood generation, and applications to combinatorial problems in power systems such as transmission expansion planning.
Boda Boda Optimisation Algorithm
A novel metaheuristic inspired by the adaptive, decentralised behaviour of motorcycle taxis (“boda bodas”) navigating urban traffic. The algorithm’s exploration–exploitation balance, mathematical model, and application to optimal power flow and voltage control.
MATLAB & Python Implementations
Every algorithm is coded and explained line‑by‑line, enabling you to simulate, modify, and extend the examples to your own projects. Code is modular and well‑commented.
About the Author
Prof. Eng. Christopher Maina Muriithi is a Professor of Electrical Engineering with over 25 years of experience in teaching, research, and professional practice. He is a registered engineer with the Engineers Board of Kenya and has published extensively in the areas of voltage stability, renewable energy integration, and computational intelligence. His pioneering work on applying metaheuristics to power system problems has earned him international recognition. This book distils his practical knowledge and academic rigour into a single, accessible volume.
Pricing & Packages
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Sr.
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Item
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Price (KES)
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|---|---|---|
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1
|
Book (Softcover)
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3,200
|
|
2
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Delivery (within Nairobi)
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300
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3
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MATLAB / Python Code Pack (optional – digital download)
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500
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4
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Total (Book + Delivery + Code Pack)
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4,000
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For deliveries outside Nairobi, please contact us for a shipping quote.
How to Order
- Make Payment via M‑Pesa Paybill or Bank Transfer (details below).
- Send confirmation (M‑Pesa message or bank slip) to 0722 497 463 or email info@dochsustainable.co.ke.
- We will confirm your order and arrange delivery (or email the code pack).
Official Payment Details
Company: DOCH SUSTAINABLE SOLUTIONS COMPANY LTD
Bank: ABSA BANK KENYA – TRM Branch
Paybill (M‑Pesa): 303030
Account Number: 2045584626
When using Paybill, enter the account number exactly as shown.
Frequently Asked Questions
Q: Is the code pack included in the book price?
A: No, the code pack is optional and can be purchased separately for KES 500. It contains all MATLAB and Python scripts from the book, ready to run.
Q: How will I receive the code pack?
A: After payment confirmation, the code pack will be emailed to you as a downloadable ZIP file.
Q: Do you ship outside Nairobi?
A: Yes, but delivery charges will vary. Please contact us to arrange.
Q: Can I get an invoice for my organisation?
A: Absolutely – just let us know the billing details when you place your order.
Contact Us
- Phone / WhatsApp: 0722 497 463
- Email: info@dochsustainable.co.ke
Our Promise
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