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Distribution Network Loss Reduction using DSTATCOM Placement

Target year: BE Sem 7-8 (Major Project Phase-I/II) AICTE: 6 credits · ~150 hrs Bloom: Create / Evaluate MU CBCS: EE801 / EEDLO8021 BE Project

Real-world project · AICTE-aligned · AI-graded · Audit-ready certificate

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Milestones

Available mentors

Enrolled students

Core skills

About this project

Optimize placement + sizing of Distribution STATCOMs (DSTATCOMs) on a real IEEE 33-bus radial distribution feeder to minimize active power losses + improve voltage profile. Use Particle Swarm Optimization in MATLAB, validate via load-flow in OpenDSS, quantify $/MWh savings.

Course Learning Outcomes (CLOs):
CLO1: Apply load-flow methods to a real distribution feeder.
CLO2: Formulate DSTATCOM placement as a constrained optimization.
CLO3: Implement PSO / GA + evaluate convergence.
CLO4: Quantify technical + economic benefits of compensation.
CLO5: Defend design choices in oral panel review.

Industry/societal relevance: India's discoms (MSEDCL, Tata Power-Delhi, Adani Electricity) are losing crores to T&D losses; aligned with placement at power-system consultancies (PRDC, Power Research, Siemens PTI).

Milestones

1. Feeder Modeling

15 marks 18d

Build IEEE 33-bus + a real Indian feeder section in OpenDSS. Validate base case load flow.

2. DSTATCOM Model

20 marks 21d

Inject reactive power as PV/PQ bus. Verify voltage rise + loss reduction with single DSTATCOM at trial bus.

3. PSO Optimization

25 marks 21d

PSO with N DSTATCOMs (N=2,3,4). Each particle = [location, size]. Objective: min losses, subject to voltage ±5%.

4. Sensitivity + Robustness

20 marks 18d

Test under load variation (50%, 100%, 150%). Verify solution remains feasible. Compare PSO vs GA convergence.

5. Cost-Benefit + IEEE Paper

20 marks 22d

$/MWh savings from loss reduction, vs DSTATCOM capex + opex over 10-year life. 14-page IEEE-format report + oral defense.

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Upcoming sessions

Session	Window	Enrolled
Distribution Network Loss Reduction using DSTATCOM Placement	11 Jun 2026 to 10 Jun 2028	0

Skills you'll learn

Power Systems AnalysisReactive Power CompensationOptimization (PSO / GA)Load Flow AnalysisOpenDSSMATLAB advancedEconomic Analysis

Tools used

MATLAB R2024 + Optimization ToolboxOpenDSSPython (for COM interface)IEEE 33-bus test dataMS Excel

Prerequisites

Power Systems-II; Power Quality elective (or self-study); Optimization basics; MATLAB intermediate

Available mentors

Priyang Kumar

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