Clustering and Fuzzy Logic-Based Demand-Side Management for Solar Microgrid Operation: Case Study of Ngurudoto Microgrid, Arusha, Tanzania

Permanent electricity availability should not be taken for granted since grid sustainability and reliability are at stake when there is no balance between supply and demand. This paper employs a load balancing demand-side management (DSM) approach based on fuzzy logic, considering the low energy use...

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Bibliographic Details
Published in:Advances in fuzzy systems 2021, Vol.2021, p.1-13
Main Authors: Philipo, Godiana Hagile, Chande Jande, Yusufu Abeid, Kivevele, Thomas
Format: Article
Language:English
Subjects:
Algorithms
Cluster analysis
Clustering
Controllers
Customers
Demand side management
Developing countries
Distributed generation
Electric power demand
Electrical loads
Electricity
Electricity distribution
Energy consumption
Energy efficiency
Energy management
Energy utilization
Fuzzy logic
LDCs
Linear programming
Load
Prices
Supply & demand
Use statistics
Vector quantization
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Summary:Permanent electricity availability should not be taken for granted since grid sustainability and reliability are at stake when there is no balance between supply and demand. This paper employs a load balancing demand-side management (DSM) approach based on fuzzy logic, considering the low energy users who have insignificant influence on system peaks. Through the K-means clustering algorithm, suitable candidates for DSM are identified, and the control mechanism is based on energy utilization and load priority. The results reveal that about 3.7 kW in power saving was achieved per month. This result indicates that, with a proper energy management strategy for an individual customer, almost a flatter load profile and power saving can be achieved.
ISSN:1687-7101
1687-711X
DOI:10.1155/2021/6614129