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

Godiana Hagile Philipo | Zendy; Yusufu Abeid Chande Jande | Zendy; Thomas Kivevele | Zendy

Open Access

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

Author(s) -

Godiana Hagile Philipo,

Yusufu Abeid Chande Jande,

Thomas Kivevele

Publication year - 2021

Publication title -

advances in fuzzy systems

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.38

H-Index - 19

eISSN - 1687-711X

pISSN - 1687-7101

DOI - 10.1155/2021/6614129

Subject(s) - microgrid , cluster analysis , fuzzy logic , computer science , demand side , environmental economics , tanzania , energy management , load management , demand management , reliability (semiconductor) , electricity , peak demand , grid , reliability engineering , power (physics) , operations research , control (management) , environmental science , energy (signal processing) , economics , electrical engineering , engineering , artificial intelligence , mathematics , statistics , environmental planning , macroeconomics , physics , geometry , quantum mechanics

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.

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