SOURCE:

Faculty: Engineering
Department: Electronic And Computer Engineering

CONTRIBUTORS:

Ajuzie, U.C;
Inyiama, H. C;
Azubogu, A.C.O;

ABSTRACT:

This work presents an Energy Management System (EMS) for Smart Campus Hybrid Microgrid (SCHMG). The SCHMG test-bed consists of four sub-grids located at the School of Postgraduate Studies (SPGS), Faculty of Law (LAW), Faculty of Engineering (ENG) and University Main Library (LIB) all at Nnamdi Azikiwe University (NAU) Awka. The interconnection architecture that enables the four sub-grids to operate independently or in active interconnected modes were described. Energy sources for the test-bed are renewable resources of solar-PV modules, Battery Energy Storage System (BESS) and the installed diesel generators. To provide the estimated energy demand of the four sub-grids, HOMER Grid simulation software was used to perform optimal sizing of the required components for each sub-grid based on the result of the detailed electrical load estimation conducted at the different sub-grids. From the HOMER Grid simulation software, the components required for each sub-grid were computed as follows; for SPGS sub-grid: 984 pieces of 300W solar-PV modules and 52 pieces of 200AH, 12V lead acid batteries, for LAW sub-grid: 4160 pieces of 300W solar-PV modules and 336 pieces of 200AH, 12V lead acid batteries, for ENG sub-grid: 2690 pieces of 300W solar-PV modules and 160 pieces of 200AH, 12V lead acid batteries and for LIB sub-grid:10240 pieces of 300W solar-PV modules and 620 pieces of 200AH, 12V lead acid batteries. An estimated cost of running the sub-grids using conventional sources of diesel generators and public utility supply was computed based on data collected from the University Works Department. This was compared with the cost of running the sub-grids using the microgrid architecture as obtain from the HOMER grid simulation software, and the result showed that NGN254,896,412.01 amount will be saved annually by the SCHMG. Analysis on the electrical loads allowed their categorization into; high priority (hpls), priority (pls) and less priority loads (lpls). An energy management algorithm for the sub-grids was developed from the mathematical model of the sub-grids. This EMS which is a multi-function intelligent agent called the Localized Intelligent Agent (LIA), was modelled in MatLab using the Fuzzy Logic tool box. The LIA model was then implemented in Simulink and simulated using simulation scenarios of real life test conditions. For the solar plant, four major states represented by the following fuzzy logic linguistic variable were used; VERY LOW (12.1V), LOW (12.5V), HIGH (13V) and VERY HIGH (13.5V). The other input sources had only two fuzzy logic states represented by LOW (1-1.5V) and HIGH (4.5-4.9V). The results of ten different test scenarios were observed and recorded. Results obtained from each of these test conditions showed that the EMS reliably and intelligently achieved its goals and objectives. The obtained results when compared with the expected system responses showed that the microgrid is able to deliver a steady and cost effective electric power to the different electrical load categories within each sub-grid.