Browsing by Author "Shililiandumi, Naiman"

Now showing 1 - 4 of 4
  • Thumbnail Image
    Item
    Adopting Renewable Energy in Tanzania: Opportunities and Challenges
    (IFIP-WG8.9 Enterprise Information Systems, 2017-10-19) Shililiandumi, Naiman; Rwegasira, Diana; Kalinga, Ellen; Kondoro, Aron; Dhaou, Imed Ben; Kwame, Ibwe; Kelati, Amleset; Mvungi, Nerey H.; Tenhunen, Hannu
    Abstract: Solar energy is one of the sources of power that is obtained in a natural way. Many countries, especially developing countries are making use of the renewable energy for the benefit of their communities, however, the issue of counting the benefit of using solar energy, mainly on cost bases remained undefined to many users/consumers at their premises. In this paper, the research on how thermal solar power can effectively be used in the house to minimize the cost, its requirements and the payback money upon investing on solar power is being addressed. The scenario was based on comparing the cost spends by the residential house with thermal solar power and another house without thermal solar power. The analysis shows that the electric energy saving per year when using solar power is about 51.52% for houses and flats, with payback for the investment cost within 3-4 years. The paper also discussed the building blocks for low-cost ICT infrastructures to deploy solar technologies.
  • Thumbnail Image
    Item
    A Framework for Load Shedding and Demand Response in DC Microgrid using Multi Agent System
    (FRUCT ASSOCIATION, 2017-11) Rwegasira, Diana; Dhaou, Imed Ben; Anagnoston, Anastasia; Kondoro, Aron; Shililiandumi, Naiman; Kelati, Amleset; Taylor, Simon J.E.; Mvungi, Nerey H.; Tenhunen, Hannu
    This paper presents a framework of load shedding experiment for a DC Microgrid using Multi-Agent System (MAS). The microgrid uses solar panels as source of energy to serve a community without access to electricity. The generated framework includes modelling of solar panels, battery storage and loads for effective control and better operation. The loads are classified as critical and non-critical loads. The agents are designed in a decentralized manner which include solar agent, storage agent and load agent. The load shedding experiment of the framework is mapped with the manual operation done at Kisiju village, Pwani, Tanzania. The results of the experiment focus on using accurate solar and PV panels which provide: (i) the multi agent system that runs in the DC microgrid, (ii) the controlling and monitoring of power to be used for critical and non-critical loads and (ii) the management power in the production process through selling extra power from an individual load to the storage
  • Thumbnail Image
    Item
    A Multi-Agent System for Solar Driven DC Microgrid
    ((ICCEREC, 2017-09) Rwegasira, Diana; Dhaou, Imed Ben; Kondoro, Aron; Shililiandumi, Naiman; Kelati, Amleset; Mvungi, Nerey H.; Tenhunen, Hannu
    This paper proposes a Multi-Agent System (MAS) modeling and control architecture for a solar driven DC microgrid. The microgrid consists of solar system as a source of power, energy storage system, critical and non-critical houses (loads) with their own solar and storage as well. For the proposed MAS an individual house can have the ability to sell extra power to the main solar source. The main solar source can generate power and provide to the community when needed. The MAS also controls and monitors an automatic load shedding technique to disconnect non critical loads when there is a deficiency of power supply to the system. The validity of the objectives are demonstrated by agent based system which runs under REPAST simulation tool which used successfully three loads: hospital and two houses during simulation
  • Thumbnail Image
    Item
    Simulation Tools for a Smart Micro-Grid: Comparison and Outlook
    (FRUCT ASSOCIATION, 2017-11) Kondoro, Aron; Dhaou, Imed Ben; Rwegasira, Diana; Kelati, Amleset; Shililiandumi, Naiman; Mvungi, Nerey H.; Tenhunen, Hannu
    Smart micro-grids are low voltage autonomous power systems that integrate information and communication technologies with electrical energy systems. In order to realize this, it is important to find the optimal configuration of components that will result in the most efficient and sustainable DC micro-grid. To facilitate this analysis, a number of modeling and simulation tools for power systems have been proposed. However, in practice, these tools differ widely in the features they provide and the implementation approach. In this paper, we compare the strength and weakness of four popular simulation tools for power systems: Anylogic, Repast, GridLAB-D and RAPSim. We propose a simplified model of a Photovoltaic (PV) panel for smart micro-grid which is implemented in all tools. We determine the strength and weaknesses of each tool based on ease of implementation, accuracy of the final model, and the ability to view results. We also recommend further improvements for existing tools