A. Fereidunian, H. Lesani, C. Lucas, M. Lehtonen, M. M. Nordman,
Volume 2, Issue 3 (7-2006)
Abstract
Almost all of electric utility companies are planning to improve their
management automation system, in order to meet the changing requirements of new
liberalized energy market and to benefit from the innovations in information and
communication technology (ICT or IT). Architectural design of the utility management
automation (UMA) systems for their IT-enabling requires proper selection of IT choices for
UMA system, which leads to multi-criteria decision-makings (MCDM). In response to this
need, this paper presents a model-based architectural design-decision methodology. The
system design problem is formulated first then, the proposed design method is introduced,
and implemented to one of the UMA functions–feeder reconfiguration function (FRF)– for
a test distribution system. The results of the implementation are depicted, and
comparatively discussed. The paper is concluded by going beyond the results and fair
generalization of the discussed results finally, the future under-study or under-review
works are declared.
N. Thakkar, P. Paliwal,
Volume 18, Issue 4 (12-2022)
Abstract
In the last decade, there has been a lot of focus on sustainable development in the electrical power industry to meet the growing energy demand. This has led to an increase in the integration of renewable energy sources (RES). In addition to being abundantly available, the RES offers advantages such as low environmental impact and increased social development of rural communities which are imperative for a sustainable society. However, the selection of a particular generating resource or resource mix (RM) for an autonomous micro-grid is a complex problem that involves multiple conflicting factors. In this paper, a planning strategy for selecting an appropriate RM has been proposed. Seven RMs comprising different combinations of four generation/storage technologies such as solar photovoltaic array (SPVA), wind turbine (WT), diesel generator (DG) and battery storage (BS) have been considered. The planning is initiated with the determination of optimal component sizing for all seven RMs. The RMs are then analyzed with respect to four primary sustainability parameters i.e. economic, social, technical and environmental. The analysis is further enhanced by investigation of 13 sub-parameters as well. Thereafter, prioritization of RMs is carried out using two MCDM methods: Best worst method (BWM) and PROMETHEE II. Finally, to assert the importance of weight assignment on RM ranking, sensitivity analysis is performed. In order to impart the practical aspect to analysis, the planning formulation is applied to a case study of the Thar desert, India. The results suggest that a combination of SPVA and BS provides the most optimum RM solution.
