학술논문

Techno-economic optimization of sustainable power for telecommunications facilities using a systems approach
Document Type
Conference
Source
Proceedings of the 2010 IEEE International Symposium on Sustainable Systems and Technology Sustainable Systems and Technology (ISSST), 2010 IEEE International Symposium on. :1-6 May, 2010
Subject
Components, Circuits, Devices and Systems
Communication, Networking and Broadcast Technologies
Computing and Processing
Engineered Materials, Dielectrics and Plasmas
Geoscience
Power, Energy and Industry Applications
Robotics and Control Systems
Power generation economics
Power generation
Power system economics
Telecommunication control
Costs
Energy consumption
Performance analysis
Base stations
Power system modeling
Power system management
Radio Base Station
Renewable Energy Model
Hybrid Wind/Solar
Incentive
Ontology
Language
ISSN
1095-2020
2378-7260
Abstract
Telecommunications network operators face the dual challenges of powering remote equipment while controlling both operating costs and energy consumption. As a means to help meet these challenges, this paper describes the functionality and performance of an Alternative Power Analyzer tool specially made for remote base station applications which models the outputs of renewably generated power based on location and user inputs. It combines these results with economic inputs to produce a business plan for the implementation of the preferred system. An important factor affecting economic viability is the various incentives for sustainable power generation. These can vary greatly by value, duration, equipment eligibility, location, and other constraints. To manage these complex datasets, a dynamic ontological information framework has been developed which is designed to iteratively interface with the APA tool. The outputs of the work indicate that a techno-economic systems approach can be applied both to assess the viability of location-specific system configurations under current incentives frameworks and to inform policy makers in terms of future incentives optimization.