Journal ArticleDOI
Development of an optimization model for energy systems planning in the Region of Waterloo
TLDR
Results indicate that UREM can help tackle dynamic and interactive characteristics of the energy management system in the Region of Waterloo and can address issues concerning cost-effective allocation of energy resources and services.Abstract:
In this study, a large-scale dynamic optimization model (University of Regina Energy Model, UREM) has been developed for supporting long-term energy systems planning in the Region of Waterloo. The model can describe energy management systems as networks of a series of energy flows, transferring extracted/imported energy resources to end users through a variety of conversion and transmission technologies over a number of periods. It can successfully incorporate optimization models, scenario development and policy analysis within a general framework. Complexities in energy management systems can be systematically reflected; thus, the applicability of the modeling process can be highly enhanced. Four scenarios (including a reference case) are considered based on different energy management policies and sustainable development strategies for in-depth analysis of interactions existing among energy, socio-economy and environment in the Region. Useful solutions for the planning of energy management systems have been generated, reflecting trade-offs among energy-related, environmental and economic considerations. They are helpful for supporting (a) adjustment or justification of the existing allocation patterns of energy resources and services, (b) allocations of renewable energy resources, (c) formulation of local policies regarding energy consumption, economic development and energy structure, and (d) analysis of interactions among economic cost, system efficiency, emission mitigation and energy-supply security. Results also indicate that UREM can help tackle dynamic and interactive characteristics of the energy management system in the Region of Waterloo and can address issues concerning cost-effective allocation of energy resources and services. Thus, it can be used by decision makers as an effective technique in examining and visualizing impacts of energy and environmental policies, regional/community development strategies and emission reduction measures within an integrated and dynamic framework. Copyright © 2008 John Wiley & Sons, Ltd.read more
Citations
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Journal ArticleDOI
Size optimization of a PV/wind hybrid energy conversion system with battery storage using simulated annealing
Orhan Ekren,Banu Yetkin Ekren +1 more
TL;DR: It is come up with that the SA algorithm gives better result than the Response Surface Methodology (RSM) in the study of optimizing size of a PV/wind integrated hybrid energy system with battery storage.
Journal ArticleDOI
Paradigm shift in urban energy systems through distributed generation: Methods and models
TL;DR: In this paper, a selection of currently available models for distributed generation planning and design is presented and analyzed in the perspective of gathering their capabilities in an optimization framework to support a paradigm shift in urban energy systems.
Journal ArticleDOI
Identification of optimal strategies for energy management systems planning under multiple uncertainties
TL;DR: In this paper, a fuzzy-random interval programming (FRIP) model is proposed to identify optimal strategies in the planning of energy management systems under multiple uncertainties through the development of a FRIP model, which is based on an integration of the existing interval linear programming, superiority-inferiority-based fuzzy-stochastic programming (SI-FSP) and mixed integer linear programming (MILP).
Journal ArticleDOI
Community-scale renewable energy systems planning under uncertainty—An interval chance-constrained programming approach
TL;DR: In this article, an inexact community-scale energy model (ICS-EM) is developed for planning renewable energy management (REM) systems under uncertainty, which allows uncertainties presented as both probability distributions and interval values to be incorporated within a general optimization framework.
Journal ArticleDOI
Planning and Scheduling under Uncertainty: A Review Across Multiple Sectors
TL;DR: This paper provides an overview of the key contributions within the planning and scheduling communities with specific emphasis on uncertainty analysis, and is the first work which attempts to provide a comprehensive description of two-stage stochastic programming and parametric programming.
References
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