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
Development of an integrated methodology for the energy needs of a major urban city: The case study of Athens, Greece
TL;DR: In this paper, a linear programming methodology for the city of Athens, Attica region is implemented trying to identify the energy supply levels based on the energy use, aiming to determine the optimal way for the energy needs to be covered.
Journal ArticleDOI
Study on multi‐objective optimization of load dispatch including renewable energy and CCS technologies
TL;DR: In this paper, a novel singular weighted method (SWM) has been proposed for solving this kind of multi-objective and multi-constraint optimization problem, and a power system with five generators has been applied in one case study to test the model and SWM.
Journal ArticleDOI
CCEM: A City-cluster Energy Systems Planning Model
TL;DR: In this article, the authors developed a City-cluster Energy Systems Planning Model (CCEM) and applied it to the Toronto-Niagara Region (TNR) as a case study.
Journal ArticleDOI
A Robust Inexact Joint-optimal α cut Interval Type-2 Fuzzy Boundary Linear Programming (RIJ-IT2FBLP) for energy systems planning under uncertainty
TL;DR: The results of the RIJ-IT2FBLP model not only deliver an optimized energy scheme, but also provide a suitable way to balance uncertain cost and profit parameters of an energy supply system.
Journal ArticleDOI
Fuzzy interval programming for energy and environmental systems management under constraint-violation and energy-substitution effects: A case study for the City of Beijing
TL;DR: The developed FIP-CVESE method could not only tackle uncertainties expressed as both interval numbers and fuzzy sets, but also allow several given levels of tolerable violations of system objective and constraints to expand the model's decision space, facilitating the improvement in solution robustness.
References
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Hal Turton,Leonardo Barreto +1 more
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