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Journal ArticleDOI

Development of an optimization model for energy systems planning in the Region of Waterloo

TL;DR: 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.
Citations
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Journal ArticleDOI
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.

467 citations

Journal ArticleDOI
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.

392 citations

Journal ArticleDOI
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).

269 citations

Journal ArticleDOI
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.
Abstract: In this study, an inexact community-scale energy model (ICS-EM) has been developed for planning renewable energy management (REM) systems under uncertainty. This method is based on an integration of the existing interval linear programming (ILP), chance-constrained programming (CCP) and mixed integer linear programming (MILP) techniques. ICS-EM allows uncertainties presented as both probability distributions and interval values to be incorporated within a general optimization framework. It can also facilitate capacity-expansion planning for energy-production facilities within a multi-period and multi-option context. Complexities in energy management systems can be systematically reflected, thus applicability of the modeling process can be highly enhanced. The developed method has then been applied to a case of long-term renewable energy management planning for three communities. Useful solutions for the planning of energy management systems have been generated. Interval solutions associated with different risk levels of constraint violation have been obtained. They can be used for generating decision alternatives and thus help decision makers identify desired policies under various economic and system-reliability constraints. The generated solutions can also provide desired energy resource/service allocation and capacity-expansion plans with a minimized system cost, a maximized system reliability and a maximized energy security. Tradeoffs between system costs and constraint-violation risks can also be tackled. Higher costs will increase system stability, while a desire for lower system costs will run into a risk of potential instability of the management system. They are helpful for supporting (a) adjustment or justification of allocation patterns of energy resources and services, (b) formulation of local policies regarding energy consumption, economic development and energy structure, and (c) analysis of interactions among economic cost, system reliability and energy-supply security.

235 citations

Journal ArticleDOI
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.
Abstract: This paper provides an overview of the key contributions within the planning and scheduling communities with specific emphasis on uncertainty analysis. As opposed to focusing in one particular industry, several independent sectors have been reviewed in order to find commonalities and potential avenues for future interdisciplinary collaborations. The objectives and physical constraints present within the planning and scheduling problems may vary greatly from one sector to another; however, all problems share the common attribute of needing to model parameter uncertainty in an explicit manner. It will be demonstrated through the literature review that two-stage stochastic programming, parametric programming, fuzzy programming, chance constraint programming, robust optimization techniques, conditional value-at-risk, and other risk mitigation procedures have found widespread application within all of the analyzed sectors. This review is the first work which attempts to provide a comprehensive description of t...

210 citations

References
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Journal ArticleDOI
TL;DR: In this article, the authors give an overview of different decentralized energy models used worldwide, their approaches and their applications along with a few emerging energy models, and explain the need of DEP and shows how different types of energy planning and optimization models, supply demand models, regional models, resource models and neural models have been carried, adopted and applied at decentralized level.
Abstract: Energy planning is carried out at a centralized level using computer-based modeling. The centralized energy planning models and approaches have already been reviewed in literature. Decentralized energy planning (DEP) is a concept of recent origin with limited applications. Literature shows that different models are being developed and used worldwide. This paper gives an overview of different decentralized energy models used worldwide, their approaches and their applications along with a few emerging energy models. The central theme of the energy planning at decentralized level would be to prepare an area-based DEP to meet energy needs and development of alternate energy sources at least-cost to the economy and environment. Ecologically sound development of the region is possible when energy needs are integrated with the environmental concerns at the local and global levels. Taking into account these features, this paper explains the need of DEP and shows how different types of energy planning and optimization models, supply demand models, regional models, resource models and neural models have been carried, adopted and applied at decentralized level.

320 citations

Journal ArticleDOI
TL;DR: An environmental system dynamics model, named ErhaiSD, is developed for supporting this planning task of effective planning for the Lake Erhai Basin, China, and the results are directly useful for simulating and evaluating a variety of decision actions and their dynamic consequences.

291 citations

Journal ArticleDOI
TL;DR: In this paper, a bottom-up energy system optimisation model is proposed in order to support planning policies for promoting the use of renewable energy sources in Apulia region in Southern Italy.
Abstract: In this paper, a bottom-up energy system optimisation model is proposed in order to support planning policies for promoting the use of renewable energy sources. A linear programming optimisation methodology based on the energy flow optimisation model (EFOM) is adopted, detailing the primary energy sources exploitation (including biomass, solid waste, process by-products), power and heat generation, emissions and end-use sectors. The modelling framework is enhanced in order to adapt the model to the characteristics and requirements of the region under investigation. In particular, a detailed description of the industrial cogeneration system, that turns out to be the more efficient and increasingly spread, is incorporated in the regional model. The optimisation process, aiming to reduce environmental impact and economical efforts, provides feasible generation settlements that take into account the installation of combined cycle power plants, wind power, solid-waste and biomass exploitation together with industrial combined heat and power (CHP) systems. The proposed methodology is applied to case of the Apulia region in the Southern Italy.

291 citations

Journal ArticleDOI
TL;DR: In this paper, a solar hydrogen-based energy network is proposed to meet the future energy demand for the major cities of India in a sustainable way, where the solar generated electricity that is excessive of demand is stored in the form of hydrogen to be utilized during nocturnal hours and prolonged overcast conditions.
Abstract: Fossil fuel reserves are diminishing rapidly across the world, intensifying the stress on existing reserves day-by-day due to increased demand. Not only that, fossil fuels, presently contributing to 80% of world primary energy, are inflicting enormous impacts on environment. Climatic changes driven by human activities, in particular the production of greenhouse gas emissions, directly impact the environment. Energy sector has a key role in this regard since energy during its production, distribution and consumption is responsible for producing environmentally harmful substances. A secure and accessible supply of energy is thus very crucial for the sustainability of modern societies. There is an urgent need for a quicker switch over of energy systems from conventional to renewables that are sustainable and can meet the present and projected world energy demand. Solar power is one of the most promising renewables. It is reliable and less vulnerable to changes in seasonal weather patterns. Hydrogen, in the capacity of energy vector, is expected to be the optimum solution for intermittency and storage of energy produced by renewables. Thus, coupled with hydrogen as an energy carrier, solar energy has a large potential to become the fuel of the future. The present study is aimed to explore such potential for India in 2025. India is expected to have a high growth rate in energy demand over the coming years due to its huge population and rapid economic development. By the year 2020, the country's demand for commercial energy is expected to increase by a factor of 2.5. Presently, more than 90% of the energy demand is met by fossil fuels, in spite of the fact that India has limited fossil fuel resources as compared to global reserves. By the year 2020, India, presently the world's sixth largest energy consumer, is expected to meet 75% of its oil and gas needs by imports. Being an energy deficient country, it has not been able to keep up with demand, leading to power shortages and supply interruptions. The growing gap between the demand and supply of energy, and environmental externalities associated with fossil fuel require immediate and substantial increases in electric power generation and transmission capacities, and exploitation of new avenues of energy supply that are more stable and environment friendly. The geographic location of India makes it a strong candidate for harnessing solar energy. Thus, solar PV is a potential technology to meet India's future energy demand and its associated environmental challenges. The present work proposes solar hydrogen based energy network to meet the future energy demand for the major cities of India in a sustainable way. In the proposed energy network, solar PV produced electricity is to be utilized to meet the energy demand during day hours. The solar generated electricity that is excessive of demand is to be stored in the form of hydrogen to be utilized during nocturnal hours and prolonged overcast conditions. A modular approach has been adopted for the purposed energy network to meet the year 2025 demand of six major cities of India: Chennai, Delhi, Jodhpur, Kolkata, Mumbai and Trivandrum. Present as well as projected cost scenarios for 2025 have been provided for all the proposed technologies to evaluate the economical viability of the energy network under study. Based on the futuristic trends, it is foreseen that by the year 2025, the PV electricity would be more economical than the fossil fuel electricity.

199 citations

Journal ArticleDOI
TL;DR: In this paper, the role of several policy instruments in managing energy security and climate risks and stimulating technological change towards a more secure and climate-benign global energy system in the long-term future is examined.

196 citations