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| 1 |
ID:
105782
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2011.
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| Summary/Abstract |
This document shows the importance of policies for electric energy savings and efficient energy utilization in power planning. The contributions of economic, social, and environmental items were evaluated according to their financial effects in the delay of investments, reduction of production costs and decrement of environmental emissions. The case study is Baja California, México; this system has a unique primary source: geothermal energy. Whether analyzing the planning as usual or planning from the supply side, the forecast for 2005-2025 indicates that 4500 MW additional installed capacity will be required (3-times current capacity), representing an investment that will emit 12.7 Mton per year of CO2 to the atmosphere and will cost US$2.8 billion. Systemic planning that incorporates polices of energy savings and efficiency allows the reduction of investments and pollutant emissions. For example, a reduction of 20% in the growth trend of the electricity consumption in the industrial customers would save US$10.4 billion over the next 20 years, with a potential reduction of 1.6 Mton/year of CO2. The increase in geothermal power generation is also attractive, and it can be combined with the reduction of use and energy losses of utilities, which would save US$13.5 billion and prevent the discharge of 8.5 Mton/year of CO2.
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| 2 |
ID:
109313
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| Publication |
2011.
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| Summary/Abstract |
Energy policies are often related to the global effort in reducing greenhouse gas emissions through increased use of renewable energies in electricity production. The impact of these policies is usually calculated by energy planning tools. However, the modeling methodologies most currently used are not adequate to simulate long-term scenarios while considering the hourly dynamics of supply and demand.
This paper presents an extension of the TIMES energy planning tool for investment decisions in electricity production that considers seasonal, daily and hourly supply and demand dynamics. The inclusion of these dynamics enables the model to produce more accurate results in what concerns the impact of introducing energy efficiency policies and the increased use of renewable energies.
The model was validated in São Miguel (Azores, Portugal) for the years 2006-2009, where a comparison with real data showed that the model can simulate the supply and demand dynamics. Further, the long-term analysis shows that the inclusion of these dynamics contributes to a better assessment of the renewable energy potential, suggests the postponement of investments in new generation capacity, and demonstrates that using fine time resolution modeling is very valuable for the design of effective policy measures under high renewable penetration energy systems.
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| 3 |
ID:
092614
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2009.
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| Summary/Abstract |
Concerns over increasing energy price, exacerbating power shortage and changing climatic conditions are emerging associated with municipal energy management systems. Most of the previous studies could hardly address multiple uncertainties that exist in such systems; this may lead to incomplete, simplified or even false solutions, and could jeopardize the robustness of management decisions. This study is to develop a dynamic inexact stochastic energy systems planning model (DITS-MEM) for managing municipal energy systems and greenhouse-gas (GHG) emissions under uncertainty. Through integrating mixed-integer, interval-parameter and two-stage stochastic programming techniques, DITS-MEM can handle not only the uncertainties expressed as interval values and probabilistic distributions associated with GHG-emission reduction targets, but also the dynamics of capacity-expansion issues. The developed model is then applied to the Beijing Municipality. The results suggest that the DITS-MEM model is applicable in reflecting complexities of multi-uncertainty, dynamic and interactive municipal energy management systems, and capable of addressing two-stage stochastic problem of GHG-emission reduction. The obtained solutions can provide decision bases for formulating GHG-reduction policies and assessing the associated economic implications in purchasing emission credits or bearing economic penalties.
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