Academia.edu no longer supports Internet Explorer.
To browse Academia.edu and the wider internet faster and more securely, please take a few seconds to upgrade your browser.
2019, Energies
Fossil fuels have been heavily exploited since the Industrial Revolution. The resulting carbon emissions are widely regarded as being the main cause of global warming and climate change. Key mitigation technologies for reducing carbon emissions include carbon capture and storage (CCS) and renewables. According to recent analysis of the International Energy Agency, renewables and CCS will contribute more than 50% of the cumulative emissions reductions by 2050. This paper presents a new mathematical programming model for multi-footprint energy sector planning with CCS and renewables deployment. The model is generic and considers a variety of carbon capture (CC) options for the retrofit of individual thermal power generation units. For comprehensive planning, the Integrated Environmental Control Model is employed in this work to assess the performance and costs of different types of power generation units before and after CC retrofits. A case study of Taiwan’s energy sector is presente...
IET Gener. Transm. Distrib., 2020, Vol. 14 Iss. 26, pp. 6650-6662, 2020
Fossil fuel‐fired power plants are still the principal power producers in most power systems. Retrofitting these pollutant generators with carbon capture and storage (CCS) technology can be a key solution to decarbonisation, especially for power systems with low expansion potential for renewable and hydroelectric energy resources. This study presents a coordinated generation and transmission expansion planning (G&TEP) and CCS expansion planning model for carbon emission constrained power systems. The proposed model determines the optimal order and time of retrofitting carbon emitter generators with CCS technology coordinated with the G&TEP. The limits on renewable resources capacity expansion potential and the yearly emission reduction targets are considered. Additionally, the proposed model allows for determining the incentives that are to be offered by the central planning authority to the pollutant generators to incentivise their participation in emission reduction through CCS retrofitting. The problem is formulated as a mixed‐integer linear programming model and is decomposed into a master and three subproblems to tackle the large‐scale nature of the developed optimisation problem. Numerical results demonstrate that a coordinated G&TEP and CCS expansion planning is a least‐cost planning solution for emission constrained power systems with low expansion capacity potential for renewable and hydroelectric resources.
Applied Energy, 2014
This paper approaches the CCEP and CCS planning problems for a country by considering multi-period planning scenario. New pinch analysis and optimisation techniques are proposed. A case study based on Malaysia energy sector planning is reported. a b s t r a c t Carbon constrained energy planning (CCEP) is useful to ensure that the CO 2 emissions limit for a region is met through deployment of low-carbon technologies. The increased demand in energy consumption due to economic growth requires additional energy supply and generation which would subsequently increase the carbon emissions. Nevertheless, most countries are now committed to reduce carbon emission to achieve long term sustainability goals. However, the development of alternative energy sources or carbon capture and storage (CCS) initiatives for power plants entails major capital investments. This paper demonstrates how these issues may be handled using CCEP with insight-and optimisation-based targeting techniques for multi-period scenarios. Both approaches were developed recently for CCEP problems, but previous techniques were limited to single-period planning. The extensions to multi-period scenarios are demonstrated in this work with hypothetical illustrative examples, as well as a Malaysian case study.
Applied Energy, 2010
This paper describes a general modeling approach for optimal planning of energy systems subject to carbon and land footprint constraints. The methodology makes use of the source-sink framework derived from the analogies with resource conservation networks used in process integration. Two variants of the modeling approach are developed for some of the important technologies for carbon emissions abatement: liquid biofuels in transportation, and carbon dioxide capture and storage in power generation. Despite the positive impact on environment, widespread use of these technologies has certain disadvantages. In case of biofuels, their production may strain agricultural resources, that are needed also for satisfying food demands. At the same time, carbon capture and storage is rather expensive technology and its practical implementation in power facilities must be carefully considered and planned. Optimum utilization of both technologies is identified with flexible and expandable mathematical modeling framework. Case studies are used to illustrate the variants of the methodology.
Sustainable Production and Consumption, 2023
A dependable and sustainable energy supply is crucial as energy consumption continues to rise due to population growth, economic development, and improved living standards. The use of fossil fuels leads to CO 2 emissions and are subject to volatility in prices. Capital-intensive technologies to reduce emissions are challenging to implement on a practical scale, and economic instruments are likely to play a role in future energy systems by encouraging adoption of these technologies. Carbon trading is an emerging economic instrument that enables entities (plants, governments, etc.) to exchange emission rights, allowing economic and environmental aspects to be balanced. This study introduces a scalable carbon trading modelling approach, integrated into previously developed DECO2 open-source energy planning framework. Direct and indirect optimisation approaches are proposed, both consisting of superstructure-based mixed-integer nonlinear programming formulations. Carbon price is a variable in the direct optimisation or a parameter in the indirect optimisation approach. While the direct optimisation approach involves more non-linearity, it is shown to result in solutions with greater decarbonisation, higher profits, and lower costs, compared to the indirect optimisation results. A novel feature of this multi-period model not considered in previous works is the simultaneous emissions trading across time periods and among entities (power plants and government). This enables efficient and coordinated emission allowances trading among various entities and timeframes. Various new costs and revenue streams are added into the energy planning framework; therefore, profits can also be predicted, along with predictions of electricity prices. New energy resources (nuclear and wind) and carbon capture utilisation and storage are also introduced to the modified DECO2 model. The models are tested on the Pakistan's power sector. Minimisation of emissions using direct optimisation showed that the carbon trading increased profits significantly in the second, third, and fourth planning periods (4.74, 3.86, and 3.55 times, respectively), but in the first period, profits were slightly higher without carbon trading (1.06 times more). Minimisation of budget using indirect optimisation showed higher profits in case of no carbon trading for all the periods. Between 2021 and 2040, hydropower is expected to grow the most (by a minimum of 3.14 times and a maximum of 15.87 times), followed by solar (with an expected increase between 2.54 and 3.26 times) and wind generation (which may increase by 2.35 to 2.66 times). Deployment of emission reduction technologies is significantly lower when carbon trading is implemented as compared to when it is not, due to increased pressure on CO 2-intensive generation. Results show that incorporating carbon trading into an energy market leads to both financial (increased profits) and environmental (lower emissions) sustainability, and that using direct optimisation approach increases benefits of carbon markets.
International Journal of Greenhouse Gas Control, 2008
i n t e r n a t i o n a l j o u r n a l o f g r e e n h o u s e g a s c o n t r o l 2 ( 2 0 0 8 ) 1 0 5 -1 2 9
Renewable Energy, 2010
This paper presents a Mixed Integer Linear Programming (MILP) model that was developed for the optimal planning of electricity generation schemes for a nation to meet a specified CO 2 emission target. The model was developed and implemented in General Algebraic Modeling System (GAMS) for the fleet of electricity generation in Peninsular Malaysia. In order to reduce the CO 2 emissions by 50% from current CO 2 emission level, the optimizer selected a scheme which includes Integrated Gasification Combined Cycle (IGCC), Natural Gas Combined Cycle (NGCC), nuclear and biomass from landfill gas and palm oil residues. It was predicted that Malaysia has potential to generate up to nine percent of electricity from renewable energy (RE) based on the available sources of RE in Malaysia.
Chemical Engineering Transactions, 2014
Climate change is increasing as an effect of human activities around the world. The reduction of CO2 emissions by human activities would be the most important measure to reduce this negative effect. Recently, many countries around the world have committed to reduce his CO2 emissions over time. In this context, the world has been struggling to balance the growth in energy requirement and environment conservation for a sustainable future, mainly due the adverse environmental, social and economic impacts of global warming that are associated with greenhouse gas emissions. In the last decade, some methodologies based on Pinch Analysis (Linnhoff et al., 1982) were developed as a tool for carbon emission reductions and planning. Thus, the concepts of Pinch Analysis were applied to solve carbon transfer, maximum carbon recovery, minimum carbon targets and the design of carbon exchange networks. Focusing in planning for the power generation sector, a new methodology is presented based in th...
2015 48th Hawaii International Conference on System Sciences, 2015
In this paper, a much more detailed representation of the nation's electricity system than has been traditionally used in policy models is employed. This detailed representation greatly increases the computational difficulty of obtaining optimal solutions, but is necessary to accurately model the location of new investment in generation. Given the proposed regulation of CO 2 emissions from US power plants, an examination of economically efficient policies for reducing these emissions is warranted. The model incorporates realistic physical constraints, investment and retirement of generation, and price-responsive load to simulate the effects of policies for limiting CO 2 emissions over a twenty-year forecast horizon. Using network reductions for each of the three electric system regions in the U.S. and Canada, an optimal economic dispatch, that satisfies reliability criteria, is assigned for 12 typical hour-types in each year. Three scenarios are modeled that consider subsidies for renewables and either CO 2 emissions regulation on new investment or cap-and-trade. High and low gas price trends are also simulated and have large effects on prices of electricity but small impacts on CO 2 emissions. Low gas prices with cap-and-trade reduce CO 2 emissions the most; large subsidies for renewables alone do not reduce carbon emissions much below existing levels. Extensive retirement of coal-fired power plants occurs in all cases.
Nafta, 2009
The paper deals with problems of energy system development planning under restrictive conditions, which will be imposed by global climate preservation agreements. It analyses the problems of planning and impacts of particular primary energy forms and technologies. In addition, it specifies risks, restrictions and planning conditions. Pilot investigations of possible consequences of development restrictions related to considerable reductions of CO 2 emissions on energy production and consumption structure are presented. Significant structural changes and cost increases are pointed out.
International Journal of Greenhouse Gas Control, 2010
The aim of this study is to discuss the long term analysis of post-Kyoto commitments, with the modelling tool ETSAP-TIAM-FR. Through the specification of CO 2 mitigation targets scenarios covering the period 2000-2050, this analysis focuses on the effects of these carbon constraints on several indicators such as global and regional CO 2 emissions, the cost of the climate policy, carbon marginal costs, the primary energy consumption and the energy mix. This paper compares global efforts of CO 2 mitigation with the cost of carbon and finally discusses the development of CCS technologies.
Energy, 2015
Concerns related to climate change and security of energy supply are pushing various countries to make strategic energy planning decisions. This requires the development of energy models to aid decisionmaking. Large scale energy models are often very complex and use economic optimization to define energy strategies. Thus, they might be black-boxes to public decision-makers. This work aims at overcoming this issue by proposing a new modelling framework, designed to support decision-makers by improving their understanding of the energy system. The goal is to show the effect of the policy and investment decisions on final energy consumption, total cost and environmental impact. The modelling approach and the model structure are described in detail. Final energy consumption is represented as the sum of three main components: heating, electricity and transportation. In this framework, a sequential modelling strategy allows the assessment of the competition between electricity and fuels in the heating and transportation sectors without increasing the model complexity. A monthly resolution is chosen in order to highlight seasonality issues of the energy system. Developed with the goal of being easily adaptable to any large-scale energy system, the modelling approach is currently implemented within an online energy calculator for the case of Switzerland.
Industrial & Engineering Chemistry Research, 2005
This paper considers the problem of reducing CO 2 emissions from a power grid consisting of a variety of power-generating plants: coal, natural gas, nuclear, hydroelectric, and alternative energy. The problem is formulated as a mixed integer linear program (MILP) and implemented in GAMS (General Algebraic Modeling System). Preprocessing and variable elimination strategies are used to reduce the size of the model. The model is applied to an existing Ontario Power Generation (OPG) fleet analyzed under three different operating modes: (1) economic mode, (2) environmental mode, and (3) integrated mode. The integrated mode combines the objectives of both the economic and environmental modes through the use of an external pollution index as a conversion factor from pollution to cost. Two carbon dioxide mitigation options are considered in this study: fuel balancing and fuel switching. In addition, four planning scenarios are studied: (1) a base-load demand, (2) a 0.1% growth rate in demand, (3) a 0.5% growth rate in demand, and (4) a 1.0% growth rate in demand. A sensitivity analysis study is carried out to investigate the effect of parameter uncertainties such as uncertainties in natural gas price, coal price, and retrofit costs on the optimal solution. The optimization results show that fuel balancing can contribute to the reduction of the amount of CO 2 emissions by up to 3%. Beyond 3% reductions, more stringent measures that include fuel switching and plant retrofitting have to be employed. The sensitivity analysis results indicate that fluctuations in gas price and retrofit costs can lead to similar fuel-switching considerations. The optimal carbon dioxide mitigation decisions are found, however, to be highly sensitive to coal price.
Energies, 2020
Cheap and clean energy demand is continuously increasing due to economic growth and industrialization. The energy sectors of several countries still employ fossil fuels for power production and there is a concern of associated emissions of greenhouse gases (GHG). On the other hand, environmental regulations are becoming more stringent, and resultant emissions need to be mitigated. Therefore, optimal energy policies considering economic resources and environmentally friendly pathways for electricity generation are essential. The objective of this paper is to develop a comprehensive model to optimize the power sector. For this purpose, a multi-period mixed integer programming (MPMIP) model was developed in a General Algebraic Modeling System (GAMS) to minimize the cost of electricity and reduce carbon dioxide (CO2) emissions. Various CO2 mitigation strategies such as fuel balancing and carbon capture and sequestration (CCS) were employed. The model was tested on a case study from Paki...
Energy, 2011
This paper studies the cost of energy (COE) for several emerging, fossil fuel power plants such as an integrated gasification combined cycle (IGCC) power plant, a natural gas combined cycle (NGCC) power plant, and a pulverized coal (PC) power plant under three different scenarios defined by the International Energy Agency (IEA). In order to compare the COE for each power plant more realistically, the concept of the 20-year levelized cost of energy (LCOE) was used. Since previous LCOE analyses did not consider the changes in fuel price and CO 2 prices, the reliability of previous LCOE results is not good enough to be acceptable for future energy planning. In this study, modified LCOEs, which consider the changes in fuel and CO 2 prices with respect to the different scenarios were suggested in order to increase the reliability of the economic comparisons of emerging, fossil power plants. In addition, energy planning was done in order to present the applicability of the proposed calculation method for the COE.
International Journal of Hydrogen Energy, 2019
Long-term planning for replacement of fossil fuel energy technologies with renewables is of great importance for achieving GHG emission reduction targets. The current study is focused on developing a five-year mathematical model for finding the optimal sizing of renewable energy technologies for achieving certain CO 2 emission reduction targets. A manufacturing industrial facility which uses CHP for electricity generation and natural gas for heating is considered as the base case in this work. Different renewable energy technologies are developed each year to achieve a 4.53% annual CO 2 emission reduction target. The results of this study show that wind power is the most cost-effective technology for reducing emissions in the first and second year with a cost of 44 and 69 CAD per tonne of CO 2 , respectively. Hydrogen, on the other hand, is more cost-effective than wind power in reducing CO 2 emissions from the third year on. The cost of CO 2 emission reduction with hydrogen doesn't change drastically from the first year to the fifth year (107 and 130 CAD per tonne of CO 2). Solar power is a more expensive technology than wind power for reducing CO 2 emissions in all years due to lower capacity factor (in Ontario), more intermittency (requiring mores storage capacity), and higher investment cost. A hybrid wind/ battery/hydrogen energy system has the lowest emission reduction cost over five years. The emission reduction cost of such hybrid system increases from 44 CAD per tonne of CO 2 in the first year to 156 CAD per tonne of CO 2 in the fifth year. The developed model can be used for long-term planning of energy systems for achieving GHG emission targets in a regions/country which has fossil fuel-based electricity and heat generation infrastructure.
dyna.unalmed.edu.co
The generation expansion planning (GEP) problem consists in determining the type of technology, size, location and time at which new generation units must be integrated to the system, over a given planning horizon, to satisfy the forecasted energy demand. Over the past few years, due to an increasing awareness of environmental issues, different approaches to solve the GEP problem have included some sort of environmental policy, typically based on emission constraints. This paper presents a linear model in a dynamic version to solve the GEP problem. The main difference between the proposed model and most of the works presented in the specialized literature is the way the environmental policy is envisaged. Such policy includes: i) the taxation of CO 2 emissions, ii) an annual Emissions Reduction Rate (ERR) in the overall system, and iii) the gradual retirement of old inefficient generation plants. The proposed model is applied in an 11region to design the most costeffective and sustainable 10technology US energy portfolio for the next 20 years.
Journal of Environmental Management, 2010
This paper considers the problem of reducing CO 2 emissions from a power grid consisting of a variety of power-generating plants: coal, natural gas, nuclear, hydroelectric, and alternative energy. The problem is formulated as a mixed integer linear program (MILP) and implemented in GAMS (General Algebraic Modeling System). Preprocessing and variable elimination strategies are used to reduce the size of the model. The model is applied to an existing Ontario Power Generation (OPG) fleet analyzed under three different operating modes: (1) economic mode, (2) environmental mode, and (3) integrated mode. The integrated mode combines the objectives of both the economic and environmental modes through the use of an external pollution index as a conversion factor from pollution to cost. Two carbon dioxide mitigation options are considered in this study: fuel balancing and fuel switching. In addition, four planning scenarios are studied: (1) a base-load demand, (2) a 0.1% growth rate in demand, (3) a 0.5% growth rate in demand, and (4) a 1.0% growth rate in demand. A sensitivity analysis study is carried out to investigate the effect of parameter uncertainties such as uncertainties in natural gas price, coal price, and retrofit costs on the optimal solution. The optimization results show that fuel balancing can contribute to the reduction of the amount of CO 2 emissions by up to 3%. Beyond 3% reductions, more stringent measures that include fuel switching and plant retrofitting have to be employed. The sensitivity analysis results indicate that fluctuations in gas price and retrofit costs can lead to similar fuel-switching considerations. The optimal carbon dioxide mitigation decisions are found, however, to be highly sensitive to coal price.
2010
Problem statement: Electricity can be generated from different type of technologies such as fossil and non-fossil power plants. Among these technologies, coal-fired power plants have been a major route for electricity generation. Recently, environmental constraints were imposed over the coal power plant operations in order to reduce their emissions. Besides, renewable energy power plants such as hydroelectric, wind, solar and geothermal have emerged with a potential of low impact on the environment. Approach: In this study, coal-fired power plants with a mix of low emission power plants were analyzed from the viewpoint of coal power plant emission reductions while supplying electricity demand. Electricity capacity expansion was also included within the problem to insure sufficient electricity supply in circumstances of emission reduction constraints. Results: Pollutants such as Nitrogen Oxides (NO x), Sulfur Oxides (SO x) and mercury (Hg) were assumed to be the target compounds. A discrete mathematical programming model was formulated to give an assessment about the coal-fired power plant operations in an electricity generation network. Different scenarios of increased electricity demand and emission reduction targets were applied on Ontario Power Generation (OPG) network to give an illustration of the proposed model. Conclusion: The case study results show the significant impact of combining renewable energy or zero emission technologies on the optimal operation of a network that combines coal-fired power plants.
Journal of Cleaner Production, 2012
The addition of carbon capture and storage to a power station will impact the net power generated and increase the cost of electricity produced from the power stations. A method is presented to help design the carbon capture and compression process retrofitted to the power station. It combines simulation, automated heat integration and multi-objective optimisation. The methodology is applied to a coal fired power station combined with potassium carbonate based solvent absorption. To capture 90% of the CO 2 emissions the energy penalty, the ratio of the change in efficiency of the power station due to the addition of carbon capture and storage relative to the efficiency of the original power station, can be reduced from 38% to 14% using this method. However to minimise the cost of electricity, more modest reductions in energy penalty of 25%e30% are recommended.
Loading Preview
Sorry, preview is currently unavailable. You can download the paper by clicking the button above.