Energy, 2008

This work presents algebraic targeting techniques for energy sector planning with carbon (CO 2 ) emission and land availability constraints. In general, it is desirable to maximize the use of low-or zerocarbon energy sources to reduce CO 2 emission. However, such technologies are either more expensive (as with renewable energy) or more controversial (as in the case of nuclear energy or carbon capture and storage) than conventional fossil fuels. Thus, in many energy planning scenarios, there is some interest in identifying the minimum amount of low-or zero-carbon energy sources needed to meet the national or regional energy demand while maintaining the CO 2 emission limits. Via the targeting step of pinch analysis, that quantity can be identified. Besides, another related problem involves the energy planning of biofuel systems in view of land availability constraints, which arises when agricultural resources need to be used for both food and energy production. Algebraic targeting approach of cascade analysis technique that was originally developed for resource conservation network is extended to determine targets or benchmarks for both of these problems.

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...

Energies, 2019

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...

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

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.

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.

International Journal of Greenhouse Gas Control, 2010

Modern Applied Science, 2015

Carbon capture and storage (CCS) is one of the technologies to reduce greenhouse gas emissions (GHG) tocapture of CO2 from the flue gas of a power plant that typically use coal as a Source of energy and then store it ina suitable geological storage (in specific locations). In practice, these sites may not be readily available forstorage at the same time that the Sources (GHG producing) are operating which gives rise to multi – periodplanning problems. This study presents a mathematical approach by considering constraints limit flowratereceived by Sink, various time availability of Sink and Source and calculation with the purpose to determine theminimum cost network which is getting the maximum load that is exchanged from Source to Sink. Illustrativecase studies are given to demonstrate the application of mathematical models to obtained with the exact result ofthe exchange network from Source to Sink. Derived from network obtained from the calculation of theMaximum Load Source to Sin...

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.

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.