دانلود ترجمه مقاله بررسی جداسازی و ذخیره کربن در برنامه ریزی توسعه تولید الکتریسیته

Nowadays, CO2 is the primary greenhouse gas pollutant and fossil fuel-fired electrical power plants are the major producer of CO2. In this regard, it is required to equip the electrical power plants with carbon capture and storage (CCS) systems. CCS system can capture about 90 percent of the emitted carbon and significantly decreases the environmental pollutions. On the other hand, implementation of CCS increases the capital cost of the electrical power plants. As a result, the investors (or planners) in electricity generation sector should decide on constructing fossil fuel-fired units with CCS, or installing the units without pollutions such as nuclear and renewable units. But, due to growing demand for energy in the world, limitations of the renewable energy resources, and hazards of the nuclear energy, the consumption of fossil fuels is expected to growth through 2035. Regarding these issues, the investors should decide on a combination of nuclear and renewable energy power plants as well as fossil fuel-fired units equipped with CCS. This combined planning may be carried out to minimize the investment cost and the pollutions at the same time, while it satisfies the growing energy demand over the future years. The proposed decision making system is mathematically expressed through electricity generation expansion planning (GEP) problem. This paper addresses a multistage GEP including nuclear units, renewable energy units, and different fossil fuel-fired units equipped with CCS. The proposed GEP minimizes the planning costs and CO2 at the same time, while it considers CCS cost and revenue. The problem is mathematically expressed as a constrained, mixedinteger, and nonlinear optimization problem and solved using particle swarm optimization (PSO) algorithm. The problem is scheduled considering all practical constraints including security constraints of the network, and the generating units constraints of operation. Simulation results demonstrate that utilizing CCS significantly impacts on the planning output. Eventually, a comprehensive sensitivity analysis is carried out based on the CCS cost and revenue.