Risk Averse Two-Stage Stochastic Optimization Model for the Electric Power Generation Capacity Expansion Problem

2012 ◽  
Author(s):  
Marida Bertocchi ◽  
Maria Teresa Vespucci ◽  
Stefano Zigrino
Keyword(s):  
Power Generation ◽  
Stochastic Optimization ◽  
Electric Power ◽  
Optimization Model ◽  
Capacity Expansion ◽  
Risk Averse ◽  
Two Stage ◽  
Electric Power Generation ◽  
Generation Capacity

Performance Analysis of Integrated Solar Tower With a Conventional Heat and Power Co-Generation Plant

2018 ◽  
Vol 141 (2) ◽  
Author(s):  
Esmail M. A. Mokheimer ◽  
Yousef N. Dabwan
Keyword(s):  
Power Generation ◽  
Power Plant ◽  
Electric Power ◽  
Gas Turbine ◽  
Economic Feasibility ◽  
Field Size ◽  
Electric Power Generation ◽  
Electricity Cost ◽  
Generation Capacity ◽  
Solar Field

This paper presents the results of a thermo-economic analysis of integrating solar tower (ST) with heat and power cogeneration plants that is progressively being installed to produce heat and electricity to operate absorption refrigeration systems or steam for industrial processes. The annual performance of an integrated solar-tower gas-turbine-cogeneration power plant (ISTGCPP) with different sizes of gas turbine and solar collector's area have been examined and presented. Thermoflex + PEACE software's were used to thermodynamically and economically assess different integration configurations of the ISTGCPP. The optimal integrated solar field size has been identified and the pertinent reduction in CO2 emissions due to integrating the ST system is estimated. For the considered cogeneration plant (that is required to produce 81.44 kg/s of steam at 394 °C and 45.88 bars), the study revealed that (ISTGCPP) with gas turbine of electric power generation capacity less than 50 MWe capacities have more economic feasibility for integrating solar energy. The levelized electricity cost (LEC) for the (ISTGCPP) varied between $0.067 and $0.069/kWh for gas turbine of electric power generation capacity less than 50 MWe. Moreover, the study demonstrated that (ISTGCPP) has more economic feasibility than a stand-alone ST power plant; the LEC for ISTGCPP is reduced by 50–60% relative to the stand-alone ST power plant. Moreover, a conceptual procedure to identify the optimal configuration of the ISTGCPP has been developed and presented in this paper.

scholarly journals Optimization of the Midterm Electricity Generation Mix Considering the Effects of Water, Land and Carbon Footprints

10.29007/vpvk ◽  
2018 ◽  
Author(s):  
Mohsen Bozorg ◽  
Hamed Mazandarani Zadeh ◽  
Dragan Savic
Keyword(s):  
Power Generation ◽  
Power Consumption ◽  
Electric Power ◽  
Electricity Generation ◽  
Optimization Problem ◽  
Solar Thermal ◽  
Series Data ◽  
Electric Power Generation ◽  
Advantages And Disadvantages ◽  
Generation Capacity

Electric energy plays a key role in the development of modern societies. Each of the electric power generation technologies (e.g., hydroelectric, wind, solar, thermal, etc.) has some advantages and disadvantages with respect to the fundamental resource indicators, including water footprint, land footprint, carbon footprint, as well as electricity generation costs. Due to the shortage and frequent crisis associated with the above resources, optimal selection of the mix of electricity generation technologies is very important and the share of each technology in the capacity expansion of the generation system must be carefully defined. Iran is in an arid and semi-arid region, with less than one third of the average world precipitation. Moreover, the available water resources are restricted due to the water crises in the Middle-East region. In this paper, we first estimated the peak power consumption of Iran in 2024, based on the time-series data from 2004 to 2014. Then, we formulated an optimization problem to find the share of each electric power generation technology to cover the required extra generation capacity for supplying the power consumption in the target year 2024, considering the effect of the four aforementioned performance indicators. The optimization problem is solved using Genetic Algorithm. Numerical results show that in the target year, 20 GW of electricity should be added to the generation capacity. The results also show that, solar thermal and solar photovoltaic are the best electric generation technologies regarding the available resources.

scholarly journals OPTIMIZATION MODEL FOR THE RUSSIAN ELECTRIC POWER GENERATION STRUCTURE TO REDUCE ENERGY INTENSITY OF THE ECONOMY

2019 ◽  
Vol 9 (3) ◽  
pp. 379-387
Author(s):  
Alexander N. Semin ◽  
Vadim V. Ponkratov ◽  
Kirill G. Levchenko ◽  
Andrey S. Pozdnyaev ◽  
Nikolay V. Kuznetsov ◽  
...  
Keyword(s):  
Power Generation ◽  
Electric Power ◽  
Optimization Model ◽  
Energy Intensity ◽  
Electric Power Generation ◽  
Generation Structure
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