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Power sector, as one of the least progressed division, is limiting the socioeconomic development in Afghanistan. Although the country has a vast solar energy potential with a bright prospect for growth, however inadequate endorsement and attention have prevented its proper use. Meanwhile, Kabul the capital city and one of the fastest growing cities in the world, is suffering severe challenges to supply its energy needs. Presently, Kabul electrical system is subjected to insecure and insufficient supply due to the lack of integrated networks and deployment of Renewable Energy (RE) sources. This research investigates an appropriate approach by introducing two Linear Fresnel Reflector (LFR) plants with a total capacity of 120 MW to overcome the present challenges in Kabul city. The proposed LFR units are incorporated with an energy storage system of full capacity production for five hours to cover the power shortage at night. The design aspect of LFR is specified by using of System Adviser Model (SAM). Levelized Cost of Electricity (LCOE) and the total annual output of the proposed LFR units are estimated as 0.2508$/kWh and 294,657.28 kWh respectively. To minimize the total operating costs of the integrated model and mitigate CO2 emissions, an optimal Unit Commitment is (UC) fulfilled as well. UC is accomplished by using MATLAB INTLINPROG optimization toolbox.

Due to the electric power liberalization, many power producers are entering into the deregulated power market. Most of the electrical power companies are introducing Renewable Energy Sources (RES), which will increase the power system uncertainty. Consequently, the underlyng uncertainty imposed by RES will increase the likelihood of voltage instability and voltage collapse. Also, fluctuations in supply and demand are increased by the introduction of renewable energies. On the other hand, Demand Response Program (DRP) is one of the potential solutions that reduces the power fluctuations. In this study, we proposed multi-objective optimal operation based Unit Commitment (UC) considering voltage stability and demand response. The effectiveness of the proposed method is verified by simulation results using the MATLAB.

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