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Present communication is an attempt to explore the best PV technology suitable for PVT solar drying system through environmental and economic feasibility. Experimental setup for one of the PV technology (c‐Si) has been taken for experimental validation with theoretical model. Further, the environmental feasibility and environ economic evaluation for drying system having roof with various PV namely, c‐Si, p‐Si or m‐Si, a‐Si, CdTe, and CIGS have been evaluated through energy matrices (EPBT, EPF, and LCCE), CO2 emission, net CO2 mitigation and carbon credit earned which is based on energy and exergy output of the system on yearly basis. The economic analysis has been carried out with experimental data taken on c‐Si PVT drying system by considering grapes as a crop. Cogeneration efficiency has been calculated for different PV technologies and found to be highest for c‐Si PV technology that is, 61.71%, 77.98%, and 12.25% based on energy (electrical and thermal) gain, equivalent (overall) energy gain, and exergy gain, respectively. LCCE on energy basis reveals that for the five‐year system life, c‐Si and CIGS have equal efficiency but after five years, c‐Si is best. Cogeneration efficiency of system on the basis of energy (electrical + thermal) gain, equivalent (overall) energy gain and overall exergy gain found to be maximum with c‐Si PV technology that is, 61.71%, 77.98%, and 12.25%, respectively.

Please cite this article in press as: Singh, B., et al., GA-based multi-objective optimization for distributed generations planning with DLMs in distribution power systems. J. Electr. Syst. Inform. Technol. (2016), http://dx. AbstractIn the present scenario of all over world, the planning of distributed generations (DGs) in distribution power systems are very important issues from power system performances viewpoints. The broad categories of different types of DGs on the basis of their power delivering characteristics are considered T 1 , T 2 , T 3 and T 4 with different load models (DLMs) for the analysis in this paper. This paper presents the impact assessment of optimally placed different types of DGs (such as T 1 , T 2 , T 3 and T 4 ) with DLMs by employing genetic algorithm (GA) in the distribution power systems (DPSs) form total minimum real power loss of the system viewpoint. Different DPS performance parameters such as minimization of real power loss, minimization of reactive power loss, improvement of voltage profile, reduction of the short circuit current or MVA line capacity and reduction of the environmental green house gases like carbon dioxide (CO 2 ), sulphur dioxide (SO 2 ), nitrogen oxide (NO x ) and particulate matters in emergency e.g. under fault, sudden change in field excitation of alternators or load increase in the distribution power system are considered. The contribution of the present work is to investigate the comparisons of different DGs with DLMs by excercizing GA in the distribution systems form minimum total real power loss of the system viewpoint. The effectiveness of the proposed methodology is tested on IEEE-37 bus distribution test system. The different types of DGs (such as T 1 , T 2 , T 3 and T 4 ) with DLMs have shown different behaviours for power system performance indices such as PLI, QLI, VDI, SCCI and EIRI viewpoints. The sequence of overall power system performance indices such as PLI, QLI, VDI, SCCI and EIRI are as follows: T 2 > T 1 > T 4 > T 3 . This paper presents that the overall performance of T 2 type DG is better as compared to T 1 , T 3 and T 4 types DGs in the distribution system form minimum real power loss of the system viewpoint.Please cite this article in press as: Singh, B., et al., GA-based multi-objective optimization for distributed generations planning with DLMs in distribution power systems. J. Electr. Syst. Inform. Technol. (2016), http://dx.