With the increasing number of hydropower plants under construction and proposed in Nepal, the country is anticipated to experience a surplus of hydropower that exceeds its peak load demand. This surplus electricity becomes particularly high during the wet seasons, when hydropower production reaches its maximum capacity. This research focuses on the mathematical modeling of an alkaline electrolyzer, specifically analyzing the stack performance and the electricity flow within the balance of plants required to support the stack operation. The developed model is then used to estimate the production cost of hydrogen by utilizing forecasted surplus electricity up until the year 2030. The output of the study is expected to help in the sustainable utilization of surplus hydropower in the country, thus enhancing the low carbon economic development path. The study shows that there is a significant opportunity for hydrogen production from surplus hydroelectricity, ranging from 91 ktonne/year to maximum, of 414 ktonne/year. The average levelized cost of hydrogen is estimated at 5.65 USD/kg. The cost can be further reduced if policy interventions like tax rebates and tariff rate subsidies are in place.

Alkaline water electrolysis (AWE) operated by surplus electricity is suitable for producing green hydrogen in Nepal. Simulation models are built using DWSIM software for AWE, multistage compression, and the Organic Rankine Cycle (ORC). The AWE system's Capital Expenditure (CAPEX) is determined to be $47 million and Operational Expenditure (OPEX) of $7.65 million/year. The storage system, including the multistage compression system and Type IV cylinders, has a CAPEX of $52 million and an OPEX of $17 million/year. The ORC has a CAPEX of $500,000 and an OPEX of $200,000/year. The thermal power generated from AWE and multistage compression can be converted to electricity by the ORC and supplied to the AWE system. This process decreases the Levelized Cost of Hydrogen (LCOH) from $3.5141/kg over 5 years to $3.4725/kg over 25 years. The techno-economic analysis performed confirms the feasibility of implementing these plants in Nepal.

There are several sensors available in the market to measure the plane-of-array irradiance for photovoltaic applications. The prices of these sensors vary according to the design, calibration procedure, and conducted characterization. In this article, two types of silicon-based sensors with and without temperature correction capabilities are compared with a high-accuracy thermopile pyranometer to check their performance. The obtained results showed that silicon-based sensors deviate from the output of the pyranometers. The tested silicon-based pyranometers overestimate the irradiance with the median bias deviations of around 1.43% (with the average measured irradiance of 256 W/m2). For temperature-corrected silicon pyranometer, the bias deviation is 0.07% with the deviation range of -6.5%-10% (with the average measured irradiance of 257 W/m2). A working-class reference cell was also tested, resulting in a bias deviation of -1.74% and the deviation range of -13%-7% (with the average measured irradiance of 304 W/m2). The effect of air mass on the performance of cost-effective sensors was additionally analyzed. Within the measurement time window, the result also showed that for the silicon-based sensors under tests, the effects of the environmental conditions have the following qualitative order of influence: angle of incidence > red-shift > temperature. The performance of silicon-based sensors also showed seasonal dependence, being more accurate during summertime and wintertime, respectively, for the silicon pyranometer and the working-class reference cell. Finally, using the statistical evaluation, simple linear correction functions are introduced for silicon-based sensors.