Study on the Optimal Operation of a Hydropower Plant Group Based on the Stochastic Dynamic Programming with Consideration for Runoff Uncertainty

Hydropower plant operation reorganizes the temporal and spatial distribution of water resources to promote the comprehensive utilization of water resources in the basin. However, a lot of uncertainties were brought to light concerning cascade hydropower plant operation with the introduction of the stochastic process of incoming runoff. Therefore, it is of guiding significance for the practice operation to investigate the stochastic operation of cascade hydropower plants while considering runoff uncertainty. The runoff simulation model was constructed by taking the cascade hydropower plants in the lower reaches of the Lancang River as the research object, and combining their data with the copula joint function and Gibbs method, and a Markov chain was adopted to construct the transfer matrix of runoff between adjacent months. With consideration for the uncertainty of inflow runoff, the stochastic optimal operation model of cascade hydropower plants was constructed and solved by the SDP algorithm. The results showed that 71.12% of the simulated monthly inflow of 5000 groups in the Nuozhadu hydropower plant drop into the reasonable range. Due to the insufficiency of measured runoff, there were too many 0 values in the derived transfer probability, but after the simulated runoff series were introduced, the results significantly improved. Taking the transfer probability matrix of simulated runoff as the input of the stochastic optimal operation model of the cascade hydropower plants, the operation diagram containing the future-period incoming water information was obtained, which could directly provide a reference for the optimal operation of the Nuozhadu hydropower plant. In addition, taking the incoming runoff process in a normal year as the standard, the annual mean power generation based on stochastic dynamic programming was similar to that based on dynamic programming (respectively 305.97 × 108kW⋅h and 306.91 × 108kW⋅h), which proved that the operation diagram constructed in this study was reasonable.

Assessment of Effect of Hydropower Plant Projects on Socio-Environmental Sustenance and Development in Rwanda: A Review Done At Rubagabaga Hydropower Ltd.

The study investigated the socio-economic and environmental impact of hydropower projects in Rwanda with a case study of Rubagabaga hydropower Ltd operating from Nyabihu District. It examines the impact of a socio-economic and environmental hydropower plant in Rwanda, identifies the challenge hydropower plants face in Rwanda, and finally investigates the relationship between hydro powers and their socio-economic impact in Rwanda? In this research, the quantitative research design is based on statistical data of the research that was used with quantitative and qualitative methods. Questionnaires were used to collect data. The target population of this study was made up of 252 participants including 154 respondents all from ten different villages surrounding the Rubagabaga plant in Nyabihu District. Data were analyzed using descriptive and correlation analysis and tables that were interpreted to confirm or deny the relevance of the main and specific objectives. Based on results from table no.16 demonstrates that the beta= 0.397 with the t value of 2.333 and the p-value of 0. 021. Since the p-value is less than 0.05, the researcher rejected the null hypothesis and considered it an alternate. There is a strong positive relationship between environmental assessment of hydropower plant projects and socio-environmental sustenance and development. In a nutshell, the researcher has rejected the null hypothesis and considered its alternate. Community structure and dynamics have a positive influence on socio-environmental sustenance and development. Table no.16 shows that beta= 0.341 with the t value of 2.668 as the p-value was 0.009. Since the p-value is less than 0.05. Therefore, the researcher rejected the null hypothesis and considered it an alternate. According to table no.21, the changes in community structure and dynamics of the hydropower plant project cause the increase of 0.341 (34.1%) of the socio-environment sustenance and development. The ratio of beta modal results for the t value expressed t=2.66 hence the probability value is significant on socio-environment sustenance and development noting that sig. =0.009. Carefully, the researcher has rejected the null hypothesis and considered its alternate. With this in mind, community structure and dynamics has a positive influence on socio-environmental sustenance and development. Table no.16 has shown beta= 0.478 with the t value of 4.543 as the p-value was 0.000 which is less than 0.05. According to the findings, the changes in government policies, stability, and support of hydropower plant project causes the increase of 0.478 (47.80%) of the socio-environment sustenance and development. The ratio of beta modal results for the t value expressed t= 4.54 hence the probability value is significant on socio-environment sustenance and development noting that sig. =0.000.

Optimization of the operation of Dokan hydropower development using Cuckoo Search Algorithm

In this paper one of the recently developed metaheuristic algorithms, the Cuckoo Search algorithm is used for the optimization of the operation of a large hydropower plant in Kurdistan, Iraq. The optimization problem is to realize an annual planned energy generation with monthly imposed fractions. The obtained results are excellent, nevertheless, there are some limitations of the algorithm determined by the initial level into the reservoir and a certain correlation between the type of the year, the starting level and the planned energy to be realized.

Identification of Most Significant Parameter of Impact of Climate Change and Urbanization on Operational Efficiency of Hydropower Plant

The operational performance of hydropower plants (HPPs) is largely affected as the output from the plant entirely depends on the rainfall and demand from consumers both of which are compromised due to the vulnerability in climatic patterns and rapid change in urbanization rate. Although, not all the parameters are equally affected and the present study aims to find the degree of impact on the various correlated parameters on which production efficiency of HPPs varies. In this aspect, a neural network concept was used as decision making tool to identify the most significant parameters with respect to change in climate, urbanization along with machine failure because as a combined effect of the first two parameters, the probability of machine failure will also increase. The result from the study provides an opportunity to mitigate the impact that can be caused as a result of climate change impact and change in rate of urbanization. According to the result it was found that Efficiency of Generators is the most significant parameter of impact of climate change and urbanization on operational efficiency of hydropower plant. The result from the scenario analysis suggested that if the A2 scenario becomes true in 2061-70 there will be a maximum decrease in the OE and if land use scenario: PR story line is found to be adopted in the future world of 2020-30 the change in OE will be the greatest (an increase of 6.056%) compared to any other scenario developed for the impact of urbanization followed by land use change scenario of the 2031-40 decade, which will be equal to an increase of 5.247% compared to the baseline.

PREDIKSI DEBIT ALIRAN MASUK KE TELAGA MENJER MENGGUNAKAN PERSAMAAN NERACA AIR DAN PEMODELAN HEC-HMS

The Menjer lake is the main source for Hydroelectric Power Plant of the PLTA Garung. Information about the water balance and the potential of existing water resources in the Menjer Catchment Area (DTA) is needed to obtain an efficient operating pattern, the sustainability of the Garung hydropower plant, and good management of the Menjer Lake. The purpose of this study was to estimate the inflow of three main rivers in the Menjer catchment area using HEC-HMS hydrological and water balance approach. Simulated results of the HEC-HMS model shows that the average of total the inflows of three main rivers to the Menjer lake in 2017, 2018 and 2019 during rainy season are 0.954 m3/s, 0.944 m3/s, and 1.017 m3/s, and during dry season are 0.820 m3/s, 0.783 m3/s, and 0.80 m3/s, respectively. While the prediction results of the discharge with the equation of the water balance shows that the average of total river inflows to the Menjer lake during rainy season is 2017 is 1.628 m3/s, in 2018 it is 1.579 m3/s, and in 2019 it is 3.296 m3/s and during dry season is 1.893 m3/s in 2017, 1.176 m3/s tahun 2018, and 1.893 m3/s in 2019. These results indicate that the results of discharge modeling with HEC-HMS are smaller than those predicted by the water balance equation. The study concluded that HEC-HMS could be used to predict daily inflows. However, further calibration and validation need to be carried out by recommending installing a river flow monitoring station at each river outlet.Keywords: water balance HEC-HMS, inflow prediction

Performance Analysis of a Low Head Water Vortex Turbine

A small hydropower plant is an environment-friendly renewable energy technology. The run-of-river type gravitational water vortex turbine can be designed to produce electricity at sites with low water heads. In this study, an experimental investigation was undertaken on this type of turbine with a water tank and a runner which is connected to a shaft. At the end of the shaft, a rope brake was attached to measure the output power, torque and overall efficiency of the vortex turbine by varying flow rates. The designed vortex turbine can achieve an overall efficiency of . The experimental results were validated with available data in the literature and theories associated with the turbine. The results also showed that the flow rate plays a vital role in generating power, torque as well as overall efficiency. The project was completed using local resources and technologies. Moreover, as water is used as the input power, this project is eco-friendly which has no adverse effect on the environment.