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The records of suspended sediments and associated hydro-meteorology of the glacierized catchments are very limited in Sikkim Himalaya. Therefore, we carried out the first-ever estimate of suspended sediment transport from the meltwater stream of East Rathong Glacier for June-September during three consecutive melt seasons (2013–2015). These records were used to estimate the suspended sediment concentration (SSC), load (SSL), yield (SSY) and erosion rate (ER). The daily mean SSC was 105.75, 84.20, and 91.51 mg/l during melt seasons of 2013–2015 respectively. The monthly mean SSC of the combined melt season of 2013–2015 was 92.72, 107.14, 105.93 and 60.46 mg/l for June-September, respectively. The observation shows that July-August contributed to maximum SSC, accounting 70.45% of total SSC. Similarly, the monthly mean SSL for June-September was 55.64, 69.61, 65.75 and 25.72 tons, respectively. We observed high variability in SSL (CV = 0.54) than SSC (CV = 0.38) since the estimation of SSL depends on both discharge (Q) and SSC. The relationship between monthly mean SSC and Q was highly significant (R2 = 0.98) than daily SSC and Q (R2 = 0.25) due to reduced variability on a monthly scale. Further, mean SSY in the catchment was high during peak melting season (July-August), which substantially reduced during the end of the melting season. We estimated the mean SSY of 281.93 ton/yr km2 during the combined melt season (2013–2015). The average ER for the East Rathong Glacier basin was 1.04 mm/yr, which is lower than the ER of most of the Himalayan glaciers. We observed significant meteorological control of Tmean, Tmax and Rainfall in the transportation of suspended sediments from meltwater stream at a monthly scale. These in-situ based records on dynamics of suspended sediment and associated hydro-meteorological parameters are relevant for the planning and management of freshwater resources and planning for hydropower projects under a changing climate.

The hydropower sector is currently experiencing several technological developments. New technologies and sustainable practices are emerging to make hydropower more flexible and eco-friendly. Novel materials have also been recently developed to increase performance, durability, and reliability; however, no systematic discussions can be found in the literature. Therefore, in this paper, novel materials for hydropower applications are presented, and their performance, advantages, and limitations are discussed. For example, composites can reduce the weight of steel equipment by 50% to 80%, polymers and superhydrophobic materials can reduce head losses by 4% to 20%, and novel bearing materials can reduce bearing wear by 6%. These improvements determine higher efficiencies, longer life span, waste reduction, and maintenance needs, although the initial cost of some materials is not yet competitive with respect to the costs of traditional materials. The novel materials are described here based on the following categories: novel materials for turbines, dams and waterways, bearings, seals, and ocean hydropower.

This version of the article has been accepted for publication, after peer review and is subject to Springer Nature’s AM terms of use, but is not the Version of Record and does not reflect post-acceptance improvements, or any corrections. The Version of Record is available online at https://doi.org/10.1007/s10750-021-04709-4. Sustainable global energy production is back-stopped by hydropower which is responsible for a significant share of the green energy produced worldwide. Hydropower, however, does not come without some environmental impacts but has worked to reduce those impacts. Here, we discuss the historical, legislative, and design configurations of hydropower facilities located in three of the world’s most important producers: Brazil, Canada, and Norway. The background is intended to inform the collection of scientific papers from each country aimed at assessing and improving the sustainability of hydropower production that form the core of this special issue on sustainable hydropower. We review the development and key legislative history for hydropower in each country and point out the common backgrounds and interests each nation has in the continued sustainable development of its hydropower resources. Keywords Hydropower regulation Development History Facilities Legislation Sustainable production

In the last few decades, the energy demand is increasing globally which, given the present dependency of the energy generation on fossil fuels, results in a continuous increase in CO2 emissions. In an isolated electric grid system like in the SIDS, the majority of the electricity is produced by fossil fuels, therefore most of the SIDS nations are now focusing on Variable Renewable Energy sources (VREs). VREs such as wind and solar are hardly predictable and bring instabilities in the electric power system if not buffered by a storage system. Here we investigate the possibility of using Seawater Pump Storage Hydropower Systems (S-PSHS) as a renewable energy storage solution in an isolated electric grid. For this, the island of Curacao (one of the SIDS nations) is used as proof of the concept. For detecting potential locations for the S-PSHS sites on the island, GIS application was developed. The application of this conceptual proposed solution in similar systems is straightforward and it can be easily upscaled in other geographies. The concept of using seawater for the pumped hydro project is not common in practice and it is anticipated to have technical, environmental and financial challenges which are discussed in this paper.

Industrial development, increased demand for energy, limited fossil fuels, and the prevention of environmental damage have led to the use of renewable energy to produce power. The combined system includes renewable wind and solar energy systems or other renewable energy. The hybrid system has been widely used in recent decades to provide energy. In this research, an optimal integrated system has been used to generate electricity. The proposed system includes wind, hydropower, and photovoltaic systems. to estimate the maximum power generation and reduce fluctuations in electricity generation, three proposed algorithms have been used and three common solutions have been applied to solve the optimization problem. The performance of the combined system in different weather conditions has also been assessed. The results showed that among the three proposed algorithms, the model improved the Barnacles Mating Optimizer Algorithm (IBMO) has the best distribution and convergence. Among the three common solutions, a common solution has the most logical solution to the optimization problem. And among the different hydrological conditions, the highest electricity generation is related to the wet season. the most important role in the hybrid system related the hydropower so that despite the reduction of electricity produced in the wind and photovoltaic power plants, the hydropower plant compensates for the drop in production of these systems and causes the production flow to continue.

The world’s climate has changed dramatically in recent years due to the development of the industry. Climate change can significantly affect hydropower plants. One of the negative effects of climate change is the reduction of hydropower generation. Therefore, to better management of power supply and demand, the climate change effect on hydropower plants should be examined. The main purpose of this study is the prediction of future hydropower generation (2021–2050) in terms of climate change. One of the factors sensitive to climate change in hydropower plants is the amount of input flow to the reservoir. In this study, a method has been used that can increase the accuracy of flow estimation. This innovation is the use of the ANN model under the new version of the Developed Crow Search Algorithm (DCSA). This algorithm increases the accuracy of prediction by solving optimization disadvantages such as getting stuck in the optimal location, the imbalance between exploitation and exploration at different levels The results showed that the DCSA algorithm with minimum error (MSE = 1.06) and maximum correlation (R2 = 0.88) compared to other algorithms has the best performance. The results of the prediction of climate change under RCPs scenarios showed that the average annual power generation will decrease under RCP2.6 and RCP4.5 and RCP8.5 about 10.74% and% 16.38 and 22.25% respectively. Also, the average annual power generation under scenarios RCP2.6, RCP4.5, and RCP8.5 by 2050 are 740.33 MW, 603.12 MW, and 585.77 MW, respectively.

This study investigates the impact of monetary policy on renewable energy generation in Iran. It examines three types of renewable energy generation: total renewable energy generation; solid biomass and biogas energy generation; and the hydropower, solar, and wind group energy generation. The study uses the Kalman filter and vector autoregression (VAR) models to examine annual data from 1984 to 2016. The Kalman filter model showed that the money supply parameter moved with a steady trend, except for a sharp point during the Iran-Iraq War. A sharp point can be found for real interest rate parameter as well, although the time of global crisis and sanctions also affects this coefficient. The VAR model results indicate that only a shock to money supply can affect all the three renewable energy generation types.

Over the last decade, the rapid expansion of hydroelectric power generation has required an intense collaboration process between stakeholders. These relationships between the primary stakeholders – governments and large energy corporations – contextualise the discussion regarding governance regimes from a territorial perspective. The different levels of intervention that companies can exercise at the local, regional and national levels influence the various territorially embedded scales, places and networks that enable large-scale energy production. Therefore, the evolving role of borders and boundaries across territorial social groups and material interests influences the reach and extent of conflict/collaboration dynamics. With the purpose of exploring the effects of territorial factors of governance regimes on hydropower sustainability, this study adopts a mixed-methods sequential design approach using content analysis preceded by bibliometric data recollection and processing with high-end visualisation of the similarities mapping technique. These territorial factors can be divided into three separate fields of enquiry: institutional arrangements and spatial fixes, which can be captured spatio-temporally, and the role of local culture; stakeholder interdependencies, which must be studied in terms of the diverse scales on which they must interact to understand territorial-level conflict/collaboration dynamics; and joint actions and adaptative mechanisms that help to explain why changes in hydropower business governance regimes are attached to the territorial context. If we can understand the evolution of corporate sustainability dimensions in certain contexts, we might be able to capture the structured coherence of governance regimes in terms of the action–impact–adaptation cycle in the hydropower industry.

This paper presents renewable energy systems based on micro-hydro and solar photovoltaic for rural areas, with a case study in Yogyakarta, Indonesia. The Special Region of Yogyakarta, located on the island of Java, Indonesia, has a high potential for the development of renewable energy resources, especially hydropower and solar power. Many rural areas in Yogyakarta lack a supply of electricity. In this study, data on the potential for hydropower and solar power in rural regions of Yogyakarta are processed to determine the best capacity of hydroelectric and solar power plants. The extended particle swarm optimization (PSO) technique has been used to ensure optimal capacity optimization of this hybrid systems. The final result of this study is the most optimal of hydropower and solar power generation capacity based on the calculation of cost of capital, grid sales, cost of energy, and net present value.

Providing clean water for energy generation is of particular importance. Due to limited water resources, hydropower generation is facing problems in today’s world societies. Due to this issue, the purpose of this study is to investigate the optimal management of water resources and its impact on optimal hydropower generation. The innovation of this research is the use of a new version of Developed Wildebeest Herd Optimization (DWHO) to forecast hydropower generation. This proposed algorithm solves optimization problems and increases the accuracy of the results obtained for reservoir operation to generate power. The results of this study showed that the developed algorithm has the highest convergence speed and utilizes minimum time-consuming mathematical processes to reach the global solution and prevents trapping in local solutions. The results related to the estimation of power showed that the DWHO method produces about 17% more electricity than other compared algorithms. Also, the highest reliability index 89.7% and resilience index 68.1% and the lowest vulnerability index 12.8% belong to the DWHO method.

Energy consumption in Pakistan has increased considerably over the last two decades particularly due to industrialization, urbanization, and population growth. To keep pace with the economic growth, the growing energy demands have been fulfilled at the cost of switching from abundant, cheap, and environmentally friendly domestic hydropower to expensive, imported, and higher GHG emitting petroleum products, thus leaving Pakistan at the mercy of global oil crises and environmental degradations. While employing the trans-log production framework, this study has investigated the potential inter-fuel and inter-factor substitution among energy vs. non-energy factors in calculating substitution elasticities between pairs of labour, capital, petroleum, coal, natural gas, and hydroelectricity in order to design policy for Pakistan on how to ensure secure energy and environmental protection. Using the time-series data covering the period 1980–2017, the ridge regression technique was adopted to calculate parameter estimates. The findings show that labour-energy and capital-energy are substitutes, thus signifying the need for greater focus on technological progress and skilled employment creation to save energy and mitigate CO2 emissions. The gradual removal of energy subsidies is suggested to discourage inefficient energy use and stimulate capital-intensive production approaches. The findings also advocate the significance of a diversified energy-mix consisted of hydroelectricity and natural gas.

There is a common misconception that at least 95% of Egypt’s potential hydropower has already been used, which does not reflect reality. Currently, only five hydropower plants operate along the river Nile, from Aswan high dam to Assiut barrage. The total installed capacity is around 2840 MW. However, Egypt has many main canals and Rayahat and an irrigation network system, including barrages, head regulators, and navigation locks, which enable 120 MW of clean electricity (equivalent to 4 times of Assiut power station generation) if used to generate electricity. This paper aims to assess mini and micro hydropower’s potential in Egypt for the main grid areas. Eight sites have been selected and ranked as an application sample in this work based on their hydraulic data availability. The rank of the most suitable energy generation sites is determined with spatial maps’ aid based on the flow duration curves, capacity factor, and multi-criteria analysis. The decision matrix developed to rank the selected locations, and the turbine efficiency curve is proposed in terms of the available flow to decide the suitable turbines. Also, the spatial maps give a clear vision to decision-makers of the possibility of exploiting different resources and the priority of implementation. The results obtained show a promising prospect of mini and micro hydropower in Egypt. The annual energy from the eight studied sites is estimated by 200 GWh according to the daily hydraulic data of the year 2017. Damietta barrage takes priority as the weight value of criteria is the highest value by 2.85, and its annual energy is estimated by 78.5 GWh. The eight sites are more suitable for peak load plants, but Damietta and Zefta are appropriate by less priority for baseload plants.

Globally, demand for electricity has seen a steady increase, with nations striving to meet the demand. However, Nigeria is abysmally struggling to meet the increasing demand with the meagre per capita electricity consumption of 151 kWh, which is lower than the average of per capita electricity in Africa. Presently, the grid-tied electricity installed capacity in Nigeria, estimated at 13,435 MW is primarily generated by fossil and hydro-power plants at approximate distribution of 82.3% and 17.7%, respectively. This work presents single capsule that shows a holistic narrative of the energy access sector in view of energy penetration, sustainability, technology advancement and energy policy evolution. From available records, renewable energy sources in Nigeria are equitably distributed throughout the country, unlike the fossil reserves that are mostly concentrated in the south-south geopolitical zone. Also, there are huge potentials buried within untapped renewable energy in the country, namely wind, small-scale hydropower, geothermal, tidal and biomass energy. Furthermore, cutting edge power generation technologies that incorporate fuel cell, gas-, steam-, and low grade-turbine with carbon capture and fired by dual fuel of natural gas and biomass is promising for both energy access and climate action. The Federal Government of Nigeria's friendly energy policies, coupled with political will to excite implementation are panacea to significantly drive energy access for sustainable socio-economic development.

This paper provides a comprehensive yet concise overview of the potential, deployment, outlook, and barriers to renewable energy including small-scale hydropower, solar, wind, geothermal and bioenergy for the five Central Asian countries of Kazakhstan, Kyrgyzstan, Tajikistan, Turkmenistan and Uzbekistan. Small-scale hydropower potential estimates range from 275 MW to 30,000 MW, solar PV from 195,000 MW to 3,760,000 MW, wind from 1500 MW to 354,000 MW, geothermal from 2 MW to 54,000 MW, and bioenergy from 200 MW to 800 MW. However, deployment is minuscule: 5–225 MW in small-scale hydropower across five countries, whereas only Kazakhstan deployed large-scale solar PV (>800 MW) and wind (>300 MW). Though there are strategies and programs to increase deployment, with Kazakhstan in the lead, other countries lag behind in their efforts. A number of barriers hinder the development of renewable energy in the region, including issues with regulatory framework, infrastructure, finances, expertise, awareness and support, and data and information. Because these obstacles are interrelated, a cross-sector and integrated approach is necessary to overcome them. Renewable energy can help Central Asian countries satisfy a growing energy demand and avoid the negative environmental impacts of using fossil fuels.

This article explores the transition to renewable energy for all purposes in developing countries. Ethiopia is chosen as a case study and is an exemplary of developing countries with comparable climatic and socioeconomic conditions. The techno-economic analysis of the transition is performed with the LUT Energy System Transition model, while the socio-economic aspects are examined in terms of greenhouse gas emissions reduction, improved energy services and job creation. Six scenarios were developed, which examine various policy constraints, such as greenhouse gas emission cost. The Best Policy Scenarios cost less than the Current Policy Scenarios and generate more job. The results of this research show that it is least costing, least greenhouse gas emitting and most job-rich to gradually transition Ethiopia's energy system into one that is dominated by solar PV, complemented by wind energy and hydropower. The modelling outcome reveals that it is not only technically and economically possible to defossilise the Ethiopian energy system, but it is the least cost option with greatest societal welfare. This is a first of its kind study for the Ethiopian energy system from a long-term perspective. Publishers version

In recent decades global warming has turned into an international concern. Anthropogenic Greenhouse gases (GHG) are produced through burning fossil fuel leading to an increase in the global warming effect; thus, GHG reduction contributes to mitigating climate change. Utilizing renewable energies, increasing efficiency of and capacity factor (CF) of existing power plants, and recycling waste energy in various industries are convenient solutions to improve the energy systems performance to reduce fossil fuel consumption, leading to GHG emission. So, there is a substantial need for planning and evaluating the energy systems in which various technologies are used, technically and economically. Theis study's main objectives are utilizing the capacity of renewable energies such as biomass, wind, solar, hydropower, and enhancement of CF and efficiency of the power plants in the Mazandaran region in the south of the Caspian Sea. The energy system considered for the region is modeled and analyzed by six scenarios in this paper. The results indicated that the share of renewable energies in electricity production could be increased from 5.4% to 47.7%. The results of cost analysis show that by applying the sixth scenario, which is integrated policies of increasing RER share and improvement of efficiency and capacity factor. The trends of total annual cost, CO2 emission, and fossil fuel consumption are reduced compared to the business as usual (BAU) scenario. The average cost saved by this scenario is about 220 MUSD/year. The average amount of fossil fuels and CO2 emission save are 11 TWh/year and 2.438 Mt/year between 2020 and 2030, respectively.

Ugandan rivers are being tapped as a resource for the generation of hydropower in addition to other uses. Studies on the reliability of these hydropower plants due to climate and land-use/land cover changes on the hydrology of these rivers are scanty. Therefore, this study aimed to model the impact of the changing climate and land-use/cover on hydropower reliability to aid proper planning and management. The hydropower reliability of Muzizi River catchment was determined from its past (1998–2010) and midcentury (2041–2060) discharge at 30 and 95% exceedance probability under Representative Concentration Pathways (RCPs) of 4.5 and 8.5, respectively. The past and projected hydropower were compared to determine how future climate and land-use changes will impact the discharge and hydropower reliability of Muzizi River catchment. Six LULC scenarios (deforestation, 31–20%; grassland, 19–3%; cropland, 50–77%; water bodies, 0.02–0.01%; settlement, 0.23–0.37%, and Barren land 0.055–0.046% between 2014 and 2060) and three downscaled Regional Climate Model (REMO and RCA4 for precipitation and RACMO22T for temperature from a pool of four CORDEX (Coordinated Regional Climate Downscaling Experiment) Africa RCMs) were examined. A calibrated SWAT simulation model was applied for the midcentury (2041–2060) period, and a potential change in hydropower energy in reference to mean daily flow (designflow ≥ 30% exceedance probability), firm flow (flow ≥ 95% exceedance probability), and mean annual flow was evaluated under the condition of altered runoff under RCP4.5 and RCP8.5 climate change scenarios for an average of REMO and RCA4 RCM. The future land use (2060) was projected using the MOLUSCE (Module for Land Use Change Evaluation) plugin in QGIS using CA-ANN. Three scenarios have been described in this study, including LULC change, climate change, and combined (climate and LULC change). The results suggest that there will be a significant increase in annual hydropower generation capacity (from 386.27 and 488.1 GWh to 867.82 and 862.53 GWh under RCP4.5 and RCP8.5, respectively) for the combined future effect of climate and land-use/cover changes. Energy utilities need to put in place mechanisms to effectively manage, operate, and maintain the hydropower plant amidst climate and land-use change impacts, to ensure reliability at all times. HIGHLIGHTS Innovative approaches for hydrological modeling in data-scarce scenarios.; The possibility to utilize bias-corrected reanalysis and historical discharge data to build a climate model in data-scarce scenarios.; Sheds light on the potential risks of land-use and climate change on hydropower reliability in data scarcity areas.; Informs the need to implement prudent catchment management practices and develop policies.

Energy losses in the region between the runner and outlet section of a conventional hydraulic turbine have been the subject of investigation for a long time. In this paper as well, elbow draft tube losses are determined for the relevant wide range on-cam operating modes of the Kaplan turbine using a contemporary approach. The research considers the impact of swirl flow parameters, defined for the referent inlet of the draft tube, on the hydraulic losses. According to the methodology and obtained numerical results, a new formula for the calculation of draft tube losses is proposed. In the process of a hydropower plant refurbishment, the presented approach may enable more efficient and economically justified consideration of the performance improvement of the entire double regulated hydraulic turbine, especially in the case of keeping the existing elbow draft tube.

This paper presents an economical-technical-environmental dispatch (ETED) model for an adapted IEEE 30-bus system incorporated with thermal and a mix of renewable energy sources (RESs). Total fuel costs, active power losses, and emissions level minimization is the main aim. Different equality and inequality limits involving prohibited operating zones (POZs) are considered as system restrictions. Metaheuristic optimization techniques – moth-flame optimization, salp swarm algorithm, improved grey wolf optimizer, and multi-verse optimizer – are employed to find the best solution for the generation cost, losses, and emissions. Various scenarios are examined to approve the ability of the formulated optimization model in solving the problem. A weighted sum strategy using the analytic hierarchy process (AHP) is used to convert the multi-objective problem into a normalized single-objective one. The AHP-ETED model presented in this work can significantly minimize fuel costs to 902.4951 $/h, lower emission levels as 0.09785 t/h, and achieve a lower power loss of 2.4110 MW. The results attained validate that the IGWO outperforms the other considered algorithms in finding the best solution to the ETED problem.

Wind power generation faces intermittency challenges, typically requiring reserve power sources to maintain reliability of the electricity grid. This study proposes that hydropower turbines installed at low-head dams can provide reserve power generation to support wind power, avoiding the externalities associated with fossil-fuel plants and conventional hydropower. Low-head dams in the United States are used for flood control, securing municipal water supplies, and providing reservoir pools for recreation. As a case study, we estimated hydropower potential at 12 low-head dams along a 150-km reach of the Fox River (Northeastern Illinois, USA) using a calibrated river flow model. We analyzed the model's output to assess power generation capacity and reliability as a source of baseload power and as a component in a coupled wind-hydropower system. The modeled system performed reliably over a five-year time period despite significant long-term fluctuations in streamflow, offsetting the short-term variability of wind power. However, combining the low-head hydropower system with wind power limited the output of the system to the minimum generated by the low-head hydropower. The low-head hydropower system's small capacity and high break-even price suggest that it is better suited for local applications rather than grid-scale operations, especially if permitting regulations are considered.

Small-scale hydropower generation can satisfy the needs of communities located near natural sources of flowing water. The operating conditions of a Michell–Banki Turbine (MBT) are relatively easier to meet than those of other types of turbine, making it useful in places where other devices are not suitable. Moreover, MBT efficiency is almost invariable with respect to flow rate conditions. Nevertheless, such efficiency commonly ranges between 70% and 85%, which is lower than that of other water turbines like Turgo, Pelton, or Francis turbine. The objective of this work is to determine the maximum theoretical efficiency of an MBT and its associated geometrical parameters by implementing Particle Swarm Optimization. The results show a higher effectiveness of the mathematical formulation compared with other cases from literature and show the performance of the optimization method proposed in this study in terms of solution and processing time. Finally, a maximum MBT efficiency of 93.3% was achieved

This study develops a new national-scale bottom-up energy system optimization model called Kenya-TIMES. The model evaluates the implication of greenhouse gas emission's reduction on the techno-economic and environmental evolution of Kenya's power system under three government-projected electricity demand levels, which covers the 2020–2045 period. To assess the implications of greenhouse gas emission reduction measures, a business as usual and a carbon emission cap scenarios were developed. The model shows that energy security can be achieved under the two scenarios, and for all the three demand levels. The generation mix suggested by the model is dominated by renewable sources under the carbon emission cap scenario compared to the business as usual scenario. The higher share of renewable technologies under the carbon emission cap scenario results in lower emission but increased electricity cost. Consequently, to meet its emission reduction targets, the Kenyan government need to enact and implement policies that will enhance deployment of renewable energy technologies. The findings indicate that the Kenyan government should prioritize developing geothermal and hydropower resources in the short- to medium-term, which can provide affordable and secure energy while limiting GHG emissions.

Latin America has the largest share of renewable energy for power generation in the world, but has historically been dependent on hydropower, and is vulnerable to long-term phenomena like the El Nino-Southern Oscillation (ENSO). The region is currently experiencing a steady increase in gas-based power generation along with a rapid growth in non-hydro renewables, mainly aimed at improving reliability. But exploiting complementarities between hydropower and other renewables could offer additional benefits. This paper investigates to what extent improved deployment of wind turbines and solar photovoltaic cells (PV), aimed at complementing existing hydropower, could mitigate the impacts of ENSO in Latin America. We use a meteorological reanalysis dataset to model the variations in wind-, solar- and hydropower throughout the entire 20th century and their association with different ENSO phases in the same period. A statistical algorithm is then used to identify locations at national and regional levels offering the maximal level of complementarity. The results show that adding 136 GW of wind- and solar-power with high-complementarity has the potential to cost-effectively compensate the fluctuations of hydropower and reduce the variability of renewable power not only during drought ENSO phases but also outside ENSO events. Benefits include: (i) an increase of up to 5-fold the minimum threshold of renewable power available every month, (ii) a reduction of up to 65% in the variability of renewable power generation, and (iii) reaching a levelized cost of electricity (LCOE) of 0.09–0.23 $/kWh, which is comparable to that of new gas plants.

Hydrokinetic energy conversion refers to the conversion of kinetic energy in moving water to electricity. It offers an alternative to conventional hydropower, with benefits of modularity and scalability, in addition to being environmentally and socially less impactful. This study aims to determine the theoretical global riverine hydrokinetic resource. We use a 35 year modelled daily discharge data set and vectorised representation of rivers, with near-global coverage and suitable spatiotemporal resolution, to determine the mean annual energy yield of 2.94 million river reaches. The mean global resource (excluding Greenland) is estimated to be 58 400 ± 109 TWh yr−1 (6.660 ± 0.012 TW). Consideration of global spatial distribution, by river reach, illustrates regional variation and shows a tendency for potential to be concentrated along major rivers and in areas of significant elevation change. China, Russia and Brazil are found to be the countries with the greatest potential. After normalisation by total river length, Bhutan, Nepal and Tajikistan also show great potential. Hydrokinetic energy conversion can benefit isolated communities currently without access to electricity. We consider how the specific advantages of this particular technology have the potential to be combined with and complement other established forms of renewable energy technology, providing the means to support the reduction of energy poverty.

A new model, REVUB-Light, an extended modelling approach for the recently developed “Renewable Energy Variability Upscaling and Balancing” (REVUB) model, is highlighted in this study for its relatively simple and effective parameterization for power balance optimization simulations, considering high Intermittent Renewable Energy integration. We demonstrate the effective use of the REVUB-Light model, considering a study for Suriname. The results for different cases are compared to those of the REVUB model, previously used for similar assessments for Suriname. Following distinct optimization procedures, our results confirm the REVUB model findings, i.e., a highly complementary role for wind energy, with up to 20–30% feed-in potential, based on the assumed (currently most probable) hydrological and wind regimes. The REVUB-Light model is validated based on actual operational data, enabling assessments of the potential real world response, and the benefits of flexible (optimized) operational regimes, underlining its potential for renewable energy modelling. It is further shown that Suriname has potential for (near) 100% renewable energy supply, for the mid-term horizon (2030), if additional hydropower potential is developed in combination with hydro-supported wind energy. Overall, the parsimonious approach of REVUB-Light proves to be a reliable modelling tool, and facilitates general usability by “non-experts” such as policymakers.

Winter construction in seasonally frozen soil areas is inevitable. The variation of ambient temperature causes the freeze-thaw of the filling soils and its impact is significant, and whether the countermeasures can be effectively established and adopted is particularly important for the management and control of the construction quality of the project. This paper conducts systematic research based on the winter construction process of the dam core wall of the Lianghekou Hydropower Station, which is the third highest earth-core rockfill dam in the world under construction. The results show that for the construction site in the seasonally frozen soil area, there is a development process of the short-term frozen soils for the filling soils under the environment with low temperature in winter. The soil underwent a high-frequency freeze-thaw process wherein it was frozen at night and completely thawed during the day. During the freezing process, a large number of thin-layered segregated ice developed inside the soil to form a thin-layered or integral cryostructure, which will have an adverse effect on the engineering properties and the quality of the filling soils. And, the field tests demonstrate that the filling compaction degree of the frozen soils is difficult to meet the designed requirements. In order to effectively cope with the adverse effect of the freeze-thaw on the construction quality during the construction process, based on the analysis of the freeze-thaw characteristics of soils and its influence, and the energy exchange process of soils on-site, the principles and methods for establishing the freeze prevention system during the winter construction process are established, and a comprehensive monitoring system suitable for on-site is established in this paper. This research will provide an important reference for the scientific management and efficiency improvement of the winter construction process of the dams in cold regions.

Positive displacement hydraulic turbine (PDT) is a new class of turbine, capable of effectively generating micro and Pico hydro power for low specific speed applications. This type of turbine is not very popular and hence, it is interesting to research on it. With the rising concerns of environmental pollution, climate change and global warming, emphasis is laid to harness power from renewable energy sources. Micro and Pico hydro turbines are actively researched to generate clean power in addition to the existing conventional turbines. PDT was designed and developed to replace the pressure differential control valves in the hot water supply system and utilize the surplus differential head to generate power and make the system energy efficient. In the present work, experimental studies were conducted on the developed PDT at the designed rotational speed with water at 15, 50 and 110 °C and various differential heads ranging from low to high. The performance data showed the effect of fluid properties on the performance of the PDT due to the change in the temperature of the working fluid. Also, empirical co-relation was developed based on dependent variables using Buckingham π-theorem to predict the flowrate through the PDT at various heads and temperatures. This could help engineers, in future, for designing a new turbine for harnessing micro and Pico hydropower for any application.

Million miles of gravity-fed drinking water and sewage pipelines around the world, especially in rural and urban areas in mountain ranges, have introduced a new renewable energy sources (RES), i.e., in-pipe hydropower systems (IHS). Output power of this technology, similar to other types of RES, suffers from intermittency, while it is still more predictable in comparison to other technologies of RESs. Besides, energy storage systems (ESS) are introduced as a pivotal technology for dealing with the intermittent and non-dispatchable characteristics of IHS through spatio-temporal arbitrage. This paper aims to develop a stochastic mixed-integer linear programming (MILP) formulation that simultaneously determines the optimal location and size of ESS and IHS in a microgrid (MG) considering the correlation between prevailing uncertainties. In this regard, the proposed optimization problem minimizes the expected social cost of MG considering the AC power flow equations and operation constraints. Finally, the efficiency and applicability of the proposed model are illustrated using numerical simulations on the IEEE 33-bus distribution test system.

This paper enables a screening of existing irrigation dams in order to assess and rank potential sites for small hydropower development by using a Geographic Information System (GIS)-fuzzy logic multi-criteria scoring technique. The following criteria are evaluated: dam characteristics (reservoir normal level, reservoir capacity, dam purpose, dam ageing), and grid connection spatial characteristics. The proposed method estimates the suitability degree of each criterion separately and then aggregates them into a Site Suitability Index (SSI). Existing irrigation dams in Turkey are assessed in order to be utilized for hydropower development. The overall score of each candidate site is obtained and, their performance is compared for different strategies. One of the most suitable dams, Karadere, was chosen as a case study. By using the daily continuous monitored data, we showed that flow and head is highly variable during the irrigation season. Accordingly, we evaluated an innovative compact medium-head hydro turbine that can capture those fluctuations with its operational flexibility and minimal civil works. Moreover, an optimal path methodology was applied to find the best grid connection route from the dam to its nearest substation considering the site land use characteristics in order to minimize land expropriation.

Optimizing the hydro unit commitment (HUC) has the potential to increase water use efficiency. However, the large number of variables, along with some nonlinear and non-concave constraints, present a huge challenge to the efficient solution of the HUC problem. For hydropower stations including multiple power plants that have different hydraulic heads, the problem is even more difficult. In this paper, we address this complex HUC problem using a two-layer nested optimization method. First, the total load demand is allocated to each power plant using a novel distribution rate. Thus, in the outer layer, a cuckoo search algorithm optimizes the distribution rate and each unit’s on/off status, while in the inner layer, the load demand of each plant is allocated to online units through dynamic programming. China’s Gezhouba Hydropower Station is selected for a case study. It is shown that: (1) the optimized water consumption is, on average, 1.71% lower than that of actual operations; (2) the optimized status of units vary smoothly with fewer startup/shutdown events; and (3) the optimization performance in non-flood seasons is better than that in flood seasons. These findings verify that the two-layer nested optimization method is an effective means of solving HUC problems for hydropower stations including multiple hydro plants with different hydraulic heads.

In this paper, independent optimization operation strategy and global optimization operation strategy for cascaded hydropower plants are studied in aim to maximize total power energy of all the cascaded hydropower plants. In the first strategy, upstream hydropower plants are optimally operated first and then obtained results are used to operate downstream hydropower plants. On the contrary, all hydropower plants are operated simultaneously in the second strategy. The two strategies are accomplished by using an improved cuckoo search algorithm (ICSA) together with particle swarm optimization (PSO), cuckoo search algorithm (CSA), Salp Swarm Algorithm (SSA), sunflower optimization algorithm (SFO), equilibrium optimizer (EO) and marine predator algorithm (MPA). Result comparisons can lead to the evaluation that the first strategy can bring more benefits for upstream plants whereas the second strategy is more suitable for downstream hydroelectric plants. For the purpose of maximizing total energy of all plants, the second strategy is more effective than the first strategy. Compared to PSO, CSA, SSA, SFO, EO and MPA, ICSA method finds higher energy with a highly faster speed. Thus, the paper suggests the second strategy should be executed for hydroelectric plants in cascaded reservoir systems and ICSA can be a favorable method for implementing the recommended optimization operation strategy.

Swedish government’s target is to have 100% renewable electricity production by 2040. Currently, hydropower contributes the majority of renewable electricity generation of the country. The wind power capacity has increased significantly in the past decade. In this paper, practical data is used to study the possibility of reaching the 100% renewable electricity generation goal by replacing existing thermal generations with wind power generations. It is found that the Swedish electricity generation system can reach 100% renewable by tripling the existing wind power capacity combined with the existing hydropower in the country. Based on current growth rate of wind power installation, the goal could be reached within 20 years. Hourly simulation shows that 100% renewable energy generation system composed by wind power and hydropower satisfy hourly operation requirements.

Water resources infrastructure is critical for energy and food security; however, the development of large-scale infrastructure, such as hydropower dams, may significantly alter downstream flows, potentially leading to water resources management conflicts and disputes. Mutually agreed upon water sharing policies for the operation of existing or new reservoirs is one of the most effective strategies for mitigating conflict, yet this is a complex task involving the estimation of available water, identification of users and demands, procedures for water sharing, etc. A water sharing policy framework that incorporates reservoir operating rules optimization based on conflicting uses and natural hydrologic variability, specifically tailored to drought conditions, is proposed. First, the trade-off between downstream and upstream water availability utilizing multi-objective optimization of reservoir operating rules is established. Next, reservoir operation with the candidate (optimal) rules is simulated, followed by their performance evaluations, and the rule selections for balancing water uses. Subsequently, a relationship between the reservoir operations simulated from the selected rules and drought-specific conditions is built to derive water sharing policies. Finally, the reservoir operating rules are re-optimized to evaluate the effectiveness of the drought-specific water sharing policies. With a case study of the Grand Ethiopian Renaissance Dam (GERD) on the Blue Nile river, it is demonstrated that the derived water sharing policy can balance GERD power generation and downstream releases, especially in dry conditions, effectively sharing the hydrologic risk in inflow variability among riparian countries. The proposed framework offers a robust approach to inform water sharing policies for sustainable management of water resources.

Increasing capacity of intermittent generation brings new challenges to balance demand and supply in power systems. With retirement of conventional fossil generation, the role of energy storage is increasing. One of the most competitive storage technologies is pumped storage hydropower plant (PSHP). Usually, such PSHPs are constructed as green field solutions, but in some cases conversion of a hydropower plant into a pump storage hydropower plant by building a pump station is possible. To evaluate the feasibility of such modernisation it is necessary to estimate the benefits of PSHP operation. The simplified model was developed for simulation of charging and discharging cycles of PSHP in Latvian power system and trading electricity in Nord Pool power exchange. The nature of this task is stochastic as the price volatility has a trend to increase with expansion of wind and solar power plant capacity. Results of PSHP operation simulation were then used in the economic model to evaluate the feasibility of the proposed conversion.

Mini hydropower plants can be considered as good instruments for power generation at a low cost with high efficiency. This study is undertaken to help address the electricity shortage that Iraq has faced for many decades. This study covers the design and analysis of two alternatives, which are hydropower and thermal power plants, through a mathematical financial feasibility approach. The study area is Hindiya barrage on the Euphrates River. A complete design of the powerhouse plant is presented. In the thermal power plant, two proposals were tested, one at a cost of 60 US$ per barrel of oil and the other at 30 US$. Most of the financial parameters are considered. The hydropower plant generation is more feasible than the thermal power generation. This result provides the impression of a low payback period in the power production from the established barrages on the Euphrates and Tigris rivers.

Renewable Energy Resources (RERs) are becoming increasingly significant for energy generation and will have vital for the future of humans, earth, and other living things. Due to the negative environmental impacts of fossil fuels, the authorities have taken RERs into account further. As a result, the present study extended a novel model using the Level Based Weight Assessment (LBWA) model based on in Interval Rough Number (IRN) extension of the Combinative Distance-Based Assessment (CODAS) method to cope with uncertain domain-based RER selection. A survey method using literature review and interview has been conducted to find and select appropriate perspectives and criteria; in this regard, the selected criteria were classified based on four groups, including socio-political, environmental, economic, and technical. Five sources of renewable energy, including solar energy, biomass energy, wind energy, hydropower energy, and geothermal energy, are evaluated in Turkey. The results of the extended IRN CODAS approach demonstrated that hydropower energy had the first rank among other sources, followed by solar energy, geothermal energy, biomass energy, and wind energy. In the application of the suggested model, the most suitable RER alternative is determined for Turkey. The results of this study showed the effectiveness, efficiency, and capability of the proposed methodology in the assessment of RERs.

This paper investigates the multi-frequency dynamic performance of hydropower plant (HPP) under coupling effect of power grid and turbine regulating system with surge tank. Firstly, a model of grid-connected HPP with surge tank is established and verified. Dynamic performance of grid-connected HPP with surge tank is evaluated by analyzing stability and dynamic response. Then, the number of frequencies of dynamic response is identified. The generation mechanism of multi-frequency dynamic response is revealed. Finally, the influence of system parameters on multi-frequency dynamic performance is studied. Guidance for actual applications of the obtained law and mechanism is proposed. The results indicate that the dynamic response of grid-connected HPP with surge tank has a feature of multi-frequency. There are three frequencies for the dynamic response corresponding to three subwaves i.e. mass oscillation, water hammer oscillation and grid disturbance oscillation. Low-frequency mass oscillation is induced by water flow and level oscillation in subsystem of headrace tunnel and surge tank. Medium-frequency water hammer oscillation is induced by natural hydraulic oscillation in subsystem of penstock, turbine, governor and generator. High-frequency grid disturbance oscillation is induced by power grid. The coupling effect among penstock, turbine unit and power grid on water hammer oscillation is strong.

Hydropower plants are one of the most convenient option for power generation, as they generate energy exploiting a renewable source, they have relatively low operating and maintenance costs, and they may be used to provide ancillary services, exploiting the large reservoirs of available water. The recent advances in Information and Communication Technologies (ICT) and in machine learning methodologies are seen as fundamental enablers to upgrade and modernize the current operation of most hydropower plants, in terms of condition monitoring, early diagnostics and eventually predictive maintenance. While very few works, or running technologies, have been documented so far for the hydro case, in this paper we propose a novel Key Performance Indicator (KPI) that we have recently developed and tested on operating hydropower plants. In particular, we show that after more than one year of operation it has been able to identify several faults, and to support the operation and maintenance tasks of plant operators. Also, we show that the proposed KPI outperforms conventional multivariable process control charts, like the Hotelling t 2 index.

Acquiring sustainable water resources for water-based development of countries is the experts concern in this field, who seek to follow the clean development mechanism (CDM) regulations and overcome water crisis through integrated water resources management (IWRM). The Great Karun River basin is one of the major basins in the Middle East. This basin, containing six of the largest reservoir dams with a cumulative power plant capacity of more than 10,500 MW generates about 93% of hydropower of Iran. The water balance of the aquifer in the study area was simulated using MODFLOW model while water resources and surface water reserves were simulated by the water evaluation and planning (WEAP) model. A separate simulation was performed with each of two models and the results of two models were coupled using a link file. The multi-objective function optimization process including the maximized supply of demands and hydropower and the minimized aquifer drawdown was completed using non-dominated sorting genetic algorithm (NSGA-II). All effective system components, such as inter-basin water transfer, integrated use of water resources, variation of irrigation network efficiencies, and the effect of water shortage were studied and analyzed under the targeted scenarios. Finally, the best scenario, which was capable to supply the future needs until time horizon of 2040 was planned for the basin considering minimization of aquifer drawdown and optimal generation of hydropower resulting in a maximum decrease in emission of greenhouse gases.

Fossil fuels are energy sources that supply a large part of the world's energy generation. However, they produce greenhouse gases such as carbon dioxide (CO2), nitrogen oxide (NOx) and particulates that increase global warming. For this reason, other forms of renewable energy such as hydropower have begun to be implemented through turbomachinery such as Pelton turbines, which significantly reduce these emissions since they are highly efficient turbines based on the use of natural resources (water). Pelton turbines are based mainly on three components for their operation, which are the Pelton injector, the bucket and the wheel. The injector is an important component in the energy transformation of Pelton turbines. Although to analyze its behavior, it is possible to use fluid dynamics (CFD) software to predict the trajectory of the flow through a solid or free surface. The objective of this work is to analyze by means of computational fluid dynamics (CFD) the incidence of the length and the needle tip angle of a Pelton turbine injector on the generated power. For this, an ANSYS 2020R2 computational fluid analysis software was used to study how the variation of the injector needle tip angle influences through the volume of fluid (VOF) method, starting from the generation of a commercial model with a tip angle of 60° and two (2) geometries of 55° and 75° respectively. Numerical results show a better performance for the 75° angle of 96 % and lower for the 55° and 60° with 94.1 % and 95.5 % respectively, whereby steeper angles achieve higher performances. In summary, the present study pretends to increase the power generation, in the face of phenomena occurred in the energy transfer. Although the performance of the injector in each angle configuration must be tested in practice

Several activities regarding water resources management are dependent on accurate monthly streamflow forecasting, such as flood control, reservoir operation, water supply planning, hydropower generation, energy matrix planning, among others. Most of the literature is focused on propose, compare, and evaluate the forecasting models. However, the decision on forecasting approaches plays a significant role in such models’ performance. In this paper, we are focused on investigating and confront the following forecasting approaches: i) use of a single model for the whole series (annual approach) versus using 12 models, each one responsible for predicting each month (monthly approach); ii) for multistep forecasting, the use of direct and recursive methods. The forecasting models addressed are the linear Autoregressive (AR) and Periodic Autoregressive (PAR) models, from the Box & Jenkins family, and the Extreme Learning Machines (ELM), an artificial neural network architecture. The computational analysis involves 20 time series associated with hydroelectric plants indicated that the monthly approach with the direct multistep method achieved the best overall performances, except for the cases in which the coefficient of variation is higher than two. In this case, the recursive approach stood out. Also, the ELM overcame the linear models in most cases.

Climate change projects an increase in extreme weather events in the coming decades, which could significantly affect Brazil's water and energy security. Thus, this study sought to analyze possible impacts of climate change on the projections of naturalized streamflows and Affluent Natural Energy (ANE) for the Brazilian hydropower sector utilizing five models of the Coupled Model Intercomparison Projects version 6 (CMIP6), based on SSP-4.5 and SSP-8.5 scenarios for the 21st century. Naturalized streamflows for the 24 stations representing the National Interconnected System (NIS) were estimated through the concentrated hydrological model SMAP (Soil Moisture Accounting Procedure), while the streamflows for the other stations that comprise the NIS were obtained by linear regression. The streamflows, as well as the productivity of the reservoirs, were used to calculate the ANE. The results showed that most of the models project possible reductions in annual naturalized streamflows and ANE for the three periods analyzed and for the North, Northeast, and Southeast/Midwest sectors of Brazil. Meanwhile, the Northern and Southern sectors, for the period 2080–2099, most of the models indicated an increase of annual, precipitation, naturalized streamflows and ANE. HIGHLIGHTS Most of the CMIP6 models showed that the NIS reservoirs are sensitive to increasing greenhouse gas emissions.; The medians of the standardized anomalies of annual naturalized streamflows and ANE indicated an increase for the South and North sectors of the country.; In the Northeast subsystem, most of the CMIP6 models indicated a reduction in naturalized streamflows and ANE.

Over the past decades, the reservoirs operation plays an increasingly important role in coping with the serious water, food and energy crisis. However, the curse of dimensionality poses huge challenges for operators because the computation cost often grows exponentially with the expansion of hydropower system. With strong search performance and high execution efficiency, metaheuristic search algorithms become the research hotspot in the reservoir operation field. Here, cooperation search algorithm (CSA) inspired by team cooperation behaviors in modern enterprise is introduced for power generation operation of cascade hydropower reservoirs. In CSA, the team communication operator is designed to determine promising search areas, and then the reflective learning operator is adopted to enhance the local search, while the internal competition operator is used to retain the elite individuals. The feasibility of the CSA method in numerical optimization problems is fully proved by the simulation results of several test functions. Then, the CSA method is used to solve the power generation operation of cascade hydropower reservoirs. The results show that the CSA method outperforms several traditional methods in both convergence rate and search precision. Thus, an effective tool with strong reliability and robustness is provided for the complex reservoir operation problem.

Uma Oya watershed that feeds Rantambe reservoir in Sri Lanka is severely affected by soil erosion due to the inappropriate land-use practices. This study assesses the impact of soil erosion on reservoir sedimentation and the economic losses by adopting Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) Sediment Retention model and investigates mechanisms available for minimising the impacts. Data sources included digital map data from GIS, household questionnaire survey and field level data. Three land-use interventions were modelled to determine changes in sedimentation against the current land use. Three interventions available for the power generation facility (PGF) to mitigate loss of hydropower were analysed against each land-use intervention. Mechanisms available for implementing a payment for ecosystem service were analysed next. The current average soil erosion rate in the watershed is 10.7 tons/ha/year. Under the best intervention strategy available for the PGF, this translates into a total cost of LKR 601.7 million in present value (PV) terms for the remaining life of the reservoir with a 10% discount rate. Soil and water conservation (SWC) intervention for the watershed reduces the soil erosion rate by 23%, which results in total savings of LKR 88.7 million (PV). Implementing SWC intervention by farmers requires that they are paid the full cost. Since payment from the PGF is not adequate for this, an additional payment from the fertiliser importing authority of the country is proposed. The study suggests further full scale multi-dimensional analysis that combine multitude of agencies along with temporal dimensions to arrive at the best solution.

Today, due to increasing environmental considerations and efforts to reduce fossil fuel consumption, the need to develop small hydropower plants has become apparent. One way to develop hydropower i...

To enable power supply in rural areas and to exploit clean energy, fully renewable power systems consisting of cascaded run-of-the-river hydropower and volatile energies such as pv and wind are built around the world. In islanded operation mode, the primary and secondary frequency control, i.e., hydro governors and automatic generation control (AGC), are responsible for the frequency stability. However, due to limited water storage capacity of run-of-the-river hydropower and river dynamics constraints, without coordination between the cascaded plants, the traditional AGC with fixed participation factors cannot fully exploit the adjustability of cascaded hydropower. When imbalances between the volatile energy and load occur, load shedding can be inevitable. To address this issue, this paper proposes a coordinated tertiary control approach by jointly considering power system dynamics and the river dynamics that couples the cascaded hydropower plants. The timescales of the power system and river dynamics are very different. To unify the multi-timescale dynamics to establish a model predictive controller that coordinates the cascaded plants, the relation between AGC parameters and turbine discharge over a time interval is approximated by a data-based second-order polynomial surrogate model. The cascaded plants are coordinated by optimising AGC participation factors in a receding-horizon manner, and load shedding is minimised. Simulation of a real-life system with real-time pv data collected on site shows the proposed method significantly reduces load loss under pv volatility., Comment: Accepted by IET Renewable Power Generation; 13 pages

Africa is characterised by a very high solar potential, with a yearly sum of solar irradiation exceeding 2000 kWh/m2. Many African countries are heavily dependent on hydropower, however, increasingly frequent droughts have been severely affecting hydropower generation in the last few decades. The installation of floating photovoltaics (FPV) in existing hydropower reservoirs, would provide solar electricity to help compensate hydropower production during dry periods and reduce evaporation losses while helping to sustainably satisfy the current and future energy needs of the fast-growing African population. This study provides a comprehensive analysis of the potential of FPV installation in Africa, by using highly accurate water surface data of the largest 146 hydropower reservoirs in the continent. In addition to the electricity production, evaporation savings and the potential extra hydroelectricity generated by these water savings are also estimated at reservoir level for four different cases and two types of floating structures. The results indicate that with a total coverage of less than 1%, the installed power capacity of existing hydropower plants can double and electricity output grow by 58%, producing an additional 46.04 TWh annually. In this case, the water savings could reach 743 million m3/year, increasing the annual hydroelectricity generation by 170.64 GWh.

Traditional hydropower generation is one of the most sustainable energy sources; however, the local environmental impact of hydroelectric dams and reservoirs is serious, and hydroelectric power requires high-cost turbines and generators. Because these installations utilize gravitational potential energy of massive volumes of falling water, this sort of hydropower generation is unsuitable for ubiquitous, small-scale energy production. Here, we report that wetting and evaporation of pure water from a tiny block of porous alumina generates electrical current in the direction of water transpiration. The current induced in microporous alumina is associated with mass transport of water accompanying ions that accumulate near the negatively charged surface of alumina pores. Without any pre-treatment or additives, once evaporation commences, a 3×3 cm2 piece of alumina can generate an open-circuit voltage as large as 0.27 V. The power generation scheme we propose here is simple, clean, and versatile, and it can be employed anywhere, as it utilizes only spontaneous capillary action of water and Coulombic interaction at the alumina-water interface, without requiring any input of heat or light.

This study aimed to apply the Markovian Model (MM) to obtain optimized operating rules for a hydropower reservoir to maximize its efficiency. In this study, a Markovian Control Model with continuous state space (MCM-CSS) is presented to analyze the climatological effects through stochastic integrals. The MCM-CSS compute the optimal policies of hydropower reservoir system over the Grijalva Hydropower System (GHS). The MCM-CSS can be described as follows: a) Historical data review, b) histograms of variables studied, c) state space analysis, d) action space analysis, e) admissible decision rule, f) expected benefit analysis. As a result, the optimal policy graphs were obtained. The result obtained in this research demonstrated the advantage of having applied a continuous space in reservoir inflow and water demand with the MMC-CSS method to avoid the uncertainness and inaccuracies in simulation results with a discrete space. Modified Svanidze’s Method (MSM) is also employed to investigate their capabilities to predict streamflow over the GHS and mean energy generated. The hydrological monthly simulations were calibrated and validated at GHS station for the period 1952–2018. The main objective of the study is to simulate the optimal policies obtained with the MMC-CSS for continuous states using MSM in GHS.