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The maintenance schedule planning of hydro plant generating units is a subject of great interest to several agents in the energy industry. A correct approach for this problem can prevent the degradation of physical assets and minimize the probability of forced shutdowns of their equipment. In addition to these factors, due particularities of the Brazilian system, the operational strategies of its agents are also affected by the maintenance schedule of the generating units. This occurs due to the Availability Factor (AFA), which is directly influenced by the hours of maintenance performed at the plant and, in case of a performance below the stipulated in the concession contracts, it can lead to financial losses or administrative sanctions applied by the regulatory agent. With this motivation in mind, the present work proposes a methodology for Generator Maintenance Scheduling (GMS) of a hydroelectric plant, developing a mathematical model to determine the ideal moment to perform maintenance, considering operational restrictions and regulatory aspects of hydroelectric plants. The optimization methodology proposed for this problem is done through mixed-integer linear programming, where the integer variables consist of the operating state and start date of maintenance of each generating unit. In the end, to validate the proposed modeling, a case study is carried out for a real large plant in the Brazilian system.

Multiobjective long-term generation scheduling (MOLTGS) plays a vital role in coordinating the contradiction between the generation and reliability of cascade hydroelectricity system (CHS). In this paper, a multiobjective quantum-behaved particle swarm optimization based on decomposition (MOQPSO/D) is presented to solve the MOLTGS problem of maximizing total hydroelectricity generation and firm hydroelectricity output. In MOQPSO/D, the improved logistic map is adopted to initialize the population in the feasible space, where various equality and inequality constraints are handled by a constraint handling method based on conversion and repair strategies. An improved Tchebycheff decomposition with a modified generator of direction vectors, a modified QPSO operator and normal cloud mutation are the key components of MOQPSO/D in addressing the nonlinearity and complexity of MOLTGS. The feasibility and effectiveness of MOQPSO/D are verified first on numerical experiments of benchmark instances and then on real engineering examples of the Three Gorges (TG) and Gezhouba (GZB) plants within three representative years. The results show that MOQPSO/D can not only perform better robustness, convergence and diversity performance than other seven competitors but also output a group of Pareto optimal schemes within a reasonable amount of time. So, this paper provides a new effective alternative to solve the MOLTGS problem of CHS when considering both generation and reliability objectives.

In Pakistan, hydroelectric power is one of the reliable sources of electricity with a capacity of 8,713 MW, which is 29% of the total energy mix. Hence, with such a vast resource capacity of hydroelectric power, its optimization and dispatch planning will have a great significance. This research work discusses the importance of hydroelectric power generation planning for both storage and run-of-river (ROR) hydropower plants, as well a; a solver-based optimization technique is proposed for the first time to resolve the intricate job of generation planning for hydroelectric power plants in MATLAB. A mathematical-optimization model is also developed, which uses a Mixed-Integer Linear-Programming (MILP) algorithm, based on the objective function of profit maximization, which considers a random varying revenue plan as model input. Three hydropower generators of different capacities and efficiencies are considered for the optimization problem. MILP based solution is proposed for both storage and ROR hydropower plants with two dispatch schedules, i.e., Normal dispatch schedule and optimum dispatch schedule. The objective functions are solved, and the profit (in dollars) from each dispatch schedule is calculated and compared. The preliminary optimization results show an increase of $22,000 and $29,130 in the profit for storage and ROR hydropower plants, respectively, which is 19% more than average income. Hence, ensuring the credibility of the proposed algorithm for maximizing the revenue ($), is aimed to facilitate and assist better planning for electric power producers.

The economic operation of hydrothermal systems is one of the most challenging problems in the area of power systems because it is a non-linear and non-convex problem. The use of heuristic optimization methods are an attractive alternative to traditional deterministic methods by offering excellent quality in their results with an implementation that is characterized by having a simple concept. This document solves the hydrothermal coordination problem considering the hydraulic coupling of hydroelectric power plants and the valve point effect in thermal power plants using genetic algorithms (GA), the novel grey wolf algorithm (GWO) and particle swarm optimization method (PSO). In addition, different Key Performance Indicators are proposed to validate the performance achieved by each heuristic technique applied to the planning of the economic dispatch of a multiple set of thermal and hydroelectric power plants for a daily scheduling horizon of 24-hour.

It is foreseen that the electrical energy produced using limited resources such as hydroelectric, natural gas, and thermal power plants may cause problems in terms of energy continuity in the long term. Therefore, with the incentives of governments, investment in renewable energy sources is increasing every year. Wind energy is one of the most important renewable energy sources. The calculation of the power to be produced in wind power plants is both difficult and requires experience. In this study, the amount of power produced in a wind turbine was estimated using machine learning-based regression algorithms (7 different algorithms) using wind speed and wind direction data. The proposed approach was evaluated on data from a wind turbine in Turkey. Among the regression algorithms evaluated according to the R2 performance metric, the best performance was achieved with the AdaBoosting algorithm.

Renewable energy is energy to produce electricity that can be obtained from natural resources that can be constantly replenished. One of the main potential sources of renewable energy in Indonesia is the mini-hydropower plant. The main objective of this paper is to present an analytical of technical and economic feasibility study of the run-off natural river mini-hydropower plant project. On the technical side, the most important element is a topographical and hydrological analysis which will affect the annual energy production. The hydrological analysis in this project are using methods of flow rate from the current meter and manning equation. On the economical side, the most important elements are financial and investment analysis. The studied site is located at Banjaran river, Ketenger village, Banyumas district, Central Java province. In this location, get flow rate is 3.15 m3/s, and the head is 68.5 m. From experimental, calculation and analysis, this mini-hydropower plant can generate power at 10 GWh per year, In terms of economic feasibility, after-tax IRR equity at 34.5%, after-tax IRR assets at 13.7%, the Payback Period for this project is 4.9 years. Respectively the development of the run-of-natural river mini-hydropower plant has an advantage, such a feed-in tariff trends continues to increase, direct sales, long time power purchase agreement duration, high net income, and no penalties. Based on all of the experimental, calculations and analysis mean that development on the run-of-natural river mini-hydropower plant is feasible to the renewable energy business.

The article describes the dynamics of the development of power supply systems in Tajikistan in the 21st century. The predominant development of hydropower is shown, based on the geographical features of the relief of the republic, which is rich in hydropower resources. The tendency of a significant expansion of the construction of small hydroelectric power plants, which are the most effective in addressing the issues of power supply in the hard-to-reach high-mountainous regions of the republic, is noted. The features of electricity consumers in rural settlements and their influence on the formation of requirements for control systems of small hydroelectric power plants are considered. At the same time, the main attention is paid to solving the issues of balancing the output voltage of hydroelectric power plants with a significant asymmetry of phase loads, which is typical for household consumers. It is shown that the simplest and most effective method for the implementation of small hydroelectric power plants, taking into account the peculiarities of their use for mountainous regions, is their complete automation with the maximum use of semiconductor power discrete voltage conversion devices. An analysis of the existing methods for balancing phase voltages is given and a description of a new method based on a discrete voltage converter is given.

The need for cheaper electricity generation rises as the price of fossil fuels is increasingly nowadays. Hydropower plant is one of the most efficient and environmentally friendly alternative power plant sources. In this research works, a prototype of small-scale hydro power plant known as micro hydro power plant (MHPP) was developed for educational and research purpose. The motivation of this work is based on there is no field laboratory could be used for students to study the concept and actively involved in electricity generation at Universiti Teknologi Malaysia (UTM) Johor Bahru campus, Malaysia. This work hopefully become the catalyst for further research regarding renewable energy source, particularly in MHPP research. The research flow for this work begins with feasibility activities to determine some potential sites for development of MHPP at UTM Johor Campus. There are 7 (seven) potential sites based on site visits and data analysis. From the data analysis, the most suitable site chosen for MPPP prototype development. The prototype was built based on the improved design. The results show that the constructed prototype is capable for generating electricity. This prototype can be used as a field laboratory and for educational and research purpose.

The expensive and limited fossil energy is the reason to develop renewable energy, which is the right solution to fix the environmental problems and support the national development of Indonesia. The Department of Electrical Engineering of USU supports the government and sees the potential sources of power around the campus, which is performed by developing a mini-hydro generator by using water as the source of power that comes from a tower on campus. The design of the mini-hydro generator that will be implemented in the Electrical Engineering department was made at the di Simulink Matlab R2018a. There is a speed control using PID control in HTG in the system during disturbances, namely the loading changes (loading variations). The PID control value used is the result of optimization using GA, and by controlling the speed in HTG, an IEEE standard frequency is obtained, which is ±1% (50 Hz).

Numerical simulation of the spatial flow of high-head Francis hydraulic turbine RO310 for two variants of the water passage (the runner with 15 blades (modification 1) and with 17 blades (modification 2)) was carried out using application program package. The selected software package is one of the most used products designed for solving the hydrodynamic problems, distributed under a free license GPL (General Purpose License). The visualization of the results of the numerical research of two modifications of the hydroturbine RO310-V100 is given. The method of calculation of hydraulic losses in the water passage of the hydraulic turbine is presented. The analysis of numerical simulation results is performed. This analysis showed that the modification of the hydraulic turbine with the runner having 15 blades is better in terms of efficiency than the modification with 17 blades. The comparison of the two modifications was performed only on the values of the hydraulic efficiency of the turbine.

In the paper the history of Dnieper Hydroelectric Station (DniproHES) is studied. The influence of the DniproHES building process on the European electricity industry is shown. The challenges faced by the chief engineer Ivan Alexandrov and construction head Aleksandr Vinter are highlighted. The unique technical practices are considered. The creation of architectural embodiment of the dam is shown.

The Democratic Republic of Congo (DRC) has various types of renewable energies. These include among others hydroelectric power, wind power, solar power and geothermal power. Numerous are the potential sites scattered across the country. What type of energy to produce and in which region of the country? What mix of energy would be economically better? Does it take enough care of the natural conditions of the country? Choices need to be made. In order to do that, elements that can help in considering these choices need to be provided. As the country has one of the biggest hydroelectric power potential located at Inga, some other questions arise. Should the electricity, necessary to fulfil the whole country needs, be produced by the INGA site and distributed across the country, or should the production rely on medium and small sized plants of diversified renewable energies scattered across the country? This paper aims at providing a detailed analysis of possible solutions. It will address multiple challenges such as science, economics, politics, security and the environment on which the Congolese society can rely to take a decision.

This paper explores the economic prospects for investing in the renewable energy (RE) potentials available to Nigeria, from resource availability to fiscal metrics and policy provisions. With the aid of a simplified Levelised Cost of Electricity (sLCOE) method, unit costs of electricity were simulated up to 2040 and used to derive Net Present Values (NPV), Internal Rate of Returns (IRR) and Return on Investments (ROI) for available RE resource potentials. The outcomes indicate that for a 1-gigawatt (GW) power plant capacity, the cheapest source of RE and grid-level electricity, would come from Large Hydroelectric Power (LHP) at US$28.9 MWh−1 and a 12-year payback period on investment.

The main sources of electricity generation in Brazil are hydroelectric plants. With high energy production capacity and more stability than other renewable sources, hydroelectric power plants are essential for the country’s energy security. Thus, it is of strong importance to study actions that allow an increase in the operational availability of the generating units, in order to guarantee efficiency to the process and reduce operating costs that impact directly the value passed on to the final consumer. One of the problems with the greatest impact on the plants is the wear processes of hydraulic turbines, caused by abrasion and cavitation processes. Among the numerous possible solutions, the deposition of a coating by the thermal spraying process has been shown to be efficient. This paper demonstrates the application of machine learning algorithms for modeling the wear problem in Kaplan turbines, predicting the erosion rate of the coating based on the operational characteristics of the hydroelectric plant. The best results have accomplished symmetric mean absolute percentage error (SMAPE) below 10% through 5-fold cross-validation. The model allows for monitoring the wear of the coatings and calculating their remaining life, supporting better estimation for maintenance downtimes of the generating units.

Early power stations in China have been in operation for a long time. Due to the limitations of design, construction materials and technological level at that time, many hydroelectric generators have some defects. The computer monitoring and control system of a hydropower station refers to the measurement, control, protection and monitoring of the entire equipment of a hydropower station completed and realized by the computer system. The computer monitoring and control system of hydropower station replaces the traditional control equipment, fault recording equipment, monitoring and measuring equipment and relay protection equipment. This paper studies the full homomorphic encryption algorithm, introduces the zero-knowledge proof technology into the block chain trading protocol based on the full homomorphic encryption, and constructs the block chain that protects data privacy.

The development of monitoring and control system in hydroelectric power plant can be started from the early manual control, which consists of a simple operation platform consisting of relays, operation buttons, signal lights and buzzers. The monitoring system can realize partial operation and monitoring of the unit, and the operation platform of electromechanical equipment is separated. This paper analyzes the threat of network communication in power plants and introduces the development status of network communication isolation technology at home and abroad. On this basis, through the demand analysis, this paper puts forward a design scheme of industrial network data monitoring and isolation device based on FPGA. The experimental results show that the designed industrial network data monitoring and isolation devices have high accuracy, security and transparency, and can indeed provide reliable guarantee for the network communication security of power plants.

In the present paper, an automated housing block model is proposed that allows saving electricity and water while facilitating self-generation of energy as ways to make the building self-sustaining. Methodologically, the work combines alternative technologies of self-generation such as: Peak urban-type hydroelectric power plants, photovoltaic systems, slow wind turbines with an exciter system supported by permanent magnets, intelligent elevators, supported by lighting systems with the use of natural light and intelligent elevators. The power generation sources and the support systems are managed with a control system that uses cloud computing applications to facilitate the management of several buildings at the same time. The results show the benefits in terms of self-generation that for some hours of the day allows 100% coverage of the energy demand of the buildings and additionally the possibility of having surplus energy for sale to the network operator.

The unit dispatch problem is defined as the attribution of operational values to each generation unit inside a hydro-power plant (HPP), given some criteria such as the total power to be generated, or the operational bounds of each unit. An optimal dispatch programming for hydroelectric units in HPP provides a larger production of electricity, with minimal water use. This paper presents an evolutionary approach to optimize the multi-criteria electric dispatch problem in a general HPP, based on a Multi-objective Evolutionary Swarm Hybridization (MESH) algorithm. The proposed approach integrates mathematical models and evolutionary swarm computation. The experimental analysis shows that the proposed MESH algorithm is able to reach competitive results when compared with classical evolutionary algorithms, the NGA-II and SPEA2 basing on ANOVA inference test. Results also show that the proposed MESH is able to save a large amount of water in the energy production process, supplying the requested load, and minimizing blackout risks and generating a profit around $275,000 monthly.

To benefit from all advantages of a hydropower plant, seen as a renewable source, reliable and low cost of the injected electricity in the power grids, the Hydro Plant Operator (HPO) must ensure the optimal operating regimes and an efficient maintenance program. In this context, a clustering- based methodology has been proposed in the paper to determine the representative operating characteristics (ROCs) of a hydropower plant, considering time slices associated with each generating unit. The results have confirmed the performance of the proposed approach from the point of view of the computational time and the quality of partition obtained associated with the patterns of the operating characteristics. These patterns can represent the support offered to the HPO to provide for an optimal operating of a hydropower plant.

The goal of the study presented in this paper is to highlight the different technologies used for storage of energy and how they can be applied in smart grids. Most of the modern energy technologies, such as the use of smart grids, are shifting to the exploitation of renewable energy sources (RES). Various energy storage (ES) systems including mechanical, electrochemical and thermal system storage are discussed. Battery energy storage system is the most common ES technology currently being used because of its low cost. Other ES technologies discussed include hydro, pump hydroelectric and thermal ES, including latent, sensible and thermochemical. Addressing each of these issues would ensure that the smart grids are strong and intelligent enough as an innovative network.

The climatic conditions in India are among the best that can be used maximise solar energy potential and are capable enough to make solar energy serve the purpose as an alternative source of electricity to Thermal and Hydro electricity. However, the high installation costs of the solar panel coupled has prevented solar energy growth in the country. But when looked at from a broader perspective, solar energy can decrease the costs for electricity as well as help to reduce the adverse effects of using non-renewable energy resources like Thermal electricity. The proposed system determines a mechanism to estimate the amount of savings that an individual could make by using a solar panel on their rooftop. Deep Learning is applied to process and segment the rooftop images while removing obstructions such as trees, electric poles etc. and estimate the area of the rooftop. The solar radiation values and weather patterns of a region are considered and the calculated area is used to predict the amount of energy that can be produced by installing a solar panel on the roof.

In the work, a study was carried out of the state of relay protection at hydroelectric power plants (HPP) in North Ossetia-Alania and related entities, which revealed a strong degree of deterioration of the installed electromechanical relay protections and numerous violations of the established standard operating periods. It was revealed that microprocessor-based relay protection systems have a significant advantage over the electromechanical ones currently in operation at hydroelectric power plants, which consists in the possibility of self-diagnosis, documenting all the processes that take place, which will greatly facilitate the analysis and search for the causes of any emergency, multifunctionality and a number of less significant advantages. Thus, the re-equipment of the HPP for a modern microprocessor-based relay protection and automation system will significantly increase the reliability of protection and facilitate the analysis of any emergency situations.

This paper presents the software package that implements the ability to study large-scale hydroelectric power systems with complex hydraulic and electrical connections, planning long-term regime of hydro power plant with the requirements of water users on the example of the Votkinsk hydroelectric plants, and training for the calculation of the water-energy regime of hydroelectric power. The complex is developed in the high-level Python programming language based on the current requirements specified in the rules for the use of water resources of the Votkinsk reservoir. The calculation in the software package is performed by the direct method. Given that the software package is suitable for both research and training. To improve the quality of the calculation, we consider method of swarm optimization. The complex is planned to be used in the course of laboratory work on the planning of the HPP operation mode, and for checking course papers.

Solar Photovoltaic (PV) plant installations are expanding noticeably throughout the world at an aim to generate electricity from clean and renewable sources. However, large scale PV plants are not sustainable as they are creating enormous burden of intense land requirements particularly for the country have higher population density. To preserve the valuable land, installing PV plant on water bodies like lakes, dams, reservoir, river, canals and ponds can be an attractive alternative for harnessing solar energy and is typically known as Floating Solar PV (FSPV). FSPV not only utilize the duty-free water surface, but it has enormous advantages compared to terrestrial land based PV plants including high energy efficiency due to cooling effect from water evaporation, less obstacles to block sunshine, prevents water evaporation, land and water conservation, limits algae growth by blocking penetration of sunlight. Moreover integration of floating solar PV plant with hydropower plant by installing at dam reservoir for the utilization of optimum energy combination is an excellent opportunity that could reduce the additional transmission and distribution cost. In this paper, technical feasibility and economic viability of a 50 MW p FSPV plant integrated with hydroelectric dam in Bangladesh has analyzed. The levelized tariff of electricity at USD 0.056/kWh and around 9 years of payback period confirm the feasibility of the projected plant which able to produce more power than conventional PV plant. Furthermore, the plant could reduce 52.8 million tonnes of CO 2 emission by crafting environmentally sustainable.

this paper examines the renewable energy capacity in the Republic of Ingushetia in order to increase the stability of electricity supply, to cover the power shortage that hinders the industrialization of the republic, and to solve the problem of the quality of electric energy. In the Ingushetia, the problem of debt for non-payment of electricity, non-transparency of the accounting system, quality, and stability of electricity supply is acute. The authors consider the potential use of using renewable energy resources, including solar, wind, hydroelectric, and geothermal energy, and examine the major indicators of Ingushetia. The expediency of implementing decentralized energy based on renewable energy sources is investigated. The possibility of introducing intelligent networks is being considered.

The paper presents an analysis of the structure of installed capacity and the role of small and micro hydroelectric power plants in covering electrical loads and the stability of the power system. As part of the study of the structure of production and installed power, an analysis of the state of micro-, small hydropower has been carried out taking into account their technical characteristics and parameters and the potential of electric power generation by such hydroelectric power stations has been evaluated. The operation shows the possibility of covering electrical loads in peak operation modes. Obtained results of analysis can be used in development of models and methods of estimation of reliability and efficiency of generating facilities, creation of digital systems on the basis of continuous accounting and analysis of data on technical condition of power equipment and parameters of electric power generation.

In the countries where most of the generation is hydroelectric, the long term operation planning is performed using techniques of decision making under uncertainties, due to the nature of water inflows. Also, in power systems with these characteristics which are in the process of deregulation, rules were designed in a way that generators could simultaneously profit and be protected from the risk of uncertainties. In the case of the Brazilian power market, the plan of operation defines the maximum energy a power plant can sell in a specific year but allows facilities to distribute it among the months of the year of the contract. Once the energy price is defined based on stochastic simulations, different strategies of generation distributions can be simulated and used to determine the expected profit, considering the energy available for the forthcoming year along with the short-run price of the power market. In this paper, a case study for maximizing the revenue of hydroelectric in Brazil is presented in which experiments using the Itaipu power plant were performed and discussed to illustrate the expected outcomes.

Owing to its fast response, the hydro power plant is normally assigned to provide spinning reserve for the power system. Despite of its large capacity, minimum generation constraint and lack of management of multi-unit generations result in limited spinning reserve. This paper solves this problem by integrating a battery energy storage system with the hydro power plant and proposes a unit management algorithm to cooperatively manage the multi-unit generation. As a result, the hydro power plant can virtually provide any demanded generation, and its spinning reserve is increased significantly compared to the traditional operation. A case study on Rajjaprabha hydro power plant in Thailand is conducted to confirm feasibility of the proposed concept.

Renewable energy, such as solar, is one of the main reasons for changing the scope of the electricity sector. However, their availability depends on the climate so they cannot be a constant source of producing electricity. Considering all these aspects, water is considered a steady source for generating power. The main motive of the system, proposed in this paper, is to generate hydroelectricity by utilizing wastewater through the recycling process. Different chambers are provided with exclusive features to make the recycling process for getting reliable and sustainable energy. One motorized pump has been incorporated to maintain the constant water flow during the recycling process and this DC motor has been powered by the solar panel accordingly giving energy based on the utilization of sunlight. By utilizing this prototype device, a succeeding amount of electricity can be generated as an output with continuous recycling of water. Approximately, 119.3 mA of electricity and 12.69 volts DC controlled output can be measured after the proper implementation of the project. Therefore, 1.51 watts of power is possible to generate by utilizing this prototype device. Furthermore, one of the main utilizations of this project is to install it in the mosques where ablution water will be used as a flow of source as this water is not too much contaminated. Thus it can be a possible source for generating hydroelectricity.

Energy has become one of the most important drivers of socio-economic growth. However, situations in developing countries are almost overlooked. Here Nepal is taken as one example, and is found that the results are of great importance to the sustainable of human being. Nepal is a country with a tremendous potential for different types of energy but it relies heavily on imported fossil fuel for its energy needs. Being rich in water resources and with a diverse geography, renewable resources such as hydroelectric, solar and biomass have become relatively reliable substitutes for fossil fuels. This study traces Nepal’s current energy requirements and builds a data model to forecast future demands. It further depicts the role of renewable energy in Nepal to supplement its energy needs. Both qualitative and quantitative data analysis are utilized to highlight the prospects for renewable energy in Nepal. It also focuses on the prospects and constraints for the advancement of renewable energy technologies (RETs). It is also recommended for the advancement, growth and implementation of RETs in Nepal

One of the major and growing problems in the electric grid is the integration of large scale Renewable Energy (RE) sources with conventional energy sources. Curtailment of RE generation is also an increasing concern in the electric power system. At present, a large amount of both wind and solar energy generation is connected to the power systems in California. This imposes new challenges in the grid and leads to curtailment of renewable energy resources. This paper presents solutions for reducing RE curtailment in California. The optimal energy management problem for minimizing RE Curtailment is formulated as a resource allocation and scheduling problem based on the actual supply-demand scenario in California in 2020. A quantitative study of the RE curtailment reduction potential in California is developed based on various existing and envisaged opportunities in the state. RE curtailment is reduced by first controlling the output of the Hydro Power Plant, then the reduced curtailed energy is exported to other grids who require power especially during peak demand intervals. The remaining curtailment energy is then stored into an Energy Storing System (ESS) typically being Battery. The curtailment reduction algorithm is developed usingMATLAB.

Renewable power sources such as solar, wind, hydroelectric and geothermal are considered sustainable and environmentally sound alternatives to fossil fuels. There is a lack of a reliable multidimensional index to assess renewable energy adoption across the world. We aimed to develop a new index to assess the transition to renewable sources in different countries. Variables were reviewed for suitability for inclusion in the index. Three metrics were selected: renewable energy output, consumption of renewable energy, and electricity production from renewable sources. These were used to compile the Renewable Energy Index (REI). Analysis showed that REI ranged from zero to 69.5 (mean 23.1) across 142 countries. Nations such as Denmark, Norway and New Zealand were ranked high while oil-dependent countries had a lower index value. The REI is a novel measure of adoption of renewable energy sources in countries across the world. It has the potential to be used in economic analyses and planning for sustainable development. The Index may be useful in comparing countries and regions in order to encourage investment in renewable energy production.

The Russian electric power complex operates mini hydroelectric power plants with installed capacity up to 5 MW. The quantity and installed capacity of such power plants are not significant, but they, along with large power plants, perform the function of ensuring reliable power supply to consumers in regional power systems or in remote areas.

Isolated load is considered a popular case and especially in the remote or rural areas in which diesel generators are used to cover the demand with special care of their environmental impact. This paper introduces an off-grid hybrid system (PV/Biomass/Hydroelectric Pumped Storage) as a study case in Iraq which is considered a clean, inexhaustible, and reliable energy system to achieve the sustainable and development targets. In this work, Atom Search Optimization (ASO) algorithm has been utilized to determine the optimal configuration of the hybrid system. The optimal sizing is determined from the economic point of view that achieving minimum Net Present Cost (NPC) for the whole system by using a real-time load demand information and meteorological data of a certain location in Iraq.

This work is focused on the use of a hybrid system (PV-Pumped storage) to satisfy demand for electric energy in a rural area in Iraq. Therefore, a techno-economic study will be presented to realize a minimum Net Present Cost (NPC) for this system and minimize the loss of power supply probability (LPSP) and percentage of the excess energy (EXC) that results in increasing the reliability of the power supply. The Equilibrium Optimization (EO) algorithm has been implemented to evaluate the optimal size of the generating units of the proposed hybrid system. The simulation results ensured the technical possibility of this system and proved the reliability and the effectiveness of the proposed algorithm.

In today's world, large scale hydroelectric power plants have an impact in the energy demography; although, the huge potential of pico, micro and mini-hydropower plants are still very much untapped. In this work, a techno-economic viability, of mini hydro power potential from drainage water, has been investigated in four areas of Dhaka city. Considering the head of water fall and the flow rate in the drainage system, technical, economic and environmental parameters are studied. 100 kW to 500 kW power can be generated from the proposed system with economic benefit of around BDT 3. 9M to 28M per year, and emissions reduction of around 500 to 3000 ton- CO2/year.

Short-Term Hydrothermal Scheduling (STHS) is a classic problem in power system operation where the aim is to decide the dispatch of both thermal and hydroelectric units. This problem is complex due to its non-linear non-convex nature, and the requirements for fast solving for daily operation. Technologies such as wind and solar generation introduce stochastic behaviors, which have to be considered within the mathematical model. Although the problem is frequently solved by traditional and heuristic techniques, this paper proposes a new formulation based on convex approximations, and in particular, Second-Order Cone optimization, which addresses the nonlinear relation among water discharge, reservoir volume, and hydropower generation in a rigorous mathematical approach. Moreover, the impact of wind and solar generation on the power system is analyzed, modeling their stochastic behavior in a robust way by using chance-box constraints. Numerical results demonstrate that the Second-Order Cone approximation is precise and faster than techniques proposed recently and that the chance-box constraint approach guarantees a robust solution.

Future generation will mostly depend on renewable energy resources due to lack of conventional energy resources, hence existing renewable energy resources are being modified for efficiency improvement and enhancement of power generation. Water is a huge source of renewable energy used in hydro power plants. Modelling of hydro power plant is shown in this paper and also a complete simulation model is designed. The purpose of this paper is to control the output frequency of hydro power plant. Variation in flow of water disturbs the speed of hydraulic turbine which results in variable voltage and frequency at the generator output. Therefore in order to obtain the constant frequency at the hydro power plant a PID controller is being used in governor. In this research, the controller parameters are obtained using two techniques ZeiglerNichols (Z-N) technique and Ant Colony Optimization (ACO). ACO is used to overcome the problems in traditional Z-N technique. The frequency output of the hydro power plant using both techniques are compared which proves that ACO is better than Z-N technique. This paper work can be used for practical purposes and theoretical analysis.

Solar photovoltaic (PV) based Pumped storage hydro (PSH) system has greater privilege over several storage systems in a distributed generation system. Although Pumped storage is not a direct device to store electrical energy, it facilitates the availability of electricity on-demand, through the discharge of stored water to the turbine. PSH system is useful for a wide range of applications such as irrigation, drinking water supply, and Power generation whereas India has the installed capacity of 4786 MW of power generation system through PSH which accounts for 10% of the total hydroelectricity generation capacity. In this proposed system Solar PV is used to pump water during an off-pick time and allow its release during peak time through Pico hydro turbine to uphold the stability in energy flow. Solar PV shows a potential substitute to the centralized electricity and conventional diesel-based hydro pumping system. Thoughtful of system design and an assortment of suitable parameters are necessary to attain the reliability and efficiency of any system. For PV system design and optimization, parameters such as climate data of the proposed location, solar irradiation, operating temperature and loss factors are considered. For the water pumping system (WPS), type of pump, controller, flow rate, storage size and physical parameters of the pump is preferred for efficient design consideration. Economic analysis of the system is done for the proposed site (Latitude. 19.047, longitude S3.S31) in Odisha by considering design parameters for both PV system and Pump while the results are validated through simulation software PV Syst 7.0.5 to understand the performance characteristics.

The use of solar photovoltaic panels has grown significantly in recent years. Floating solar photovoltaic (FPV) installations open up new opportunities for scaling up solar generating capacity. They can integrate with hydroelectric power plant (HPP) and have significant effects on supplying the electrical loads at different months of the year, especially hot and dry seasons. In this paper, the technical and economic parameters of a hybrid HPP FPV system in “Sardasht” region in West Azerbaijan province are studied using sensitivity analysis, and optimal designs in various scenarios are obtained for different values of the load, water levels behind the dam and equipment cost multipliers. In addition, by performing diverse simulations in HOMER software with more than 50000 studies, an optimal scheme is proposed to serve the maximum electrical load for different water levels in water shortage circumstances. The results confirm the effectiveness of the proposed techno-economic scheme.

The value of flexibility in operations for hydroelectric power plants is apparent from their investment in multiple generators to allow variable intensity of operation. This flexibility supports rapid response to outside factors that impact their performance. It follows that hydroelectricity generation often competes for water flow with downstream water demands including irrigation, urban water use, or ecosystem services. Each of these follows stochastic process that implies asynchronous demand for water flow. The associated management problem is of interest encompassing multiple switching and motivating other extensions. This paper considers the dynamic stochastic problem of water allocation for hydroelectric generation and downstream use. Our main contribution is to present a novel numerical solution to this problem. Moreover, the method allows generalization not previously possible including: (i) multiple dynamic stochastic processes with jump diffusions, (ii) the number of contingent decisions with reversibility, and (iii) characterization of risk and uncertainty including dynamic constraints.

The safety issue of technical water supply pipelines in hydroelectric power plant has been an ingrained problem, especially for the old hydraulic power plants. On the one hand, the original design and manufacture are inferior in quality; on the other hand, as the corrosion aggravates over time, water leakage and seepage frequently arise. In acute cases, the workshop may be flooded and other major accidents may occur accordingly. Starting with an accident that the fire hose of stator broke apart, this paper analysed the causes for pipeline break and presented relevant rectification scheme. It has provided technical guidance for maintaining and reconditioning the same type of water pipes.

The abundance of clean and renewable electrical energy constitutes a strategic asset for the development of the countries, and Paraguay has great availability of hydroelectric energy based on its participation in the binational power plants Itaipu and Yacyreta, in condominium with Brazil and Argentina.. However, a large part of the electricity production is not consumed in the country and is transferred to both Argentina and Brazil. In this sense, it is clear that the strategic use of the surplus of hydroelectricity that is currently being transferred could be key to lead the process of economic and social development in Paraguay, either by encouraging the consumption of its energy through the installation of industries, thus generating jobs and mobilizing the internal economy, or selling the surplus to third countries. Any selected alternative and the rejection of other alternatives will be inextricably linked to an opportunity cost. This work presents a methodology that allows identifying the opportunity cost of the sale of Paraguayan electricity to the Brazilian electricity market, with the use of the Analytical Hierarchy Process (AHP). It was possible to determine energy sales prices in the Brazilian market, for which rents would be generated that would significantly affect the development of Paraguay, ranging from US $63,55/MWh to US $2.841/MWh. It can be concluded that a scenario of high export of Paraguayan hydroelectric energy to Brazil presents an opportunity cost, for several scenarios where decision makers have a notorious predilection for the Economic, Environmental and Social criteria, in addition to some combinations of these criteria with others.

Indonesia has an electrification ratio target of 100% by 2020. This target is supported by the projected electricity demand to increase more than seven times by 2050. Therefore, the government needs to build new generators to increase the national electricity production capacity. The Ngadingoro River in Trenggalek Regency, with its fast-flowing water, is an area that has the potential to become a power plant. This study aims to create a portable pico hydropower plant to optimize the use of renewable energy to generate electricity. The power plant made in this study utilizes the power of river water as a driving force. It modifies the floating ponton's hull to become portable in adjusting the water level and optimize the kinetic energy of the water flow. The results showed that this portable floating hydropower works well by producing 720 watts of electricity/day.

Snow is an essential parameter of the cryosphere and plays a fundamental role in the hydrological cycle, therefore monitoring of the snow is of great importance specially with regard to irrigation, hydroelectric power generation, and for human consumption and production. Satellite Remote Sensing, with both optical and Synthetic Aperture Radars (SAR) instruments, can provide distributed observations of snow cover over extended and inaccessible areas such as the Andes. In this study through optical data Landsat 8, snow cover area was obtained, then applying the change detection method developed by Nagler y Rott (2000), Sentinel 1 data was used for wetsnow classification. With the cartography and with data from the gauging stations, hidro-snowy seasonal dynamics was analyzed. The study was carried out in The Andes in the province of Mendoza over the Rio Mendoza and Rio Tunuyan basins. The results obtained show the relevance of the satellite sensors to determine the snow cover and to estimate with SAR images, the wet snow, which represents a flow input to the rivers and reservoirs located downstream.

In view of the increase in electricity demand, the world is making use of sustainable energy to meet the demand without compromising the ability of future generations. Sustainable energy is nothing but renewable energy sources such as hydroelectricity, biomass, wind, tidal, geothermal and solar energy. Because of high room temperature and the high intensity of sunlight the ventilation is necessary for workshops, industries or factory buildings for cooling purposes. This paper briefs about small scale power generation using a Permanent Magnet Synchronous Generator (PMSG) which is driven by the rooftop ventilator and discusses the development of a power generation system using a Rooftop Ventilator. This system does not consume any electrical power for its operation. The generator is frameless, having the rewound ceiling fan stator and permanent magnet as the rotor in N-S pattern. The ventilator rotates, the flux of PM moves across the air gap and EMF is induced in the coil which is sufficient to charge 12V battery and later used for household work or LED lighting load when required. After implementing and testing, the prototype has been proved feasible for practical applications and can contribute little to meet energy demand.

Global mission is to reduce the carbon footprint by using “Renewable Energy resources”. It is important to speed up the development of Renewable Energy Resources like Solar, Wind, Hydro electric et al. Implementation of Renewable Energy helps to tackle the climate change issue, as most of the energy resources are currently fossil fuel based. Information on installed capacity of Solar PV Panels and Wind Turbines along with forecasted load can enable grid operators to ensure optimal and reliable operation of system. Deep learning framework is used here to detect the Wind Turbines and Solar PV Panels in Satellite images. The current work aims to remove the manual effort which is currently involved in surveying the renewable energy resources. Building-level or neighborhood-level information on Solar PV panels and Wind Turbines enable analysis of Solar PV panels and Wind turbines deployment. Carbon footprint and Payback period can be calculated using the Deep Learning model outcome approximately for the installed locations and proposed locations. Dataset was acquired from Google Maps (Satellite view) for this work.

In a hydro power plant (HPP), water that passes through a turbine will flow into the tailrace and flow back into the water channel. Water energy can be used to generate electrical power using a very low head-type turbine. However, currently, energy from HPP tail water has not been appropriately utilized. This paper discusses the study of various types of very low head hydro power to exploit the potential of electrical energy in the HPP disposal channel. The chosen location is the Dago HPP, located in Bandung, West Java, owned by PT. Indonesia Power. Technical studies are necessary to determine the magnitude of electrical energy’s potential, the suitable type of technology application, and the investment costs requirement. The location survey knew that the Dago HPP has an average flow rate of 1.192 m3/s, 1.7 m of the head, and the potential electrical energy generation is around 13.9 kW. Several types of very low power plants apply as alternatives: water wheels, Archimedes screw turbines, propeller submersible turbines, and vortex turbines. Building Micro Hydro Power Plant (MHPP) using a waterwheel required an investment cost of around IDR 335 million, an Archimedes screw turbine of IDR 445 million, a submersible propeller turbine of IDR 360 million, and a vortex turbine of IDR 315 million. The comparison from the four VLH shows that the Vortex turbine is the most potential technology because it produces a large amount of electrical energy at the cheapest investment cost.

Efficiency is a requirement when it comes to utilizing a wireless sensor network (WSN) where hydrokinetic energy harvesting through turbine is involved. Thus, not only WSN needs an efficient supply but also the sensors and the storage unit which are powered up by an energy harvesting module, a turbine DC generator. Turbine DC generator produces a low voltage and low voltage means low power. To produce high efficiency output despite the low power it produces, a DC-DC converter is one of the preliminaries. DC-DC converter regulates its input coming from the turbine DC generator and produces a more stable power supply. However, blocks that the DC-DC converter supplies have different voltage requirement. Therefore, the researchers will develop two DC-DC converter topology which are the Buck Converter and the Boost Converter. On the contrary, turbine DC generator produces varying DC supply to the boost converter inducing noises and reducing the efficiency needed. Therefore, to achieve a highly efficient output the device needs to be low noise. To prevent noise from affecting the efficiency of the device, the researchers will use a technique called Hysteretic Control (HC) of DC-DC converter. This research intended to design a high efficiency Direct Current-to-Direct Current Converter for hydroelectric energy harvester in wireless sensor network. Using an Electronic Design Automation (EDA) tool, Synopsys, and ensuing the full custom analog design is practiced, the researchers develop a DC-DC converter that will provide an efficiency of 80% - 95% by reducing the noise by using a switching DC-DC converter.