Short-Term Optimal Operation of Baluchaung II Hydropower Plant in Myanmar

Saw, May Myat Moe; Chen, Siyu; Yu, Hongjie

doi:10.3390/w12020504

Cited by 6 publications

(5 citation statements)

References 18 publications

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“…For example, it provides about 96 percent of the renewable energy in the United States [36][37][38][39]. Therefore, it has added attention to optimize the operation [40] and generate compensatory of other generation types [41,42]. In the hydraulic power stations (Hydropower on a small scale), the electrical energy can be generated by water kinetic energy, which can activate the mechanical turbine's energy [43,44].…”

Section: The Hydraulic Electrical Power Generation Systemmentioning

confidence: 99%

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Economic Design of Hybrid Pico-Hydraulic/Photovoltaic Generation System: A Case Study in Egypt

2021

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Clean and renewable energy sources are the preferable power system generations for the overall world. This research aims to present a very highly integrated, economic, professional, and simple construction, clean and natural resources usage of the renewable hybrid generation system. This research performs analysis, systematic representation, evaluation, and design of the hybrid proposed system—pico-hydraulic from home usage water and photovoltaic (PV)—to generate an optimal renewable generation system using a new professional control system. Applying this proposed technique in Egypt shows that the hybrid system successfully overcame Egypt’s energy crisis. Renewable energy will rise to 8.782% by increasing 7.323% (14,408.83 GWh/Y). Besides, this system increases the power supply reliability; it gives an additional emergency supply and reduces the exhausts from other generation stations (e.g., CO2). The saving from this hybrid system is very effective for; the residential sector (subscribes), which will be ranged from 9599.298 million E£/10Ys up to 86,393.68 million E£/10Ys that equals 5399.6 million $, government to use this extra generation energy to reduce the maximum loads from various stations. A practical model has been presented with results to verify the high efficiency of the proposed system that illustrates the effective performance of the used hybrid system.

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Section: The Hydraulic Electrical Power Generation Systemmentioning

confidence: 99%

“…V is the velocity of flow, m/s P is the pressure, N/m 2 ρ is the density of water, kg/m 3 H is the height of the level of water above some datum level, m The generated electrical power can be calculated by [39,40,46,[50][51][52][53]:…”

Section: Electric Power Computationmentioning

confidence: 99%

Economic Design of Hybrid Pico-Hydraulic/Photovoltaic Generation System: A Case Study in Egypt

2021

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“…5). The advantages of hydropower through the construction of a storage reservoir include improved hydrological balance and better conditions for navigation (Von Sperling 2012; Bajkowski & Górnikowska 2013; Anderson et al 2014; Zeleňáková et al 2018;Li et al 2020); however, it should be highlighted that they could negatively affect the ecosystem altering the natural hydrologic regime and the water quality, as well as the fish passage (Valero 2012).…”

Section: The Hydropower Plant Impact On the Regionmentioning

confidence: 99%

Hydroelectric Power Plants and River Morphodynamic Processes

Kiraga¹

2021

J. Ecol. Eng.

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Hydropower is one of the renewable energy sources. Hydropower plants generate electricity using the kinetic energy of flowing water. Although hydroelectric power plants are not as prominent as solar or wind farms, it should be noted that they generate the most significant amount of the power. They are also the most technically advanced projects. Power plants are built with different technical parameters of turbines, different sizes of dams or weirs and different ways of exploiting the energy of flowing water. A common feature, however, is the significant impact of hydroelectric power plants on the functioning of adjacent regions. The paper divides this impact into economic and local development, landscape, and ecological functions, emphasizing the interaction of these influences. The paper discusses the hydromorphological changes taking place in the immediate vicinity of the structure, as a consequence of channel development. The processes of aggradation and degradation of the channel are the answer to hydrodynamic equilibrium loss. These hydrodynamic processes are associated with the subsequent ecological response of the habitat. The most important of these include the dynamic equilibrium loss by the river and the subsequent morphological parameters striving to restore it according to Lane's relation, known as the most important principle in the fluvial morphology science. The impact of the hydropower plant on the fluvial environment results, first of all, from a significant environmental impact of the damming of the river itself. If the structure is correctly designed, maintained, and operated, it allows controlling the water conditions upstream and downstream with simultaneous energy production. Due to several geometric, hydraulic, and granulometric changes, and further, the resultant economic, landscape, and natural changes that significantly affect the operation of a region, these should be considered as early as the design stage and should be an integral part of any hydroelectric project.

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“…Time steps for long-term models range from weekly to annual. Long-term models can be useful for short-term models by providing preliminary promising solution regions [20,21]. Hourly or shorter-peak and off-peak times and energy value rates are important for hydropower decisions and pumping plant operations.…”

Section: Introductionmentioning

confidence: 99%

Representing Hourly Energy Prices in a Large-Scale Monthly Water System Model

Dogan,

White,

Yao

et al. 2024

Water

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Water system management models represent different purposes, such as water supply, flood control, recreation, and hydropower. When building large-scale system models to represent these diverse objectives, their most appropriate time steps for each purpose often do not coincide. A monthly time step is usually sufficient for water supply modeling, but it can be too coarse for flood control, hydropower, and energy operations, where hourly time steps are preferred. Large-scale water management and planning models mostly employ monthly time steps, but using monthly average energy prices underestimates hydropower revenue and overestimates pumping energy cost because these plants tend to operate during times with above- or below-average energy prices within any month. The approach developed here uses hourly varying prices depending on the percent of monthly operating hours. This paper examines an approach that approximately incorporates hourly energy price variations for hydropower and pumping into large-scale monthly time-step water system model operations without affecting water delivery results. Results from including hourly varying energy prices in a large-scale monthly water supply model of California (CALVIN) are presented. CALVIN is a hydroeconomic linear programming optimization model that allocates water to agricultural and urban users with an objective to minimize total scarcity costs, operating costs, and hydropower revenue loss. Thirteen hydropower plants are modeled with hourly varying prices, and their revenue increased by 25 to 58% compared to revenue calculated with monthly average constant energy prices. Hydropower revenue improvements are greater in critically dry years. For pumping plants modeled with hourly varying prices, the energy use cost decreased by 10 to 59%. This study improves system representation and results for large-scale modeling.

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Short-Term Optimal Operation of Baluchaung II Hydropower Plant in Myanmar

Cited by 6 publications

References 18 publications

Economic Design of Hybrid Pico-Hydraulic/Photovoltaic Generation System: A Case Study in Egypt

Economic Design of Hybrid Pico-Hydraulic/Photovoltaic Generation System: A Case Study in Egypt

Hydroelectric Power Plants and River Morphodynamic Processes

Representing Hourly Energy Prices in a Large-Scale Monthly Water System Model

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