Optimization and Evaluation of Environmental Operations for Three Gorges Reservoir

Abstract

This study proposed a multi-objective environmental reservoir operation methodology (MOEROM) and applied the new methodology to the Three Gorges Reservoir (TGR) in China. The MOEROM directly incorporated the statistical water quality models in the objective functions to reflect the response relationships between reservoir operations and water quality in three tributaries (the Xiangxi River, the Daning River and the Xiaojing River). A real-coded genetic algorithm with self-adaptive crossover operators was employed to solve the environmental reservoir operation model. And four different MCDA approaches (AHP, TOPSIS, Fuzzy AHP, and Fuzzy TOPSIS) were proposed to evaluate the optimal operational schemes. The results showed that TOPSIS and AHP were more suitable for selecting the schemes than the others because of the larger fluctuations. To demonstrate the advantage of MOEROM, the environmental operation schemes were compared with traditional and practical operation schemes in 2013. The advantages of the environmental operation scheme over the others were that it would help reach a compromise between economic benefit, flood control and water quality improvement. In the future, more water quality indices, uncertainties in water environmental information, and more efficient algorithms would be further considered and researched.Water Resour Manage (2016) 30:3553-3576 DOI 10.1007/s11269-016-1370-2 Electronic supplementary

An efficient and accurate Mixed‐integer linear programming model for long‐term operations of large‐scale hydropower systems

“…The first term on the right-hand side of (11) is the average forebay water level of reservoir r at time period t, where Z up r (⋅) is a function of volume of reservoir r. The second term indicates the tail-race water level of reservoir r at time period t, where Z down r (⋅) is a function of the discharge of reservoir r. The third term is the penstock losses of reservoir r in time period t, where H loss r (⋅) is a function of turbine discharge of reservoir r. In the real operation of China, the above-mentioned functions are all non-linear functions obtained by smooth interpolation through a large number of given design or measured points. This paper approximates the tail-race water level by (12) :…”

“…Although the improved algorithms have mitigated the dimensionality problem, they tend to reduce the global search capability. Group (b) mainly includes GA [11,12], culture algorithm [13], kidney algorithm [14], and so on. Heuristic algorithms can cope with the non-linear non-convex characteristics of the HROO, and have strong global search capacity.…”

Water Environment Variation in the Three Gorges Tributary and Its Influencing Factors on Different Scales

“…The regional water environment is determined by the combined influence of various factors, including regional geography and meteorological factors on a macro-scale [37], hydrodynamics, channel morphology, and human disturbance at the medium-scale [38], and water exchange, transmission, physiological geochemical reactions, biomes, and the like on the micro-scale [39]. Nogueira et al [40] believe that for tropical and subtropical monsoon aquatic ecosystems, variation in the water environment is usually driven by seasonal patterns of sunlight, rainfall and wind.…”

بهینه‌سازی چند هدفه ی بهره‌برداری از منابع آب به منظور تعیین نیاز اکوسیستم های آبی بر اساس الگوریتم های فراکاوشی

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