Optimizing the Reservoir Operation for Hydropower Generation by Using the Flexibility Index to Consider Inflow Uncertainty

Reservoirs play important roles in hydropower generation, flood control, water supply, and navigation. However, the regulation of reservoirs is challenged due to their adverse influences on river ecosystems. This study uses ecoflow as an ecological indicator for reservoir operation to indicate the extent of natural flow alteration. Three reservoir optimization models are established to derive ecological operating rule curves. Model 1 only considers the maximization of average annual hydropower generation and the assurance rate of hydropower generation. Model 2 incorporates ecological objectives and constraints. Model 3 not only considers the hydropower objectives but also simulates the runoff and calculates the ecological indicator values of multiple downstream stations. The three models are optimized by a simulation-optimization framework. The reservoir ecological operating rule curves are derived for the case study of China's Three Gorges Reservoir. The results represent feasible schemes for reservoir operation by considering both hydropower and ecological demands. The average annual power generation and assurance rate of a preferred optimized scheme for Model 3 are increased by 1.06% and 2.50%, respectively. Furthermore, ecological benefits of the three hydrologic stations are also improved. In summary, the ecological indicator ecoflow and optimization models could be helpful for reservoir ecological operations.

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Assessment of the Multi-Objective Reservoir Operation for Maintaining the Turbidity Maximum Zone in the Yangtze River Estuary

International Journal of Environmental Research and Public Health ◽

10.3390/ijerph15102118 ◽

2018 ◽

Vol 15 (10) ◽

pp. 2118 ◽

Cited By ~ 4

Author(s):

Yang Yu ◽

Peifang Wang ◽

Chao Wang ◽

Xun Wang ◽

Bin Hu

Keyword(s):

Reservoir Operation ◽

Yangtze River ◽

Environmental Flows ◽

River Estuary ◽

Yangtze River Estuary ◽

The Yangtze River ◽

Operation Model ◽

Hydropower Generation ◽

Quantitative Correlation ◽

The Yangtze River Estuary

The construction of multifunction reservoirs is important for flood control, agriculture irrigation, navigation, and hydropower generation, but dam construction will inevitably affect the downstream flow and sediment regimes, which can cause some environmental and ecological consequences. Therefore, this paper aims to propose a framework for assessing the multiobjective reservoir operation model based on environmental flows for sustaining the suspended sediment concentration (SSC) requirements in the turbidity maximum zone (TMZ). The Yangtze River Estuary was used as a case study. Through using an analytical model, a quantitative correlation between SSC and water flow rate was established. Then, the quantitative correlation and the SSC requirements were applied to determine the environmental flows for the estuarine TMZ. Subsequently, a multiobjective reservoir operation model was developed for the Three Gorges Reservoir (TGR), and an improved nondominated sorting genetic algorithm III based on elimination operator was applied to the model. An uncertainty analysis and a comparative analysis were used to assess the model’s performance. The results showed that the proposed multiobjective reservoir operation model can reduce ecological deficiency under wet, normal, and dry years by 33.65%, 35.95%, and 20.98%, with the corresponding hydropower generation output lost by 3.37%, 3.88%, and 2.95%, respectively. Finally, we discussed ecological satiety rates under optimized and practical operation of the TGR in wet, normal, and dry years. It indicated that the multiobjective-optimized runoff performs better at maintaining the TMZ in the Yangtze River Estuary than practical runoff. More importantly, the results can offer guidance for the management of the TGR to improve the comprehensive development and protection of the estuarine ecological environment.

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A real-time operation of the Three Gorges Reservoir with flood risk analysis

Water Science & Technology Water Supply ◽

10.2166/ws.2015.172 ◽

2015 ◽

Vol 16 (2) ◽

pp. 551-562 ◽

Cited By ~ 2

Author(s):

Yixiang Sun ◽

Deshan Tang ◽

Huichao Dai ◽

Pan Liu ◽

Yifei Sun ◽

...

Keyword(s):

Risk Analysis ◽

Flood Risk ◽

Reservoir Operation ◽

Three Gorges Reservoir ◽

Three Gorges ◽

Hydropower Generation ◽

Inference System ◽

The Three Gorges Reservoir ◽

Flood Season ◽

The Three Gorges

Risk analysis is essential to reservoir operation. In this study, a new analysis for reservoir operation is proposed to enhance the utilization rate of the flood water from the Three Gorges Reservoir (TGR) during the flood season. Based on five scenarios of hydrology forecasting with the adaptive neuro-fuzzy inference system (ANFIS), a multi-objective optimum operation was implemented employing the risk control constraints of the genetic algorithm (GA) for the TGR. The results of this analysis indicated that the optimum hydropower generation was 5.7% higher than the usual operating hydropower generation, which suggested that, during flood season, it would be beneficial to increase hydropower generation from reservoirs, while maintaining a safe degree of flood risk.

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Comparison of Optimal Hedging Policies for Hydropower Reservoir System Operation

Water ◽

10.3390/w11010121 ◽

2019 ◽

Vol 11 (1) ◽

pp. 121 ◽

Cited By ~ 3

Author(s):

Aida Tayebiyan ◽

Thamer Ahmad Mohammad ◽

Nadhir Al-Ansari ◽

Mohammad Malakootian

Keyword(s):

Power Generation ◽

Reservoir Operation ◽

Water Storage ◽

Optimal Decision ◽

Hydropower Generation ◽

Mean Power ◽

Reservoir System ◽

Operation Rules ◽

Significant Difference ◽

Hydropower Reservoir

Reservoir operation rules play an important role in regions economic development. Meanwhile, hedging policies are mostly applied for municipal, industrial, and irrigation water supplies from reservoirs and it is less used for reservoir operation for hydropower generation. The concept of hedging and rationing factors can be used to maintain the water in a reservoir for the sake of increasing water storage and water head for future use. However, water storage and head are the key factors in operation of reservoir systems for hydropower generation. This study investigates the applicability of seven competing hedging policies including four customary forms of hedging (1PHP, 2PHP, 3PHP, DHP) and three new forms of hedging rules (SOPHP, BSOPHP, SHPHP) for reservoir operation for hydropower generation. The models were constructed in MATLAB R2011b based on the characteristics of the Batang Padang hydropower reservoir system, Malaysia. In order to maximize the output of power generation in operational periods (2003–2009), three optimization algorithms namely particle swarm optimization (PSO), genetic algorithm (GA), and hybrid PSO-GA were linked to one of the constructed model (1PHP as a test) to find the most effective algorithm. Since the results demonstrated the superiority of the hybrid PSO-GA algorithm compared to either PSO or GA, the hybrid PSO-GA were linked to each constructed model in order to find the optimal decision variables of each model. The proposed methodology was validated using monthly data from 2010–2012. The results showed that there are no significant difference between the output of monthly mean power generation during 2003–2009 and 2010–2012.The results declared that by applying the proposed policies, the output of power generation could increase by 13% with respect to the historical management. Moreover, the discrepancies between mean power generations from highest to lowest months were reduced from 49 MW to 26 MW, which is almost half. This means that hedging policies could efficiently distribute the water-supply and power-supply in the operational period and increase the stability of the system. Among the studied hedging policies, SHPHP is the most convenient policy for hydropower reservoir operation and gave the best result.

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Optimal Reservoir Operation for Hydropower Generation using Non-linear Programming Model

Journal of The Institution of Engineers (India) Series A ◽

10.1007/s40030-012-0013-8 ◽

2012 ◽

Vol 93 (2) ◽

pp. 111-120 ◽

Cited By ~ 24

Author(s):

R. Arunkumar ◽

V. Jothiprakash

Keyword(s):

Linear Programming ◽

Reservoir Operation ◽

Programming Model ◽

Linear Programming Model ◽

Hydropower Generation ◽

Non Linear Programming ◽

Non Linear

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Multi-objective reservoir operation of the Ukai reservoir system using improved Jaya algorithm

Water Science & Technology Water Supply ◽

10.2166/ws.2021.374 ◽

2021 ◽

Author(s):

Vijendra Kumar ◽

S. M. Yadav

Keyword(s):

Particle Swarm Optimization ◽

Reservoir Operation ◽

Particle Swarm ◽

Jaya Algorithm ◽

Hydropower Generation ◽

Invasive Weed ◽

Swarm Optimization ◽

Multi Objective ◽

Better Than ◽

Self Adaptive

Abstract This paper introduces an effective and reliable approach based on multi population approach, namely self-adaptive multi-population Jaya algorithm (SAMP-JA), to extract multi-purpose reservoir operation policies. The current research focused on two goals: minimizing irrigation deficits and maximizing hydropower generation. Three different models were formulated. The results are compared with ordinary Jaya algorithm (JA), particle swarm optimization (PSO), and Invasive weed optimization (IWO) algorithm. In Model-1, the minimum irrigation deficit was obtained by SAMP-JA and JA as 305092.99 . SAMP-JA was better than JA, PSO and IWO in terms of convergence. In Model-2, the maximum hydropower generation was achieved by SAMP-JA, JA and PSO as 1723.50 . While comparing the average hydropower generation SAMP-JA and PSO performed better than JA and IWO. In terms of convergence, SAMP-JA was better than PSO. In Model-3, self-adaptive multi-population multi objective Jaya algorithm (SAMP-MOJA) was better than multi objective particle swarm optimization (MOPSO) and multi objective Jaya algorithm (MOJA) in terms of maximum hydropower generation, and MOPSO was better than SAMP-MOJA and MOJA in terms of minimum irrigation deficiency. While comparing convergence, SAMP-MOJA was found to be better than MOPSO and MOJA. Overall, SAMP-JA was found to be outperforming than JA, POS and IWO.

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