A Methodology to Assess Optimal Operation of a Prototype for Pressure Regulation and Hydropower Generation

Author(s):  
Nicola Fontana ◽  
Gustavo Marini
Energies ◽  
2019 ◽  
Vol 12 (1) ◽  
pp. 144 ◽  
Author(s):  
Jianjian Shen ◽  
Xiufei Zhang ◽  
Jian Wang ◽  
Rui Cao ◽  
Sen Wang ◽  
...  

This paper focuses on the monthly operations of an interprovincial hydropower system (IHS) connected by ultrahigh voltage direct current lines. The IHS consists of the Xiluodu Hydropower Project, which ranks second in China, and local plants in multiple recipient regions. It simultaneously provides electricity for Zhejiang and Guangdong provinces and thus meets their complex operation requirements. This paper develops a multi-objective optimization model of maximizing the minimum of total hydropower generation for each provincial power grid while considering network security constraints, electricity contracts, and plant constraints. The purpose is to enhance the minimum power in dry season by using the differences in hydrology and regulating storage of multiple rivers. The TOPSIS method is utilized to handle this multi-objective optimization, where the complex minimax objective function is transformed into a group of easily solved linear formulations. Nonlinearities of the hydropower system are approximatively described as polynomial formulations. The model was used to solve the problem using mixed integer nonlinear programming that is based on the branch-and-bound technique. The proposed method was applied to the monthly generation scheduling of the IHS. Compared to the conventional method, both the total electricity for Guangdong Power Grid and Zhejiang Power Grid during dry season increased by 6% and 4%, respectively. The minimum monthly power also showed a significant increase of 40% and 31%. It was demonstrated that the hydrological differences between Xiluodu Plant and local hydropower plants in receiving power grids can be fully used to improve monthly hydropower generation.


2010 ◽  
Vol 14 (10) ◽  
pp. 1895-1908 ◽  
Author(s):  
Q. Goor ◽  
C. Halleux ◽  
Y. Mohamed ◽  
A. Tilmant

Abstract. The upper Blue Nile River Basin in Ethiopia is a largely untapped resource despite its huge potential for hydropower generation and irrigated agriculture. Controversies exist as to whether the numerous infrastructural development projects that are on the drawing board in Ethiopia will generate positive or negative externalities downstream in Sudan and Egypt. This study attempts at (1) examining the (re-)operation of infrastructures, in particular the proposed reservoirs in Ethiopia and the High Aswan Dam and (2) assessing the economic benefits and costs associated with the storage infrastructures in Ethiopia and their spatial and temporal distribution. To achieve this, a basin-wide integrated hydro-economic model has been developed. The model integrates essential hydrologic, economic and institutional components of the river basin in order to explore both the hydrologic and economic consequences of various policy options and planned infrastructural projects. Unlike most of the deterministic economic-hydrologic models reported in the literature, a stochastic programming formulation has been adopted in order to: (i) understand the effect of the hydrologic uncertainty on management decisions, (ii) determine allocation policies that naturally hedge against the hydrological risk, and (iii) assess the relevant risk indicators. The study reveals that the development of four mega dams in the upper part of the Blue Nile Basin would change the drawdown refill cycle of the High Aswan Dam. Should the operation of the reservoirs be coordinated, they would enable an average annual saving of at least 2.5 billion m3 through reduced evaporation losses from the Lake Nasser. Moreover, the new reservoirs (Karadobi, Beko-Abo, Mandaya and Border) in Ethiopia would have significant positive impacts on hydropower generation and irrigation in Ethiopia and Sudan: at the basin scale, the annual energy generation is boosted by 38.5 TWh amongst which 14.2 TWh due to storage. Moreover, the regulation capacity of the above mentioned reservoirs would enable an increase of the Sudanese irrigated area by 5.5%.


2014 ◽  
Vol 955-959 ◽  
pp. 3057-3064
Author(s):  
Zheng Jie Yin ◽  
Jin Chen ◽  
Ji Jun Xu

To mitigate possible negative impacts of cascade dams in the Lower Jinsha River and maintain the natural flow regime of national natural reserve areas of rare and special fishes of the upper Yangtze River, environmental flow (e-flow) demands need to be considered in the cascade dams operation. Due to lack of regular ecological observation data, multiple hydrology-based e-flow methods including Tennant, minimum monthly flow, 7Q10 and Q90 are applied to provide specific e-flow prescripts to guide the reservoir release. A joint operation optimization model is developed for the cascade dams in the Lower Jinsha River for maximal hydropower generation under various e-flow constraints. The economic and ecological performances of cascade dams operation are evaluated by total hydropower outputs and hydrological alteration degree of downstream river individually. The operation results are analyzed and discussed, and some questions on the tradeoff relationship between ecology and hydropower generation, inherent relationship between ecological constrains and hydrological alteration, and rationality criteria of e-flow are further addressed. The conclusions indicate : (1) optimal operation for ecological considerations under e-flow constrains only reduce hydropower outputs slightly, no more than 2.4%; (2) e-flow constrains help lower hydrological alteration induced by hydropower dams, among the four e-flow methodologies Tennant is best in term of ecology; (3) there is a limitation for hydrology-based e-flow methodologies, and it is necessary to stress ecological foundation and ecological relevance for e-flow methodology. The paper will provide technical references for future ecological re-operation of the cascade dams.


Author(s):  
Omid Bozorg-Haddad ◽  
Marzie Azad ◽  
Elahe Fallah-Mehdipour ◽  
Mohammad Delpasand ◽  
Xuefeng Chu

Abstract The optimal operation of reservoirs is known as a complex issue in water resources management, which requires consideration of numerous variables (such as downstream water demand and power generation). For this optimization, researchers have used evolutionary and meta-heuristic algorithms, which are generally inspired by nature. These algorithms have been developed to achieve optimal/near-optimal solutions by a smaller number of function evaluations with less calculation time. In this research, the flower pollination algorithm (FPA) was used to optimize: (1) Aidoghmoush single-reservoir system operation for agricultural water supply, (2) Bazoft single-reservoir system operation for hydropower generation, (3) multi-reservoir system operation of Karun 5, Karun 4, and Bazoft, and (4) Bazoft single-reservoir system for rule curve extraction. To demonstrate the effectiveness of the FPA, it was first applied to solve the mathematical test functions, and then used to determine optimal operations of the reservoir systems with the purposes of downstream water supply and hydropower generation. In addition, the FPA was compared with the particle swarm optimization (PSO) algorithm and the non-linear programming (NLP) method. The results for the Aidoghmoush single-reservoir system showed that the best FPA solution was similar to the NLP solution, while the best PSO solution was about 0.2% different from the NLP solution. The best values of the objective function of the PSO were approximately 3.5 times, 28%, and 43% worse than those of the FPA for the Bazoft single-reservoir system for hydropower generation, the multi-reservoir system, and the Bazoft single-reservoir system for rule curve extraction, respectively. The FPA outperformed the PSO in finding the optimal solutions. Overall, FPA is one of the new evolutionary algorithms, which is capable of determining better (closer to the ideal solution) objective functions, decreasing the calculation time, simplifying the problem, and providing better solutions for decision makers.


Water ◽  
2020 ◽  
Vol 12 (2) ◽  
pp. 504
Author(s):  
Jiqing Li ◽  
May Myat Moe Saw ◽  
Siyu Chen ◽  
Hongjie Yu

The short-term optimal operation model discussed in this paper uses the 2016 to 2018 daily and monthly data of Baluchaung II hydropower station to optimize power generation by minimizing water consumption effectively in order to get more revenue from optimal operation. In the first stage, run-off-river type Baluchaung II hydropower station data was applied in a mathematical model of equal micro-increment rate method for optimal hydropower generation flow distribution unit results. In the second stage, dynamic programming was used to get optimal hydropower generation unit distribution results. The resultant data indicated that optimized results can effectively guide the actual operation run of this power station. The purpose of the optimal load dispatching unit was to consider the optimal power of each unit for financial profit and numerical programming on the actual data of Baluchaung II hydropower plant to confirm that our methods are able to find good optimal solutions which satisfy the objective values of 17.75% in flow distribution units and 24.16% in load distribution units.


Proceedings ◽  
2018 ◽  
Vol 2 (11) ◽  
pp. 685
Author(s):  
Francesco Pugliese ◽  
Francesco De Paola ◽  
Nicola Fontana ◽  
Gustavo Marini ◽  
Maurizio Giugni

Pumps As Turbines (PATs) can be installed in Water Distribution Networks (WDNs) to couple pressure regulation and small-scale hydropower generation. The selection of PATs in WDNs needs proper knowledge about both the performances of machines available in the market and the operating conditions of the network. In this paper, a procedure for the preliminary selection of a PAT is proposed, based on the design of the main parameters (the head drop and the produced power at the Best Efficiency Point, the impeller diameter and the rotational speed) to both maximize the producible power and regulate the exceeding pressure.


2010 ◽  
Vol 7 (4) ◽  
pp. 4331-4369 ◽  
Author(s):  
Q. Goor ◽  
C. Halleux ◽  
Y. Mohamed ◽  
A. Tilmant

Abstract. The upper Blue Nile River Basin in Ethiopia is a largely untapped resource despite its huge potential for hydropower generation and irrigated agriculture. Controversies exist as to whether the numerous infrastructural development projects that are on the drawing board in Ethiopia will generate positive or negative externalities downstream in Sudan and Egypt. This study attempts at 1) examining the (re-)operation of infrastructures, in particular the proposed reservoirs in Ethiopia and the High Aswan Dam and 2) assessing the economic benefits and costs associated with the storage infrastructures in Ethiopia and their spatial and temporal distribution. To achieve this, a basin-wide integrated hydro-economic model has been developed. The model integrates essential hydrologic, economic and institutional components of the river basin in order to explore both the hydrologic and economic consequences of various policy options and planned infrastructural projects. Unlike most of the deterministic economic-hydrologic models reported in the literature, a stochastic programming formulation has been adopted in order to: i) understand the effect of the hydrologic uncertainty on management decisions, ii) determine allocation policies that naturally hedge against the hydrological risk, and iii) assess the relevant risk indicators. The study reveals that the development of four mega dams in the upper part of the Blue Nile Basin would change the drawdown refill cycle of the High Aswan Dam. Should the operation of the reservoirs be coordinated, they would enable an average annual saving of at least 2.5 billion m3 through reduced evaporation losses from the Lake Nasser. Moreover, the new reservoirs (Karadobi, Beko-Abo, Mandaya and Border) in Ethiopia would have significant positive impacts on hydropower generation and irrigation in Ethiopia and Sudan: at the basin scale, the annual energy generation is boosted by 38.5 TWh amongst which 14.2 TWh due to storage. Moreover, the regulation capacity of the above mentioned reservoirs would enable an increase of the Sudanese irrigated area by 5.5%.


Water ◽  
2021 ◽  
Vol 13 (19) ◽  
pp. 2753
Author(s):  
Hongya Qiu ◽  
Jianzhong Zhou ◽  
Lu Chen ◽  
Yuxin Zhu

Reasonable optimal operation policy for complex multiple reservoir systems is very important for the safe and efficient utilization of water resources. The operation policy of multiple hydropower reservoirs should be optimized to maximize total hydropower generation, while ensuring flood control safety by effective and efficient storage and release policy of multiple reservoirs. To achieve this goal, a new meta-heuristic algorithm, salp swarm algorithm (SSA), is used to optimize the joint operation of multiple hydropower reservoirs for the first time. SSA is a competitive bio-inspired optimizer, which has received substantial attention from researchers in a wide variety of applications in finance, engineering, and science because of its little controlling parameters and adaptive exploratory behavior. However, it still faces few drawbacks such as lack of exploitation and local optima stagnation, leading to a slow convergence rate. In order to tackle these problems, multiple strategies combining sine cosine operator, opposition-based learning mechanism, and elitism strategy are applied to the original SSA. The sine cosine operator is applied to balance the exploration and exploitation over the course of iteration; the opposition-based learning mechanism is used to enhance the diversity of the swarm; and the elitism strategy is adopted to find global optima. Then, the improved SSA (ISSA) is compared with six well-known meta-heuristic algorithms on 23 classical benchmark functions. The results obtained demonstrate that ISSA outperforms most of the well-known algorithms. Then, ISSA is applied to optimal operation of multiple hydropower reservoirs in the real world. A multiple reservoir system, namely Xiluodu Reservoir and Xiangjiaba Rservoir, in the upper Yangtze River of China are selected as a case study. The results obtained show that the ISSA is able to solve a real-world optimization problem with complex constraints. In addition, for the typical flood with a 100 return period in 1954, the maximum hydropower generation of multiple hydropower reservoirs is about 6671 GWh in the case of completing the flood control task, increasing by 1.18% and 1.77% than SSA and Particle Swarm Optimization (PSO), respectively. Thus, ISSA can be used as an alternative effective and efficient tool for the complex optimization of multiple hydropower reservoirs. The water resources in the river basin can be further utilized by the proposed method to cope with the increasingly serious climate change.


Water ◽  
2021 ◽  
Vol 13 (13) ◽  
pp. 1851
Author(s):  
Erfan Goharian ◽  
Mohammad Azizipour ◽  
Samuel Sandoval-Solis ◽  
Graham Fogg

While hydropower in California is one the main sources of renewable energy, population growth has continuously increased demand for energy. In addition, recent droughts reduced the amount of available water behind the hydropower dams to provide the water head needed to run the turbines in hydropower plants. A more sustainable alternative, instead of developing new infrastructure, is to enhance the daily operation of reservoirs to support hydropower generation. This study suggests a new optimal operation policy for Folsom Reservoir in California and hydropower plants, which maximizes hydropower generation and reduces flood risk. This study demonstrates the application of the cellular automata (CeA) approach to optimize the daily hydropower operation of Folsom Reservoir. The reservoir operation is a nonlinear problem, where the hydropower generation and elevation-area-storage functions are the main nonlinearity to accurately represent the daily operation of the system. Moreover, the performance of the CeA approach under two extreme climate conditions, wet and dry, was evaluated and compared to the operation during normal conditions. Results showed that the CeA approach provides more efficient solutions in comparison to the commonly used evolutionary optimization algorithms. For the size of the non-linear optimization problem designed in this study, CeA outperformed genetic algorithm for finding optimal solutions for different climate conditions. Results of CeA showed that although the annual average inflow to the reservoir during the dry period was about 30% less than the normal condition, CeA offered about a 20% reduction in average hydropower generation. The new operation policy offered by CeA can partly compensate for the loss of the snowpack in California’s Sierra Nevada under a warming climate. The approach and its outcomes support an informed decision-making process and provide practical reservoir operational guideline to remediate the adverse effects of hydroclimatic changes in the future.


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