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multi-objective optimal operation of a large deep reservoir during storage period considering the outflow-temperature demand based on NSGA-II

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JOURNAL OF HYDROLOGY 2020年 586卷 124919-124919页

作者： He, Wei Ma, Chao Zhang, Jian Lian, Jijian Wang, Shan Zhao, Wenlong Hohai Univ Coll Water Conservancy & Hydropower Engn Nanjing 210098 Peoples R China Tianjin Univ State Key Lab Hydraul Engn Simulat & Safety Tianjin 300072 Peoples R China

Thermal stratification occurs in deep reservoirs and causes an outflow temperature that is significantly different from the inflow temperature, which is harmful to the ecology of downstream reaches. optimal operation of reservoirs using the multi-objective evolutionary algorithm (MOEA), which focuses on power generation, flood control, agricultural irrigation, navigation, etc., has been performed. However, the outflow temperature has not been considered. Focusing on this deficiency, we considered Sanbanxi Reservoir as a case study and used the non-dominated sorting genetic algorithm II (NSGA-II) by combining it with the calibrated 1-D General Lake Model. The trade-off relationships among three objectives, namely, total power generation (TPG), root-meansquare deviation between the inflow and outflow temperatures (RMSDtem) and weighted aggregate eco-index (EI) based on indicators of hydrologic alteration (IHAs) parameters, were estimated as Pareto frontiers during the storage period from March 15 to July 15. The results demonstrated the following. 1) Through reservoir reoperation, RMSDtem could be reduced by 1.60 degrees C from 5.99 to 4.39 degrees C at the expense of reducing TPG from 7.43 x 10(8) to 6.56 x 10(8) *** (-11.8%) during a normal year. 2) The optimized operating schemes were extracted as Pareto frontiers, and the slope of the outflow discharge curve (SODC) could be a useful parameter for determining the operating scheme in practice. A large SODC yielded high TPG, a small SODC resulted in low RMSDtem, and a medium SODC yielded minimum EL The medium SODCs ranged from -0.1 to 0.4 m(3) /(s.d), -0.4 to 0.6 m(3)/(s.d), and -0.6 to 1.2 m(3)/(s.d) for dry, normal, and wet years, respectively. 3) As the yearly inflow increased, the absolute value of the SODC for the best individuals for a single objective became larger. The range of TPG and RMSDtem in the Pareto frontier expanded, and that of EI remained basically unchanged. The results of the Sanbanxi Reservoir

关键词： multi-objective optimal operation Non-dominated sorting genetic algorithm II Total power generation Root-mean-square deviation between the inflow and outflow temperatures Weighted aggregate eco-index based on IHA parameters Slope of the outflow discharge curve

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multi-objective optimal operation Incorporating Wind Power

Multi-objective Optimal Operation Incorporating Wind Power

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General Meeting of the IEEE-Power-and-Energy-Society (PES)

作者： Shi, L. B. Wang, C. Yao, L. Z. Ni, Y. X. Masoud, B. Tsinghua Univ Grad Sch Shenzhen Shenzhen 518055 Peoples R China

ISBN: (纸本)9781457710018

In this paper, a wind generation cost model reflecting the intermittency of wind power is proposed and integrated into a multi-objective optimal operation issue of power system. The proposed wind generation cost model is based on the frequency distribution of wind farm power output, which is obtained by applying Monte Carlo simulation to the wind speed model. Total 3 objectives involving minimization of power generation costs (inclusion of wind generation), minimization of pollution emissions and minimization of transmission losses as well as the small signal stability constraints are considered during modelling. An improved evolutionary algorithm called as self-adaptive evolutionary programming (SAEP) is employed to solve the multi-objective optimal operation problem with wind power incorporated. The IEEE New England test system is employed as benchmark to carry out the case studies. Numerical results illustrate the effectiveness and validity of the proposed model and method.

关键词： wind generation cost Monte Carlo simulation multi-objective optimal operation ideal point method self-adaptive evolutionary programming intermittency

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Application of a Novel Jaya Algorithm Based on Chaotic Sequence and Opposition-based Learning in the multi-objective optimal operation of Cascade Hydropower Stations System

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WATER RESOURCES MANAGEMENT 2021年第5期35卷 1397-1413页

作者： Wei, Yiming Dong, Zengchuan Hohai Univ Coll Hydrol & Water Resources Nanjing 210098 Peoples R China

The traditional operation of the cascade hydropower stations system (CHPS) mainly focus on the maximization of power generation benefits, but ignores the interference of CHPS operation to the river ecosystem, therefore, carrying out the multi-objective optimal operation (MOOP) of CHPS considering ecological demands is crucial. In this paper, a MOOP model considering the ecological objective is established. To effectively solve the MOOP problems, a novel multi-objective Jaya algorithm (MOCOM-Jaya) is proposed, where the quality of the initial population is enhanced based on the chaotic sequence, the later disturbance term and Gaussian mutation are incorporated to improve the local search ability, the elite opposition-based learning is adopted to broaden the optimization space. The proposed algorithm is applied to the study of MOOP of CHPS in the Wujiang river, and the results show that compared with MOPSO and NSGA-II, MOCOM-Jaya can gain the solution set with better convergence and distribution for the MOOP. The competition relationship between the power generation objective (PGO) and the ecological objective (ECO) is revealed based on the partial replacement ratio method. The results show that the competitiveness of PGO and ECO experienced a trade lead with the increase of power generation. The mean competitiveness ratios of PGO to ECO ( (CPRP-E)over-bar) in three typical years (dry, normal, wet) are 3.22, 3.17 and 3.15, indicating that the PGO is dominant in the competition with the ECO as a whole.

关键词： multi-objective optimal operation Cascade hydropower stations system multi-objective Jaya algorithm Ecological runoff process The partial replacement ratio

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Research on the multi-objective optimal operation of cascade reservoirs in the upper and middle Yellow River basin

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WATER SUPPLY 2019年第7期19卷 1918-1928页

作者： Bian, Jia-qi Dong, Zeng-chuan Jia, Yi-fei Zhong, Dun-yu Hohai Univ Dept Hydrol & Water Resources 1 Xikang Rd Nanjing Jiangsu Peoples R China

The reservoirs (hydro plants) along the upper Yellow River are typical cascade reservoirs, with multiple objectives regarding flood control, ice control, water supply, power generation, and ecological security. The competition among these multiple objectives reflects the competition among various agencies with different interests. There has been a certain degree of conflict between 'power scheduling', which aims at obtaining greater power generation from the cascade reservoirs, and 'water regulation', which is currently being implemented. Questions of how to reasonably use the comprehensive regulation capacity of the cascade reservoirs, in order to relieve the conflicts among multiple objectives, and understand the nature of the competition between 'power scheduling' and 'water regulation', require urgent research and solutions. Based on an analysis of the current situation regarding water supply, electricity demand, flood control, ice control, and ecology, a multi-objective optimal operation model for the cascade reservoirs in the upper and middle reaches of the Yellow River has been constructed to reveal the relationships between power generation and other objectives. This study provides theoretical evidence for the informed operation of the cascade reservoirs and will be of great significance for coordinating the relationship between power generation and water regulation.

关键词： Modified Progressive optimality Algorithm multi-objective optimal operation power generation water regulation Yellow River

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Synergistic gains from the multi-objective optimal operation of cascade reservoirs in the Upper Yellow River basin

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JOURNAL OF HYDROLOGY 2015年 523卷 758-767页

作者： Bai, Tao Chang, Jian-xia Chang, Fi-John Huang, Qiang Wang, Yi-min Chen, Guang-sheng Xian Univ Technol State Key Lab Base Ecohydraul Engn Arid Area Xian Shaan Xi Peoples R China Natl Taiwan Univ Dept Bioenvironm Syst Engn Taipei 10617 Taiwan

The Yellow River, known as China's "mother river", originates from the Qinghai-Tibet Plateau and flows through nine provinces with a basin area of 0.75 million km(2) and an annual runoff of 53.5 billion m(3). In the last decades, a series of reservoirs have been constructed and operated along the Upper Yellow River for hydropower generation, flood and ice control, and water resources management. However, these reservoirs are managed by different institutions, and the gains owing to the joint operation of reservoirs are neither clear nor recognized, which prohibits the applicability of reservoir joint operation. To inspire the incentive of joint operation, the contribution of reservoirs to joint operation needs to be quantified. This study investigates the synergistic gains from the optimal joint operation of two pivotal reservoirs (i.e., Longyangxia and Liujiaxia) along the Upper Yellow River. Synergistic gains of optimal joint operation are analyzed based on three scenarios: (1) neither reservoir participates in flow regulation;(2) one reservoir (i.e., Liujiaxia) participates in flow regulation;and (3) both reservoirs participate in flow regulation. We develop a multi-objective optimal operation model of cascade reservoirs by implementing the Progressive optimality Algorithm-Dynamic Programming Successive Approximation (POA-DPSA) method for estimating the gains of reservoirs based on long series data (1987-2010). The results demonstrate that the optimal joint operation of both reservoirs can increase the amount of hydropower generation to 1.307 billion kW h/year (about 594 million USD) and increase the amount of water supply to 36.57 billion m(3)/year (about 15% improvement). Furthermore both pivotal reservoirs play an extremely essential role to ensure the safety of downstream regions for ice and flood management, and to significantly increase the minimum flow in the Upper Yellow River during dry periods. Therefore, the synergistic gains of both reservoirs can be

关键词： Synergistic gains Cascade reservoirs multi-objective optimal operation Progressive optimality Algorithm-Dynamic Programming Successive Approximation (POA-DPSA)

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multi-objective operation of smart stand-alone microgrid with the optimal performance of customers to improve economic and technical indices

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JOURNAL OF ENERGY STORAGE 2020年 31卷

作者： Chamandoust, Heydar Bahramara, Salah Derakhshan, Ghasem Islamic Azad Univ Dept Elect Engn Damavand Branch Tehran Iran Islamic Azad Univ Dept Elect Engn Sanandaj Branch Sanandaj Iran

he operation problem of the Smart Stand-Alone Microgrids (SSAMGs) considering the economic and the tech-nical indices is investigated in many studies. The aim of the most studies is to meet the demand of the system with the minimum cost and high reliability considering the technical constraints of the system. In this paper, maximizing the RES penetration and improving the voltage profile of the system are modeled besides the minimization of the operation cost through a multi-objective optimization model. Moreover, the demand side management (DSM) strategies consisting of the demand shifting (DS) and the demand curtailing (DC) are employed in the decision-making problem of the SSAMGs to improve its economic and technical indices. To analysis the performance of the system, the battery bank (BB) lifetime and the peak-to-average ratio (PAR) indices are used. The resulted model is solved by the augmented epsilon-constraint approach in General Algebraic Modeling System (GAMS) optimization software environment. The best solution is selected using the fuzzy and the weight sum approaches. To investigate the effectiveness of the model and its solution methodology, it is applied on the IEEE 33-bus through defining four case studies. The results show the better performance of the objective functions in the presence of DSM strategies. Moreover, the PAR and the BB lifetime indices are improved when the DSM strategies are used in the SSAMGs to meet the demand.

关键词： multi-objective optimal operation Smart Stand-Alone Microgrid (SSAMG) Customer's participation Demand side management (DSM) Augmented epsilon-constraint approach

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multi-objective OPTIMIZATION OF TRANSFERABLE WATER FOR CASCADE RESERVOIRS IN THE UPPER YELLOW RIVER

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JOURNAL OF MARINE SCIENCE AND TECHNOLOGY-TAIWAN 2019年第5期27卷 392-403页

作者： Bai, Tao Zhang, Ming Liu, Xia Huang, Qiang Xian Univ Technol State Key Lab Ecohydraul Northwest Arid Reg China Xian 710048 Shaanxi Peoples R China

Artificially controlled floods generated by cascade reservoirs upstream have been applied to regulate the suspended river formed in the main stream of Ningxia-Inner Mongolia reach, China. The presence of sufficient transferable water in reservoirs is the most important limiting factor for the successful implementation of water and sediment regulation schemes. In this study, the conception and four modes of transferable water are proposed. Taking Longyangxia (LYX) and Liujiaxia (LJX) upper the Yellow River for example, a multi-objective optimal operation model of cascade reservoirs is established and solved by Feasible Search Space optimal Particle Swarm Optimization (FSSO-PSO). Based on long-term time series of transferable water results from the four modes, the most appropriate transferable water mode is recommended and the potential of water and sediment regulation by LYX and LJX is illustrated. The research findings have important practical significance for guiding the implementation of water and sediment regulation and provision of a scientific basis for decision makers

关键词： transferable water multi-objective optimal operation FSSO-PSO potential of water and sediment regulation

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A framework for adaptive control of multi-reservoir systems under changing environment

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JOURNAL OF CLEANER PRODUCTION 2021年 316卷 128304-128304页

作者： Zhang, Yu Yu, Lei Wu, Shiqiang Wu, Xiufeng Dai, Jiangyu Xue, Wanyun Yang, Qianqian Nanjing Hydraul Res Inst State Key Lab Hydrol Water Resources & Hydraul En Nanjing 210029 Peoples R China Hohai Univ Coll Water Conservancy & Hydropower Engn Nanjing 210098 Peoples R China

The changing environment has led to significant changes in the supply and demand of runoff, directly affecting the benefits of the multi-reservoir systems. Adaptive operation and quantitative control can hedge against the negative effects of changing environment for multi-reservoir systems, while studies related to the general theory and methods or models of such operations are inadequate. In this context, an adaptive control framework for multi-reservoir systems is proposed from a supply and demand perspective. Under this framework, a multiobjective optimal operation model is first established for adaptive control analysis, and the adaptive control measures based on supply-side, demand-side, and supply-demand linkage perspectives are designed. The effects of different control measures are further evaluated through scenario simulation analysis to recommend control schemes, using a multi-reservoir system in the Upper Yangtze River Basin of China as an example. The results suggest that the supply-demand linkage is an effective method to minimize the negative effects of changing environment on multi-reservoir systems, such as changes in runoff, increasing demands in water supply, population growth and socioeconomic development, etc. The proposed framework is shown to be feasible and effective in developing control measures for multi-reservoir systems to adapt to changing environments, which can provide a theoretical basis for the management of multi-reservoir systems under changing environments.

关键词： Changing environment Adaptive control multi-objective optimal operation multi-reservoir systems

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multi-objective Sustainable operation of the Three Gorges Cascaded Hydropower System Using multi-Swarm Comprehensive Learning Particle Swarm Optimization

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ENERGIES 2016年第6期9卷 438页

作者： Yu, Xiang Sun, Hui Wang, Hui Liu, Zuhan Zhao, Jia Zhou, Tianhui Qin, Hui Nanchang Inst Technol Prov Key Lab Water Informat Cooperat Sensing & In 289 Tianxiang Rd Nanchang 330099 Jiangxi Peoples R China State Grid Jiangxi Power Corp Econ Res Inst 1588 Yingbinbei Rd Nanchang 330043 Jiangxi Peoples R China Huazhong Univ Sci & Technol Sch Hydropower & Informat Engn 1037 Luoyu Rd Wuhan 430074 Hubei Peoples R China

optimal operation of hydropower reservoir systems often needs to optimize multiple conflicting objectives simultaneously. The conflicting objectives result in a Pareto front, which is a set of non-dominated solutions. Non-dominated solutions cannot outperform each other on all the objectives. An optimization framework based on the multi-swarm comprehensive learning particle swarm optimization algorithm is proposed to solve the multi-objective operation of hydropower reservoir systems. Through adopting search techniques such as decomposition, mutation and differential evolution, the algorithm tries to derive multiple non-dominated solutions reasonably distributed over the true Pareto front in one single run, thereby facilitating determining the final tradeoff. The long-term sustainable planning of the Three Gorges cascaded hydropower system consisting of the Three Gorges Dam and Gezhouba Dam located on the Yangtze River in China is studied. Two conflicting objectives, i.e., maximizing hydropower generation and minimizing deviation from the outflow lower target to realize the system's economic, environmental and social benefits during the drought season, are optimized simultaneously. Experimental results demonstrate that the optimization framework helps to robustly derive multiple feasible non-dominated solutions with satisfactory convergence, diversity and extremity in one single run for the case studied.

关键词： multi-objective optimal operation hydropower reservoir system particle swarm optimization multi-swarm comprehensive learning

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multi-objective Ecological Long-Term operation of Cascade Reservoirs Considering Hydrological Regime Alteration

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WATER 2024年第13期16卷 1849页

作者： Xu, Changjiang Zhu, Di Guo, Wei Ouyang, Shuo Li, Liping Bu, Hui Wang, Lin Zuo, Jian Chen, Junhong Changjiang Water Resources Commiss Bur Hydrol Wuhan 430010 Peoples R China Guilin Univ Technol Guangxi Key Lab Theory & Technol Environm Pollut C Guilin 541006 Peoples R China Guilin Univ Technol Collaborat Innovat Ctr Water Pollut Control & Wate Guilin 541006 Peoples R China

Constructing and operating cascade reservoirs significantly contribute to comprehensive basin water resource management, while altering natural hydrological regimes of rivers, which imposes negative impacts on riverine ecology. The main aim of this study is to synergistically optimize the objectives of increasing hydropower generation and alleviating hydrological regime alteration for cascade reservoirs. This study first proposed a dynamic time warping scenario backward reduction (DTW-SBR) framework to extract streamflow scenarios from the historical streamflow series regarded as benchmarks for calculating deviation degrees of hydrological regimes. Then a multi-objective long-term operation model considering the hydrological regime and hydroelectricity was formed for minimizing the deviation degrees of hydrological regimes at the downstream section (O1) and maximizing the hydropower generation of cascade reservoirs (O2). The non-dominated sorting genetic algorithm-II (NSGA-II) combined with the long-term conventional operation (CO) rules of cascade reservoirs was adopted to produce the Pareto-front solutions to derive the recommended policies for guiding the long-term operation of cascade reservoirs. The six large reservoirs in the middle reaches of the Jinsha River, China with a 10-day runoff dataset spanning from 1953 to 2015 constitute a case study. The results showed that nine streamflow scenarios were extracted for calculating the O1 by the DTW-SBR framework, which could reflect the intra- and inter- annual variability of hydrological regimes at the Panzhihua hydrological station. The Pareto-front solutions obtained by the NSGA-II revealed competitive relationships between the O1 and O2. As compared to the long-term CO rules of cascade reservoirs, the O1 value could be reduced by up to 42,312 (corresponding rate of 10.51%) and the O2 value could be improved by up to 1752 x 108 kWh (corresponding rate of 5.14%). Based on the inclination to be dominat

关键词： hydropower generation hydrological regime DTW-SBR framework cascade reservoirs multi-objective optimal operation

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