Multi-objective optimization for integrated hydro–photovoltaic power system

Li, Fang‐Fang; Qiu, Jun

doi:10.1016/j.apenergy.2015.09.018

Cited by 210 publications

(72 citation statements)

References 20 publications

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“…2 there is no stages to release water in advance in the non-flood season, and the reservoir operation is maintained at the normal water level.…”

Section: Basic Data and Regularity Of The Optimal Sample Datamentioning

confidence: 99%

“…For any combination at the beginning of this stage, such as combination (2,3,3), which, respectively, represents a discretized point for upstream, midstream, and downstream reservoir, as shown in Figure 1a, with the solid line circle, we can find out the optimal candidate path that corresponds to combination (2,3,3) by traversing all M 3 combinations of the storage volume at the end of this stage. Assuming that it is the combination (3, M, 2), as shown in Figure 1a with the dotted line circle, and then save the optimal candidate path and the cumulative output of combination (2,3,3) in the memory for the usage of next stage.…”

Section: Calculation Procedures Of Mdpmentioning

confidence: 99%

“…Step 3: Repeats step 2, then the calculation of stage T − 1 can be finished by implementing the same work for the other M 3 -1 combinations of the storage volume at the beginning of this stage, except for combination (2,3,3).…”

Section: Calculation Procedures Of Mdpmentioning

confidence: 99%

“…It has exceptional advantages when compared with other energy sources [2,3], such as pollution-free, renewable, manageable, and so on. Moreover, hydropower has the unique ability to change the output quite fast, which makes it good at meeting the changing demands for electricity.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Studying Operation Rules of Cascade Reservoirs Based on Multi-Dimensional Dynamics Programming

Jiang

Qin

et al. 2017

Water

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Abstract:Although many optimization models and methods are applied to the optimization of reservoir operation at present, the optimal operation decision that is made through these models and methods is just a retrospective review. Due to the limitation of hydrological prediction accuracy, it is practical and feasible to obtain the suboptimal or satisfactory solution by the established operation rules in the actual reservoir operation, especially for the mid-and long-term operation. In order to obtain the optimized sample data with global optimality; and make the extracted operation rules more reasonable and reliable, this paper presents the multi-dimensional dynamic programming model of the optimal joint operation of cascade reservoirs and provides the corresponding recursive equation and the specific solving steps. Taking Li Xianjiang cascade reservoirs as a case study, seven uncertain problems in the whole operation period of the cascade reservoirs are summarized after a detailed analysis to the obtained optimal sample data, and two sub-models are put forward to solve these uncertain problems. Finally, by dividing the whole operation period into four characteristic sections, this paper extracts the operation rules of each reservoir for each section respectively. When compared the simulation results of the extracted operation rules with the conventional joint operation method; the result indicates that the power generation of the obtained rules has a certain degree of improvement both in inspection years and typical years (i.e., wet year; normal year and dry year). So, the rationality and effectiveness of the extracted operation rules are verified by the comparative analysis.

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“…2 there is no stages to release water in advance in the non-flood season, and the reservoir operation is maintained at the normal water level.…”

Section: Basic Data and Regularity Of The Optimal Sample Datamentioning

confidence: 99%

Section: Calculation Procedures Of Mdpmentioning

confidence: 99%

Section: Calculation Procedures Of Mdpmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Studying Operation Rules of Cascade Reservoirs Based on Multi-Dimensional Dynamics Programming

Jiang

Qin

et al. 2017

Water

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show abstract

“…So, it is very necessary to solve the CROO problem correctly and reasonably. However, CROO is a multivariate coupled and complicated nonlinear programming problem [9], which needs to consider not only the hydraulic connection between upstream and downstream reservoirs, but also a lot of constraints. It has the characteristics of high dimensionality, strong coupling, and uncertainty [10][11][12], and its solution is full of difficulties and has always been the focus of many scholars' research [13].…”

Section: Introductionmentioning

confidence: 99%

Two Dimension Reduction Methods for Multi-Dimensional Dynamic Programming and Its Application in Cascade Reservoirs Operation Optimization

Jiang

Hui

et al. 2017

Water

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An efficient reservoir operation technique plays a very important role in improving the water resources and energy efficiency of reservoirs. In order to effectively avoid or alleviate the "curse of dimensionality" of Multi-dimensional Dynamic Programming (MDP) in the application of cascade reservoirs operation optimization (CROO) and keep a global convergence at the same time, two dimension reduction methods are proposed in this paper. One is a hybrid algorithm of MDP and a Progressive Optimality Algorithm (POA), named MDP-POA, which combines the global convergence of MDP and the strong local search ability of POA. MDP-POA first takes the global optimal trajectory of MDP in a low discrete degree as the initial trajectory of the POA, and then implements further optimization to the obtained initial trajectory by the POA with a high discrete degree, so as to avoid the "curse of dimensionality" of MDP in high discrete degree and the dependency of the POA for the initial trajectory. The other is an improved MDP (IMDP), which first constructs a corridor by the optimal trajectory of MDP in a lower discrete degree, and then implements further optimization in the corridor by MDP with a relatively high discrete degree, so as to avoid a large number of unnecessary calculations, and shorten the run-time effectively. In a case study, the results of MDP-POA, IMDP, and MDP are compared and analyzed from the aspects of power generation and run-time. The analysis indicates that the proposed MDP-POA and IMDP both have a good application effect and are worthy of further promotion.

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Optimal dispatch using moth‐flame optimization for hydro‐thermal‐wind scheduling problem

Hazra

Roy

2020

Int Trans Electr Energ Syst

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A proficient algorithm, based on the moth‐flame optimization (MFO), is founded for solving economic and emission dispatch for hydro‐thermal‐wind (HTW) scheduling problem. The renewable wind power associated with hydropower‐integrated thermal power plant is a non‐linear, non‐convex optimization problem due to water discharge rate, hydraulic continuity constraint, reservoir storage limits, variable wind speed, scheduling time linkage, water transport delay, power balance constraints, as well as operation limits of renewable wind units. A renewable wind power‐oriented multi‐objective hydro‐thermal scheduling has significant value to trim down the power generation cost and emission. The usefulness of the projected method is verified on two case studies. In the most recent literature, the statistical outcomes of the applied MFO algorithm are compared with others evolutionary optimization. It is also observed that the proposed MFO method is skillful for developing hopeful outcomes and for significantly reducing the computation time.

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Multi-objective optimization for integrated hydro–photovoltaic power system

Cited by 210 publications

References 20 publications

Studying Operation Rules of Cascade Reservoirs Based on Multi-Dimensional Dynamics Programming

Studying Operation Rules of Cascade Reservoirs Based on Multi-Dimensional Dynamics Programming

Two Dimension Reduction Methods for Multi-Dimensional Dynamic Programming and Its Application in Cascade Reservoirs Operation Optimization

Optimal dispatch using moth‐flame optimization for hydro‐thermal‐wind scheduling problem

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