An overview on formulations and optimization methods for the unit-based short-term hydro scheduling problem

Kong, Jiehong; Skjelbred, Hans Ivar; Fosso, Olav Bjarte

doi:10.1016/j.epsr.2019.106027

Cited by 85 publications

(35 citation statements)

References 79 publications

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“…The STHTS problem has been extensively investigated by researchers for decades, see e.g. the recent reviews in [5], [21] and references therein. From a mathematical point of view, the problem can be characterized as a combinatorial, nonlinear and nonconvex.…”

Section: A Literature Reviewmentioning

confidence: 99%

“…Short-term hydrothermal scheduling (STHTS) models typically have a time-horizon of a few weeks or shorter, with targets or strategies for reservoir operation obtained from the longer-term models. This allows the representation of more details, such as exact unit commitment, and nonconvex hydropower generation functions [5], [6]. Although the level of details provided in the short-term scheduling is needed to provide realistic operational schedules, such details are often neglected in the longer-term models to reduce the computational effort.…”

Section: Introductionmentioning

confidence: 99%

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Convex Relaxations of the Short-Term Hydrothermal Scheduling Problem

Helseth

Jaehnert

Diniz

2021

IEEE Trans. Power Syst.

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Section: A Literature Reviewmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Convex Relaxations of the Short-Term Hydrothermal Scheduling Problem

Helseth

Jaehnert

Diniz

2021

IEEE Trans. Power Syst.

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“…(1) Identify the trends in the local inflow sample data First, we must determine whether the local inflow sample data before t now display a specific frequency fluctuation. This problem can be addressed by using the autocorrelation coefficient in statistics, as given by formula (11), as shown at the end of the next page. where A is the length of the local inflow sample set; t α 0 and t β 0 are the start periods of local inflow sample sets α and β, respectively, as shown in Fig.…”

Section: ) Forecasting the Local Inflow Of The Nonfirst-stage Cascadmentioning

confidence: 99%

“…Many scholars have studied short-term scheduling and produced many innovative research results, such as peak-shaving scheduling [1]- [5], maximizing the total benefit [6]- [8], and minimizing the total fuel cost [9], [10]. However, due to the large number of HPs, useful forecasting information is limited, the forecasting accuracy is low, large and complex constraint sets are needed, and dimensionality issues can occur [11]- [13]; as a result, the current theoretical approach faces considerable challenges in terms of practicality, universality, and computational efficiency. There is still considerable difference between short-term scheduling schemes and the real scheduling process.…”

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confidence: 99%

Ultrashort-Term Scheduling of Interbasin Cascaded Hydropower Plants to Rapidly Balance the Load Demand

et al. 2020

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The short-term scheduling schemes of cascaded hydropower plants are based on day-ahead hydrological forecasting information. Affected by the accuracy of prediction, real-term hydrological information can considerably vary from previously forecasted values, especially for the power load and local inflows. As a result, short-term scheduling schemes are difficult to apply directly in real-time scheduling. To solve this problem, a rolling optimal hourly operation model for interbasin cascaded hydropower plants is proposed to rapidly balance the load demand. The model is deemed an ultrashort-term model, and it has a short-cycle schedule between short-term and real-time schemes. The basic strategy of solving the model is as follows. First, the day-ahead power load and local inflow information are corrected using a statistical method based on the most recent real-time information. Second, the water delay time, defined as the time between when water is released from upstream reservoirs and arrives at downstream reservoirs, is updated based on the most recent real-time information. Third, a heuristic method is proposed to dynamically update the short-term scheduling scheme over the next few hours. The objective is to minimize the maximum relative deviation between the actual water level of a reservoir at the end of 24 hours and the day-ahead forecasted value. This approach can keep the reservoir water level at the end of 24 hours close to the forecasted value and improve the accuracy of estimating the initial water level the next day. The developed method is applied to solve an ultrashort-term scheduling problem involving the cascaded hydropower plants located in Yunnan Province, China. The results indicate that the proposed model can achieve seamless coupling between shortterm scheduling and real-time scheduling. The proposed method can provide a scientific basis for the realtime dispatching of large-scale hydropower plants and improve the practicality of short-term dispatching schemes. INDEX TERMS Ultrashort term, water delay time, cascaded hydropower plants, real-time scheduling, optimal scheduling. NOMENCLATURE The notations used in the mathematical model of hydropower operation are given as follows. A. SETS M Set of reservoirs or hydropower plants (HPs) M 2 Set of HPs that can increase power generation M 3 Set of HPs that can reduce their power generation The associate editor coordinating the review of this manuscript and approving it for publication was Zhiyi Li .

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“…The optimal operation of a hydropower station is to generate load with many constraints for many purposes [2]. There are many algorithms for mathematical models to optimize operation with correctly conceptualized theories and formulas [3].…”

Section: Introductionmentioning

confidence: 99%

Short-Term Optimal Operation of Baluchaung II Hydropower Plant in Myanmar

Saw

Chen

2020

Water

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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.

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An overview on formulations and optimization methods for the unit-based short-term hydro scheduling problem

Cited by 85 publications

References 79 publications

Convex Relaxations of the Short-Term Hydrothermal Scheduling Problem

Convex Relaxations of the Short-Term Hydrothermal Scheduling Problem

Ultrashort-Term Scheduling of Interbasin Cascaded Hydropower Plants to Rapidly Balance the Load Demand

Short-Term Optimal Operation of Baluchaung II Hydropower Plant in Myanmar

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