A model for optimal scheduling of hydro thermal systems including pumped‐storage and wind power

Helseth, Arild; Gjelsvik, Anders; Mo, Birger; Linnet, Úlfar

doi:10.1049/iet-gtd.2012.0639

Cited by 79 publications

(48 citation statements)

References 26 publications

(47 reference statements)

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“…It should be noted that penalty variables are used to avoid infeasible solutions and, thus, assure relatively complete recourse. Other features, such as power flow constraints and linearized start-up costs on thermal units, can, e.g., be modeled as in [9].…”

Section: The Weekly Decision Problemmentioning

confidence: 99%

Efficient Parallelization of the Stochastic Dual Dynamic Programming Algorithm Applied to Hydropower Scheduling

Helseth

Braaten

2015

Energies

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Stochastic dual dynamic programming (SDDP) has become a popular algorithm used in practical long-term scheduling of hydropower systems. The SDDP algorithm is computationally demanding, but can be designed to take advantage of parallel processing. This paper presents a novel parallel scheme for the SDDP algorithm, where the stage-wise synchronization point traditionally used in the backward iteration of the SDDP algorithm is partially relaxed. The proposed scheme was tested on a realistic model of a Norwegian water course, proving that the synchronization point relaxation significantly improves parallel efficiency.

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Section: The Weekly Decision Problemmentioning

confidence: 99%

Efficient Parallelization of the Stochastic Dual Dynamic Programming Algorithm Applied to Hydropower Scheduling

Helseth

Braaten

2015

Energies

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“…The effectiveness of the pumped hydro storage (PHS) for consuming surplus wind power was verified in [8][9][10]. Cost-optimal capacity of the PHS was studied in [11,12], a simulation platform was designed for optimizing the PHS capacity.…”

Section: Introductionmentioning

confidence: 99%

Comparative Study of Electric Energy Storages and Thermal Energy Auxiliaries for Improving Wind Power Integration in the Cogeneration System

Chen

Lei

2018

Energies

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Abstract:In regards to the cogeneration system in Northern China, mainly supported by combined heat and power (CHP) plants, it usually offers limited operation flexibility due to the joint production of electric and thermal power. For that large-scale wind farms included in the cogeneration system, a large amount of wind energy may have to be wasted. To solve this issue, the utilization of the electric energy storages and the thermal energy auxiliaries are recommended, including pumped hydro storage (PHS), compressed air energy storage (CAES), hydrogen-based energy storage (HES), heat storage (HS), electric boilers (EB), and heat pumps (HP). This paper proposes a general evaluation method to compare the performance of these six different approaches for promoting wind power integration. In consideration of saving coal consumption, reducing CO 2 emissions, and increasing investment cost, the comprehensive benefit is defined as the evaluation index. Specifically, a wind-thermal conflicting expression (WTCE) is put forward to simplify the formulation of the comprehensive benefit. Further, according to the cogeneration system of the West Inner Mongolia (WIM) power grid, a test system is modelled to perform the comparison of the six different approaches. The results show that introducing the electric energy storages and the thermal energy auxiliaries can both contribute to facilitating wind power integration, and the HP can provide the best comprehensive benefit.

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“…To consider the seasonal character and uncertainty of reservoir inflow, a composite optimization model was presented in [9]. A stochastic model with consideration of random water inflow and price errors was described by scenarios in [10]. And an energy equivalent reservoir model [11] was applied to the stochastic optimization of hydropower production decisions in the Brazilian power system.…”

Section: Introductionmentioning

confidence: 99%

An efficient stochastic algorithm for mid-term scheduling of cascaded hydro systems

Xia

Lee

2018

J. Mod. Power Syst. Clean Energy

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Due to the stochastic and correlated attributes of natural inflows, the mid-term generation scheduling problem for cascaded hydro systems is a very challenging issue. This paper proposes a novel stochastic optimization algorithm using Latin hypercube sampling and Cholesky decomposition combined with scenario bundling and sensitivity analysis (LC-SB-SA) to address this problem. To deal with the uncertainty of natural inflows, Latin hypercube sampling is implemented to provide an adequate number of sampling scenarios efficiently, and Cholesky decomposition is introduced to describe the correlated natural inflows among cascaded stations. In addition, to overcome the difficulties in solving the objectives of all the scenarios, scenario bundling and sensitivity analysis algorithms are developed to improve the computational efficiency. Simulation results from both two-station and tenstation systems indicate that the proposed method has the merits in accuracy as well as calculation speed for the midterm cascaded hydro generation scheduling. The consideration of natural inflow correlation makes the formulated problem more realistic.

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A model for optimal scheduling of hydro thermal systems including pumped‐storage and wind power

Cited by 79 publications

References 26 publications

Efficient Parallelization of the Stochastic Dual Dynamic Programming Algorithm Applied to Hydropower Scheduling

Efficient Parallelization of the Stochastic Dual Dynamic Programming Algorithm Applied to Hydropower Scheduling

Comparative Study of Electric Energy Storages and Thermal Energy Auxiliaries for Improving Wind Power Integration in the Cogeneration System

An efficient stochastic algorithm for mid-term scheduling of cascaded hydro systems

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