Convex Relaxations of the Short-Term Hydrothermal Scheduling Problem

Helseth, Arild; Jaehnert, Stefan; Diniz, André Luiz

doi:10.1109/tpwrs.2020.3047346

Cited by 13 publications

(5 citation statements)

References 39 publications

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“…This is the author's version which has not been fully edited and content may change prior to final publication. Citation information: DOI 10.1109/ACCESS.2024.3364099 displacement of each parameter and M(L) is the movement rate of water in the hydro unit, and M(T) is the movement rate of power spinning in the thermal unit and it is denoted in equation (24,25) as: 𝑴(𝑳) = 𝑺 𝒓𝒂𝒕𝒆 * 𝒓𝒂𝒏𝒅 (𝟎, 𝟏) + 𝑴(𝑺 𝒃𝒆𝒔𝒕 ) (24) 𝑴(𝑻) = 𝑰 𝒓𝒂𝒕𝒆 * 𝒓𝒂𝒏𝒅 (𝟎, 𝟏) + 𝑴(𝑰 𝒃𝒆𝒔𝒕 ) (25) Hence, the exploitation stage is built on the presumption that the allowable water flow as well as power generation either stays within a distance of zero or is displaced within a range that does not exceed Srate, where Srate stands for shortdistance movement. The fact that the allowable water flow as well as power generation outside of the typical neighborhood range Irate serves as the basis for the exploration phase.…”

Section: Enhanced Ebola Optimization Search Algorithmmentioning

confidence: 99%

“…The adaptive and variable local and global search coefficients greatly improve the suggested APSO's performance in finding the best solution. Helseth et al [25] proposed Convex Relaxations of the Short-Term Hydrothermal Scheduling Problem. Starting as a mixedinteger programming problem, it is approximated by employing Lagrangian and linear relaxation techniques.…”

Section: Introductionmentioning

confidence: 99%

“…From aforementioned literature, it is found that computation capacity and execution time is increased in [16], [17] breaks equality requirements while changing the violated dependent variables, [18] slows multimodal optimization convergence, in [19] swarm does not coalesce to a single spot, [21] cannot determine optimal scheduling, [22] does not address the objective function properly, in [23] algorithm is highly complex, [24] ignores social and cognitive factors for the PSO technique while [25] takes more computational time. The Hamilton and Egarch algorithm is a computational approach for optimizing the control of water flow in hydraulic systems based on certain criteria and constraints [26][27].…”

Section: Introductionmentioning

confidence: 99%

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A Novel Hybrid Approach for Hydrothermal Scheduling Using Mathematical and Metaheuristic Search Methods

Mundotiya,

Tiwari,

Alotaibi

et al. 2024

IEEE Access

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Hydrothermal scheduling is a significant concern in the field of power system economics that seeks to reduce the overall cost of generation by optimizing the hourly output of generators. However, this scheduling process suffers from a non-linear and complex problem due to set of uncertainty constraints from hydro and thermal units. Hence ϑ-constraint method has been proposed in which ramp constraints are considered that supply a feasible power region of the thermal units and minimize the uncertainty constraints. In addition, the existing solution techniques of hydro and thermal unit, commitment problems have not considered thermal constraints and their losses. This results in the frequent swapping of hydro units which decreases the energy conversion efficiency by a percentage at each repetition and increases the cost of the system. Therefore, a novel Chaotic geometric programming and chaotic approximation approach has been proposed that balance water discharge level without frequency swapping based on Armijo's rule and Hazen Williams's rule. Further, dynamic indexing is performed to increase the energy conversion efficiency. These balanced values are given to multiple-wave neural networks, to solve the hydro and thermal unit commitment problems. Furthermore, the cost of the system is minimized using Enhanced Ebola Optimization Search (EEOS) Algorithm in which the Srate parameter has been modified, thereby normalizing the hydrothermal scheduling problem for matured convergence. The proposed mathematical model has been implemented in the MATLAB simulator and the results obtained show better performance than the previous approaches in terms of mean, median and standard deviation.

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Section: Enhanced Ebola Optimization Search Algorithmmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

A Novel Hybrid Approach for Hydrothermal Scheduling Using Mathematical and Metaheuristic Search Methods

Mundotiya,

Tiwari,

Alotaibi

et al. 2024

IEEE Access

View full text Add to dashboard Cite

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“…Note that the spatial decomposition provided by coordinating solutions of ( 5) and ( 6) by feasibility cuts (9) has similarities to Lagrangian Relaxation techniques frequently proposed in the literature for solving the hydrothermal scheduling problem [39]. However, it is not necessary to solve (6) for each time ( 5) is solved within the SDDP algorithm.…”

Section: Feasibility Cutsmentioning

confidence: 99%

Hydropower Aggregation by Spatial Decomposition—An SDDP Approach

Helseth

2023

IEEE Trans. Sustain. Energy

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The balance between detailed technical description, representation of uncertainty and computational complexity is central in long-term scheduling models applied to hydro-dominated power system. The aggregation of complex hydropower systems into equivalent energy representations (EER) is a commonly used technique to reduce dimensionality and computation time in scheduling models. This work presents a method for coordinating the EERs with their detailed hydropower system representation within a model based on stochastic dual dynamic programming (SDDP). SDDP is applied to an EER representation of the hydropower system, where feasibility cuts derived from optimization of the detailed hydropower are used to constrain the flexibility of the EERs. These cuts can be computed either before or during the execution of the SDDP algorithm and allow system details to be captured within the SDDP strategies without compromising the convergence rate and statespace dimensionality. Results in terms of computational performance and system operation are reported from a test system comprising realistic hydropower watercourses.

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“…In contrast, ref. [16] uses a similar plant-based aggregation to [9], but tackles the problem via Lagrangian relaxation. Consequently, all forbidden zones were neglected.…”

Section: Introductionmentioning

confidence: 99%

Hydrothermal Unit-Commitment Problem of a Large-Scale System with Representation of Forbidden Zones

2021

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As we move towards electrical networks with a growing presence of renewable generation, the representation of the electrical components becomes more important. In hydro-dominated power systems, modelling the forbidden zones of hydro plants becomes increasingly challenging as the number of plants increases. Such zones are ranges of generation that either should be avoided or are altogether unreachable. However, because representing the forbidden zones introduces a substantial computational burden, hydrothermal unit-commitment problems (HTUC) for large systems are usually formulated ignoring the forbidden zones. Nonetheless, this simplification may demand adjustments to the solution of the HTUC, because the generation of the hydro stations may fall in forbidden zones. In practice, the adjustments are usually performed based on the experience of system operators and, then, can be far from an optimal correction. In this paper, we study the impact of explicitly representing the hydro-generation forbidden zones in a large-scale system with more than 7000 buses, 10,000 lines, and 700 hydro units. Our findings show that the simplified model that is current used can deviate significantly from the model with forbidden zones, both in terms of the generation of hydro plants, as well as the generation of thermal plants and the system marginal costs.

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Convex Relaxations of the Short-Term Hydrothermal Scheduling Problem

Cited by 13 publications

References 39 publications

A Novel Hybrid Approach for Hydrothermal Scheduling Using Mathematical and Metaheuristic Search Methods

A Novel Hybrid Approach for Hydrothermal Scheduling Using Mathematical and Metaheuristic Search Methods

Hydropower Aggregation by Spatial Decomposition—An SDDP Approach

Hydrothermal Unit-Commitment Problem of a Large-Scale System with Representation of Forbidden Zones

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