Optimizing Hydrothermal Scheduling with Non-Convex Irrigation Constraints: Case on the Chilean Electricity System

Pereira-Bonvallet, Eduardo; Puschel-Lovengreen, Sebastian; Matus, Marcelo; Moreno, Rodrigo

doi:10.1016/j.egypro.2015.12.342

Cited by 20 publications

(16 citation statements)

References 9 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Other environmental constraints involve statedependencies which are not easily treated in the SDDP algorithm, see e.g. [13]. The main complicating factor is the nonconvexities associated with such constraints.…”

Section: Introductionmentioning

confidence: 99%

Nonconvex Environmental Constraints in Hydropower Scheduling

Helseth

Hågenvik

2020

2020 International Conference on Probabilistic Methods Applied to Power Systems (PMAPS)

View full text Add to dashboard Cite

Environmental constraints in hydropower systems serve to ensure sustainable use of water resources. Through accurate treatment in hydropower scheduling, one seeks to respect such constraints in the planning phase while optimizing the utilization of hydropower. However, many environmental constraints introduce state-dependencies and even nonconvexities to the scheduling problem, making them challenging to capture. This paper describes how the recently developed stochastic dual dynamic integer programming (SDDiP) method can incorporate nonconvex environmental constraints in the medium-and longterm scheduling of a hydropower system in a liberalized market context. A mathematical model is presented and tested in a multireservoir case study, emphasizing on the improvements observed when accurately modelling a particular type of nonconvex environmental constraint.

show abstract

Section: Introductionmentioning

confidence: 99%

Nonconvex Environmental Constraints in Hydropower Scheduling

Helseth

Hågenvik

2020

2020 International Conference on Probabilistic Methods Applied to Power Systems (PMAPS)

View full text Add to dashboard Cite

show abstract

“…Approaches to convexify the hydropower production function within the longterm models are presented in [23]- [25]. Other examples of nonconvexities are due to irrigation [26] and river level and river-routing constraints [27].…”

Section: A Literature Reviewmentioning

confidence: 99%

“…In addition to (7), ramp-up and ramp-down limits, startup and shut-down ramp limits and minimum up and downtime constraints were modeled following the equations (16)- (26) in [38] (Section II B). We do not explicitly state these equations here for brevity.…”

Section: Thermal Constraintsmentioning

confidence: 99%

Convex Relaxations of the Short-Term Hydrothermal Scheduling Problem

Helseth

Jaehnert

Diniz

2021

IEEE Trans. Power Syst.

View full text Add to dashboard Cite

“…When (and if) the storage volume in the reservoir reach the predefined threshold, the constraint changes into a minimum reservoir level constraint. This can be imposed by (17) and (18). ( 17) is active for the first week the storage volume in the reservoir reach the wanted threshold (in t C ), while (18) becomes active from the following week.…”

Section: B Activation Of the Environmental Regulationmentioning

confidence: 99%

“…Nonconvex problem formulations are typically needed to represent the complex interaction between power output and water [12], and unit commitment of generators [13]. The challenge of representing nonconvex relationships in the SDDP algorithm has frequently been addressed in the literature by the use of approximations, e.g [14]- [17]. A few studies also consider accurate modelling of non-convexities by the use of SDP [18] or stochastic dual dynamic integer programming (SDDiP), such as in [19] and [20].…”

Section: Introductionmentioning

confidence: 99%

A Stochastic Dynamic Programming Model for Hydropower Scheduling with State-dependent Maximum Discharge Constraints

Schäffer¹,

Helseth²,

Korpås³

2021

Preprint

View full text Add to dashboard Cite

<div>We present a medium-term hydropower scheduling model that includes state-dependent environmental constraints on maximum discharge. A stochastic dynamic programming algorithm is used to enable modelling of nonconvex relationships in the problem formulation. The model is applied in a case study of a Norwegian hydropower system with multiple reservoirs. We find that the maximum discharge constraint significantly impacts the water values and simulated operation of the hydropower system. A main finding is that the nonconvex characteristics of the environmental constraint is reflected in the water values, implying a nonconvex objective function. Operation according to the computed water values is simulated for cases with and without the environmental constraint. Even though operation of the system changes considerably when the environmental constraint is included, the total electricity generation over the year is kept constant, and the total loss in expected profit limited to less than 0.8%.</div>

show abstract

Optimizing Hydrothermal Scheduling with Non-Convex Irrigation Constraints: Case on the Chilean Electricity System

Cited by 20 publications

References 9 publications

Nonconvex Environmental Constraints in Hydropower Scheduling

Nonconvex Environmental Constraints in Hydropower Scheduling

Convex Relaxations of the Short-Term Hydrothermal Scheduling Problem

A Stochastic Dynamic Programming Model for Hydropower Scheduling with State-dependent Maximum Discharge Constraints

Contact Info

Product

Resources

About