Joint optimization of regional water-power systems

Pereira-Cardenal, Silvio; Mo, Birger; Gjelsvik, Anders; Riegels, Niels; Arnbjerg‐Nielsen, Karsten; Bauer‐Gottwein, Peter

doi:10.1016/j.advwatres.2016.04.004

Cited by 46 publications

(26 citation statements)

References 20 publications

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“…SDDP has largely been used in hydropower‐dominated systems such as Norway (Gjelsvik et al, ; Mo et al, ; Rotting & Gjelsvik, ), South and Central America (Homen‐de Mello et al, ; Pereira, ; Shapiro et al, ), and New Zealand (Kristiansen, ). The SDDP algorithm constitutes the core of generic hydro‐economic models that have been used to analyze a variety of policy issues in the Euphrates‐Tigris River basin (Tilmant et al, ), the Nile River basin (Goor et al, ), the Zambezi River basin (Tilmant & Kinzelbach, ), or in Spain (Macian‐Sorribes et al, ; Pereira‐Cardenal et al, ).…”

Section: Introductionmentioning

confidence: 99%

Optimizing Multireservoir System Operating Policies Using Exogenous Hydrologic Variables

Pina

Tilmant

Côté

2017

Water Resources Research

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Stochastic dual dynamic programming (SDDP) is one of the few available algorithms to optimize the operating policies of large‐scale hydropower systems. This paper presents a variant, called SDDPX, in which exogenous hydrologic variables, such as snow water equivalent and/or sea surface temperature, are included in the state space vector together with the traditional (endogenous) variables, i.e., past inflows. A reoptimization procedure is also proposed in which SDDPX‐derived benefit‐to‐go functions are employed within a simulation carried out over the historical record of both the endogenous and exogenous hydrologic variables. In SDDPX, release policies are now a function of storages, past inflows, and relevant exogenous variables that potentially capture more complex hydrological processes than those found in traditional SDDP formulations. To illustrate the potential gain associated with the use of exogenous variables when operating a multireservoir system, the 3,137 MW hydropower system of Rio Tinto (RT) located in the Saguenay‐Lac‐St‐Jean River Basin in Quebec (Canada) is used as a case study. The performance of the system is assessed for various combinations of hydrologic state variables, ranging from the simple lag‐one autoregressive model to more complex formulations involving past inflows, snow water equivalent, and winter precipitation.

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Section: Introductionmentioning

confidence: 99%

Optimizing Multireservoir System Operating Policies Using Exogenous Hydrologic Variables

Pina

Tilmant

Côté

2017

Water Resources Research

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“…Over the past 20 years, an increasing amount of legal and policy frameworks for transboundary water management have been implemented in internationally shared water courses (Qwist-Hoffmannn and McIntyre, 2016). River basin organizations are intended to facilitate the application of such mechanisms.…”

Section: Introductionmentioning

confidence: 99%

“…The optimization framework simulates adaptation to new infrastructure and policies, climate change, and socio-economic development. Conversely, in a rule-based simulation framework, allocation rules are usually based on the current socio-economic conditions or new rules are estimated, which may lead to suboptimal allocation decisions and an underestimation of project benefits (Pereira-Cardenal et al, 2016). The optimization approach is based on a perfect foresight formulation, assuming that optimal decisions are found with full knowledge of the planning period; limitations of this common approach in sectoral planning models are discussed in Sect.…”

Section: Introductionmentioning

confidence: 99%

WHAT-IF: an open-source decision support tool for water infrastructure investment planning within the water–energy–food–climate nexus

Payet-Burin

Kromann

Pereira-Cardenal

et al. 2019

Hydrol. Earth Syst. Sci.

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Abstract. Water infrastructure investment planning must consider the interdependencies within the water–energy–food nexus. Moreover, uncertain future climate, evolving socio-economic context, and stakeholders with conflicting interests, lead to a highly complex decision problem. Therefore, there is a need for decision support tools to objectively determine the value of investments, considering the impacts on different groups of actors, and the risks linked to uncertainties. We present a new open-source hydro-economic optimization model, incorporating in a holistic framework, representations of the water, agriculture, and power systems. The model represents the joint development of nexus-related infrastructure and policies and evaluates their economic impact, as well as the risks linked to uncertainties in future climate and socio-economic development. We apply the methodology in the Zambezi River basin, a major African basin shared by eight countries, in which multiple investment opportunities exist, including new hydropower plants, new or resized reservoirs, development of irrigation agriculture, and investments into the power grid. We show that it is crucial to consider the links between the different systems when evaluating the impacts of climate change and socio-economic development, which will ultimately influence investment decisions. We find that climate change could induce economic losses of up to USD 2.3 billion per year in the current system. We show that the value of the hydropower development plan is sensitive to future fuel prices, carbon pricing policies, the capital cost of solar technologies, and climate change. Similarly, we show that the value of the irrigation development plan is sensitive to the evolution of crop yields, world market crop prices, and climate change. Finally, we evaluate the opportunity costs of restoring the natural floods in the Zambezi Delta; we find limited economic trade-offs under the current climate, but major trade-offs with irrigation and hydropower generation under the driest climate change scenario.

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“…The increasing integration and instrumentation of heterogeneous infrastructure systems, e.g. power-gas systems [3], [4] or water-power systems [5], introduces spatial and temporal overlap in time-scales across different systems, removing the insularity required previously to guarantee control performance. Moreover, there are scenarios where a suitable system decomposition may not be known a priori, e.g.…”

Section: Introductionmentioning

confidence: 99%

Decomposition of Nonlinear Dynamical Networks Via Comparison Systems

Maruf

Kundu

Yeung

et al. 2018

2018 European Control Conference (ECC)

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In analysis and control of large-scale nonlinear dynamical systems, a distributed approach is often an attractive option due to its computational tractability and usually low communication requirements. Success of the distributed control design relies on the separability of the network into weakly interacting subsystems such that minimal information exchange between subsystems is sufficient to achieve satisfactory control performance. While distributed analysis and control design for dynamical network have been well studied, decomposition of nonlinear networks into weakly interacting subsystems has not received as much attention. In this article we propose a vector Lyapunov functions based approach to quantify the energy-flow in a dynamical network via a model of a comparison system. Introducing a notion of power and energy flow in a dynamical network, we use sum-of-squares programming tools to partition polynomial networks into weakly interacting subsystems. Examples are provided to illustrate the proposed method of decomposition.

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Joint optimization of regional water-power systems

Cited by 46 publications

References 20 publications

Optimizing Multireservoir System Operating Policies Using Exogenous Hydrologic Variables

Optimizing Multireservoir System Operating Policies Using Exogenous Hydrologic Variables

WHAT-IF: an open-source decision support tool for water infrastructure investment planning within the water–energy–food–climate nexus

Decomposition of Nonlinear Dynamical Networks Via Comparison Systems

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