Scenario-based economic dispatch with tunable risk levels in high-renewable power systems
This paper introduces an empirical approach to dispatch resources in real-time power
system operation with growing levels of uncertainties emerging from intermittent and …
system operation with growing levels of uncertainties emerging from intermittent and …
Minimizing pumping energy cost in real-time operations of water distribution systems using economic model predictive control
Optimizing pump operations is a challenging task for real-time management of water
distribution systems (WDS). With suitable pump scheduling, pumping costs can be …
distribution systems (WDS). With suitable pump scheduling, pumping costs can be …
Simplified Approach to Mixed-Integer Chance-Constrained Optimization with Ensemble Streamflow Forecasts for Risk-Based Dam Operation
We developed an integrated optimization program to design the release strategy for a dam,
given a downstream flow target and considering medium-range ensemble forecasts of …
given a downstream flow target and considering medium-range ensemble forecasts of …
Scenario optimization with relaxation: a new tool for design and application to machine learning problems
Scenario optimization is by now a well established technique to perform designs in the
presence of uncertainty. It relies on domain knowledge integrated with first-hand information …
presence of uncertainty. It relies on domain knowledge integrated with first-hand information …
[HTML][HTML] Machine Learning for the Sustainable Management of Depth Prediction and Load Optimization in River Convoys: An Amazon Basin Case Study
LCP Campos Filho, NM Figueiredo, CJC Blanco… - Sustainability, 2024 - mdpi.com
The seasonal fluctuation of river depths is a critical factor in designing cargo capacity for
river convoys and logistics processes used for grain transportation in northern Brazil. Water …
river convoys and logistics processes used for grain transportation in northern Brazil. Water …
Flood management of lake toke: MPC operation under uncertainty
I Menchacatorre, R Sharma, B Furenes, B Lie - 2019 - openarchive.usn.no
A deterministic reference tracking model predictive control (MPC) is in use at Skagerak Kraft
for flood management of Lake Toke in Norway. An operational inflow estimate is used to …
for flood management of Lake Toke in Norway. An operational inflow estimate is used to …
Stochastic Model Predictive Control for Water Level Regulation in a Lake
In this paper, we propose a water level regulation framework for systems with uncertain
model parameters and subject to additive disturbances. Bayesian system identification is …
model parameters and subject to additive disturbances. Bayesian system identification is …
[图书][B] Data Science and Applications for Modern Power Systems
Measurement data has been with the operation and planning of large power grid since its
inception. However, it was really since early 2010s that the confluence of massive amount of …
inception. However, it was really since early 2010s that the confluence of massive amount of …
Design New Markets
In the past few chapters, we show how data analytics can solve technical challenges and
provide situational awareness for the future. Given the fact that many regions have …
provide situational awareness for the future. Given the fact that many regions have …
Chemical Process Optimal Design and Control with Account of Separate Probabilistic Constraints
T Lapteva, N Zyatdinov, D Mitsai - 2020 International Russian …, 2020 - ieeexplore.ieee.org
The paper proposes a new approach to solve optimal chemical process design problems,
taking into account the uncertainty of initial information. Solving the problem will allow us to …
taking into account the uncertainty of initial information. Solving the problem will allow us to …