Morten Juelsgaard

Wind turbine pitch optimization

We consider a static wind model for a three-bladed, horizontal-axis, pitch-controlled wind turbine. When placed in a wind field, the turbine experiences several mechanical loads, which generate power but also create structural fatigue. We address the problem of finding blade pitch profiles for maximizing power production while simultaneously minimizing fatigue loads. In this paper, we show how this problem can be approximately solved using convex optimization. When there is full knowledge of the wind field, numerical simulations show that force and torque RMS variation can be reduced by over 96% compared to any constant pitch profile while sacrificing at most 7% of the maximum attainable output power. Using iterative learning, we show that very similar performance can be achieved by using only load measurements, with no knowledge of the wind field or wind turbine model.

Distribution Loss Reduction by Household Consumption Coordination in Smart Grids

In this work, we address the problem of optimizing the electrical consumption patterns for a community of closely located households, with a large degree of flexible consumption, and further some degree of local electricity production from solar panels. We describe optimization methods for coordinating consumption of electrical energy within the community, with the purpose of reducing grid loading and active power losses. For this we present a simplified model of the electrical grid, including system losses and capacity constraints. Coordination is performed in a distributed fashion, where each consumer optimizes his or her own consumption pattern, taking into account both private objectives, specific to each individual consumer, as well as objectives common to all consumers. In our work, the common objective is to minimize active losses in the grid, and ensure that grid capacity limits are obeyed. These objectives are enforced by coordinating consumers through a nonlinear penalty on power consumption. We present simulation test-cases, illustrating that significant reduction of active losses, can be obtained by such coordination. The distributed optimization algorithm employs the alternating directions method of multipliers.

Utilization of Wind Turbines for Upregulation of Power Grids

This work considers the use of wind turbines for aiding upregulation of an electrical grid, by employing temporary overproduction with respect to available power. We present a simple model describing a turbine and show how the possible period of overproduction can be maximized by solving a series of convex problems, where the load is distributed among several turbines in a farm. Thereafter, we present an optimization scheme that guarantees a lower limit for the overproduction period and subsequently propose an adaptive implementation that is robust against parameter uncertainties.

Loss Minimization and Voltage Control in Smart Distribution Grid

Abstract This work presents a strategy for increasing the installation of electric vehicles and solar panels in low-voltage grids, while obeying voltage variation constraints. Our approach employs minimization of active power losses for coordinating consumption and generation of power, as well as reactive power control to maintain satisfactory grid operation. Numerical case studies illustrate how our approach can significantly increase installation of both electric vehicles and solar panels, while avoiding unsatisfactory over- and under-voltages throughout the grid.

Minimization of distribution grid losses by consumption coordination

In this work, we address the problem of optimizing the electrical consumption patterns for a community of closely located households, with a large degree of flexible consumption, and further some degree of local electricity production from solar panels. We describe optimization methods for coordinating consumption of electrical energy within the community, with the purpose of reducing grid loading and active power losses. For this we present a simplified model of the electrical grid, including system losses and capacity constraints. Coordination is performed in a distributed fashion, where each consumer optimizes his or her own consumption pattern, taking into account both private objectives, specific to each individual consumer, as well as objectives common to all consumers. In our work, the common objective is to minimize active losses in the grid, and ensure that grid capacity limits are obeyed. These objectives are enforced by coordinating consumers through nonlinear tariffs on power consumption. We present simulation test-cases, illustrating that significant reduction of active losses, can be obtained by such coordination. The distributed optimization algorithm, employs the alternating directions method of multipliers.

Wind Farm Dispatch Control for Demand Tracking and Minimized Fatigue

Abstract This work presents a strategy for dispatching production references to the individual turbines in a wind farm, such that an overall production demand for the farm is obeyed, while the fatigue experienced by the turbines is minimized. Using a turbine fatigue model for simulating the aging across the farm, we show that a 17 % reduction of the turbine aging can be obtained compared to a commonly employed industrial dispatcher, without degrading the power demand tracking.

Control structures for Smart Grid balancing

This work addresses the problem of maintaining the balance between consumption and production in the electricity grid when volatile resources, such as wind and sun, account for a large percentage of the power generation. We present control structures for Smart Grid balancing services on three different levels: portfolio, larger scale individual power units, and aggregations of small power units. Our focus is on illustrating the connection between coordination and control algorithms.

Robust Utilization of Wind Turbine Flexibility for Grid Stabilization

Abstract This work considers the use of wind turbines for stabilizing an electrical grid, by employing temporary overproduction with respect to available power. We present a simple model describing a turbine, and show how the possible period of overproduction, can be maximized through a series of convex problems, where the load is distributed among several turbines in a farm. We then present an optimization scheme that guarantees a lower limit for the overproduction period and subsequently propose an adaptive implementation that is robust against parameter uncertainties.

Distributed Coordination of Household Electricity Consumption

This work presents a distributed framework for coordination of flexible electricity consumption for a number of households in the distribution grid. Coordination is conducted with the purpose of minimizing a trade-off between individual concerns about discomfort and electricity cost, on the one hand, and joint concerns about grid losses and voltage variations on the other. Our contribution is to demonstrate how distributed coordination of both active and reactive consumption may be conducted, when consumers are jointly coupled by grid losses and voltage variations. We further illustrate the benefit of including consumption coordination for grid operation, and how different types of consumption present different benefits.