Kristian Edlund

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We consider a virtual power plant, which is given the task of dispatching a fluctuating power supply to a portfolio of flexible consumers. The flexible consumers are modeled as discrete batch processes, and the associated optimization problem is denoted the discrete virtual power plant dispatch problem (DVPPDP). First, the nondeterministic polynomial time(More)
One of the main difficulties in large-scale implementation of renewable energy in exisiting power systems is that the production from renewable sources is difficult to predict and control. For this reason, fast and efficient control of controllable power producing units – so-called “portfolio control” – becomes increasingly important as the ratio of(More)
The word flexibility is central to Smart Grid literature, but to this day a formal definition of flexibility is still pending. This paper present a taxonomy for modeling flexibility in Smart Grids, denoted Buckets, Batteries and Bakeries. We consider a direct control Virtual Power Plant (VPP), which is given the task of servicing a portfolio of flexible(More)
Economic Model Predictive Control is a receding horizon controller that minimizes an economic objective function rather than a weighted least squares objective function as in Model Predictive Control (MPC). We use Economic MPC to operate a portfolio of power generators and consumers such that the cost of producing the required power is minimized. The power(More)
In this paper, the problem of optimal choice of sensors and actuators is addressed. Given a functional encapsulating information of the desired performance and production economy the objective is to choose a control instrumentation from a given set to comply with its minimum. The objective of the work is twofold: reformulation of the business objectives(More)
This paper introduces a model predictive control (MPC) approach to construction of a controller for balancing power generation against consumption in a power system. The objective of the controller is to coordinate a portfolio consisting of multiple power plant units in an effort to perform reference tracking and disturbance rejection in an economically(More)
This paper presents a novel model predictive control scheme for frequency control in a single-area power system. The proposed controller provides set-point corrections to the system power generators, based on the solution to an optimal control problem. The optimal control problem directly incorporates the cost of operation into its objective function. A(More)
In this paper, we develop an efficient interior-point method (IPM) for the linear programs arising in economic model predictive control of linear systems. The novelty of our algorithm is that it combines a homogeneous and self-dual model, and a specialized Riccati iteration procedure. We test the algorithm in a conceptual study of power systems management.(More)