Model Predictive Control (MPC) can be used to control a system of energy producers and consumers in Smart Grid. In this paper, we use heat pumps for heating residential buildings with floor system. We the thermal capacity building shift consumption periods low electricity prices. way house becomes flexible power consumer This scenario is relevant systems significant share stochastic producers, e.g. wind turbines, where ability according production crucial. present model ground source based...

Integration of a large number flexible consumers in smart grid requires scalable power balancing strategy. We formulate the control problem as an optimization to be solved repeatedly by aggregator model predictive framework. To solve large-scale real-time decomposition methods. propose method based on Douglas-Rachford splitting this problem. The decomposes into smaller subproblems that can parallel, e.g., locally each unit connected aggregator. total consumption is controlled through...

In this work the heat dynamics of a storage tank were modelled on basis data and maximum likelihood methods. The resulting grey-box model was used for Economic Model Predictive Control (MPC) energy in tank. control objective to balance from solar collector consumption residential house. provides periods where there is low radiation stores when surplus heat. forecasts patterns based obtained meters group single-family houses Denmark. can also be heated by electric heating elements if...

Economic Model Predictive Control (MPC) is very well suited for controlling smart energy systems since electricity price and demand forecasts are easily integrated in the controller. Electric vehicles (EVs) expected to play a large role future Smart Grid. They provide grid services, both peak reduction ancillary by absorbing short term variations production. In this paper MPC minimizes cost of consumption single EV. Simulations show savings 50-60% costs compared uncontrolled charging from...

Abstract An integrated model predictive control (MPC) strategy to the power consumption and effluent quality of a water resource recovery facility (WRRF) by utilizing storage capacity from sewer system was implemented put into operation for 7-day trial period. This price-based MPC reacted electricity prices forecasted pollutant loads 24 hours ahead. The large available in directly upstream plant used incoming and, indirectly, WRRF during dry weather operations. balances costs treatment based...

The method described in this paper balances power production and consumption with a large number of thermal loads. Linear controllers are used for the loads to track temperature set point, while Model Predictive Control (MPC) model estimation load behavior coordination. total all is controlled indirectly through real-time price. MPC incorporates forecasts disturbances that influence loads, e.g. time-varying weather forecasts, order react ahead time. A simulation scenario demonstrates allows...

We develop an efficient homogeneous and self-dual interior-point method (IPM) for the linear programs arising in economic model predictive control of constrained systems with objective functions. The algorithm is based on a Riccati iteration procedure, which adapted to system equations solved IPMs. Fast convergence further achieved using warm-start strategy. implement MATLAB C. Its performance tested conceptual power management case study. Closed loop simulations show that: 1) proposed...

In this paper, we present a warm-started homogenous and self-dual interior-point method (IPM) for the linear programs arising in economic model predictive control (MPC) of systems. To exploit structure optimization problems, our algorithm utilizes Riccati iteration procedure which is adapted to non-standard system solved IPMs, specifically tailored MPC. Fast convergence further achieved by means recent warm-starting strategy IPMs that has not previously been applied We implement MATLAB its...

This paper summarizes comprehensively the work in four recent PhD theses from Technical University of Denmark related to Economic MPC future power systems. Future systems will consist a large number decentralized producers and controllable consumers addition stochastic such as wind turbines solar plants. Control scale requires new control algorithms. In this paper, we formulate system an Model Predictive (MPC) problem. When have linear dynamics, may be expressed program. We provide models...

A power balancing strategy based on Douglas-Rachford splitting is proposed as a control method for large-scale integration of flexible consumers in Smart Grid. The total consumption controlled through negotiation procedure between all units and coordinating system level. problem formulated centralized optimization but then decomposed into smaller subproblems that are solved locally by each unit connected to an aggregator. For systems the faster than solving full can be distributed include...

We have developed a versatile Model Predictive Control (MPC) framework, which can handle real-time control of large variety water systems. The framework combines fast-solvable optimisation model (a quadratic program) with evaluation and realignment by detailed hydrological-hydrodynamic model. flexibility the MPC is highlighted two case studies: (1) large-scale river system several weeks travel time, (2) an urban storm wastewater concentration time about half hour to one hour. Both studies...