Oliver Gehrke

Application of Model Predictive Control for Active Load Management in a Distributed Power System With High Wind Penetration

Summary form only given. This paper introduces an experimental platform (SYSLAB) for the research on advanced control and power system communication in distributed power systems and one of its components-an intelligent office building (PowerFlexHouse), which is used to investigate the technical potential for active load management. It also presents in detail how to implement a thermal Model Predictive Controller (MPC) for the heaters power consumption prediction in the PowerFlexHouse. It demonstrates that this MPC strategy can realize load shifting, and using good predictions in MPC-based control, a better matching of demand and supply can be achieved. With this demand side control study, it is expected that MPC strategy for active load management can dramatically raise energy efficiency and improve grid reliability, when there is a high penetration of intermittent energy resources in the power system.

Active load management in an intelligent building using model predictive control strategy

This paper introduces PowerFlexHouse, a research facility for exploring the technical potential of active load management in a distributed power system (SYSLAB) with a high penetration of renewable energy and presents in detail on how to implement a thermal model predictive controller for load shifting in PowerFlexHouse heaters power consumption scheme. With this demand side control study, it is expected that this method of demand response can dramatically raise energy efficiencies and improve grid reliability, when there is a high penetration of intermittent energy resources in the power system.

Wind and Photovoltaic Large-Scale Regional Models for Hourly Production Evaluation

This work presents two large-scale regional models used for the evaluation of normalized power output from wind turbines and photovoltaic power plants on a European regional scale. The models give an estimate of renewable production on a regional scale with 1h resolution, starting from a mesoscale meteorological data input and taking in account the characteristics of different plants technologies and spatial distribution. An evaluation of the hourly forecasted energy production on a regional scale would be very valuable for the transmission system operators when making the long-term planning of the transmission system, especially regarding the cross-border power flows. The tuning of these regional models is done using historical meteorological data acquired on a per-country basis and using publicly available data of installed capacity.

Evaluation of smart grid control strategies in co-simulation — integration of IPSYS and mosaik

This paper presents two different aspects considering a co-simulation of smart grid scenarios. First considers representing the control strategy in a separate discrete event simulation developed in a multi-agent platform. This study investigates the design and implementation of such a simulator. Special attention is given to timing issues presenting time variant and time invariant models. The second aspect presented in this paper is the co-simulation composition, investigating how to integrate a control simulation with other simulators in a co-simulation ecosystem. In this study the attention is given to the co-simulation scheduling, proposing two integration approaches: overall control and separate domain. Results from a proof-of-concept implementation are included.

Building a test platform for agents in power system control: Experience from SYSLAB

A tighter integration of information and communication technologies into power grids and a gradual decentralization of control are widely regarded as key responses to the transformation of power systems, even though many different approaches are investigated to achieve this. Lack of system-level simulation tools and the high risk of tests on a real-world power grid create a need for small, experimental grids on which new control concepts can be safely tested and demonstrated. In order to accommodate a wide range of possible control structures, the controller platform on such grids needs to be as flexible as possible. Software agents promise to be a programming paradigm in support of flexible, distributed applications. This paper describes their application in SYSLAB, an experimental facility for distributed power systems, and discusses experience gained in the implementation process.

Application genetic algorithms for load management in refrigerated warehouses with wind power penetration

Wind energy is produced at random times, whereas the energy consumption pattern shows distinct demand peaks during day-time and low levels during the night. The use of a refrigerated warehouse as a giant battery for wind energy is a new possibility that is being studied for wind energy integration as well as a way to store electricity produced during night-time by wind turbines. The controller for load management in a refrigerated warehouse with wind power penetration by GA-based is introduced in this paper. The objective function is to minimize the energy consumption for operating the refrigerated warehouse. It can be seen that the GA-based control strategy achieves feasible results for operating the temperature in refrigerated warehouse. Balancing the wind power production with refrigerated warehouse load management promises to be a clean and cost effective method. For refrigerated warehouse owners, it has the potential to lower operational costs.

Distribution Line Parameter Estimation Under Consideration of Measurement Tolerances

State estimation and control approaches in electric distribution grids rely on precise electric models that may be inaccurate. This work presents a novel method of estimating distribution line parameters using only root mean square voltage and power measurements under consideration of measurement tolerances, noise, and asynchronous timestamps. A measurement tolerance compensation model and an alternative representation of the power flow equations without voltage phase angles are introduced. The line parameters are obtained using numeric methods. The simulation demonstrates in case of the series conductance that the absolute compensated error is -1.05% and -1.07% for both representations, as opposed to the expected uncompensated error of -79.68%. Identification of a laboratory distribution line using real measurement data grid yields a deviation of 6.75% and 4.00%, respectively, from a calculation based on the manufacturers cable specifications and estimated line length. The transformed power flow equations deliver similar results despite the reduced problem complexity.

Activate distributed energy resources' services: Hierarchical voltage controller as an application

The flexibilities from controllable distributed energy resources (DERs) offer the opportunities to mitigate some of the operation problems in the power distribution grid. The provision of system services requires the aggregation and coordination of their flexibilities, in order to obtain the flexible capacity of large scale. In this paper, a hierarchical controller is presented to activate the aggregation, and tries to obtain a global optimum of the grid operation. A distribution grid with large penetration of highly varying generation or load is under the risk that the voltage quality delivered to the end users is very poor. Hence, a coordinated voltage control function is investigated given such control hierarchy utilizing the flexibilities from the DER units to obtain an optimal voltage profile along the distribution feeder. The results are two folded: the controller enables the efficient aggregation and dispatch, and it simplifies the optimization complexity; the involvement of DER flexibilities in voltage services can significantly improve the voltage quality and reduce the grid power loss without additional regulating devices.

Simulation-based validation of smart grids - status quo and future research trends

Smart grid systems are characterized by high complexity due to interactions between a traditional passive network and active power electronic components, coupled using communication links. Additionally, automation and information technology plays an important role in order to operate and optimize such cyber-physical energy systems with a high(er) penetration of fluctuating renewable generation and controllable loads. As a result of these developments the validation on the system level becomes much more important during the whole engineering and deployment process, today. In earlier development stages and for larger system configurations laboratory-based testing is not always an option. Due to recent developments, simulation-based approaches are now an appropriate tool to support the development, implementation, and roll-out of smart grid solutions. This paper discusses the current state of simulation-based approaches and outlines the necessary future research and development directions in the domain of power and energy systems.

Voltage estimation in active distribution grids using neural networks

The power flow in distribution grids is becoming more complicated as reverse power flows and undesired voltage rises might occur under particular circumstances due to integration of renewable energy sources, increasing the occurrence of critical bus voltages. To identify these critical feeders the observability of distribution systems has to be improved. To increase the situational awareness of the power system operator data driven methods can be employed. These methods benefit from newly available data sources such as smart meters. This paper presents a voltage estimation method based on neural networks which is robust under complex load and in-feeder generation situations. A major advantage of the proposed method is that the power system does not have to be explicitly modeled.