Thierry Van Cutsem

Model Predictive Control of Voltages in Active Distribution Networks

This paper presents a centralized control scheme to regulate distribution network voltages in the presence of high penetration of distributed generation. The approach is inspired of Model Predictive Control in order to compensate for modeling inaccuracies and measurement noise. The control actions, calculated from a multi-step optimization, are updated and corrected by real-time measurements. The proposed controller uses a linear model to predict the behavior of the system and the optimization is solved using quadratic programming. The proposed corrective control has been tested in a 11-kV distribution network including 75 nodes and hosting 22 distributed generating units.

A short survey of methods for voltage instability detection

This paper shortly surveys existing and proposed methods for voltage instability detection. The emphasis is on methods relying on real-time measurements as well as on long-term voltage instability. Methods are classified according to the required measurement configuration: local vs. wide-area, standard SCADA-type vs. synchronized phasor measurements, etc. In the various categories, some of the features are summarized, and what appears to the authors as advantages or limitations is shortly discussed. An important feature is the ability to anticipate instability. Some tracks for further work on the subject are also outlined.

Dynamic Simulation of Large-Scale Power Systems Using a Parallel Schur-Complement-Based Decomposition Method

Power system dynamic simulations are crucial for the operation of electric power systems as they provide important information on the dynamic evolution of the system after an occurring disturbance. This paper proposes a robust, accurate and efficient parallel algorithm based on the Schur complement domain decomposition method. The algorithm provides numerical and computational acceleration of the procedure. Based on the shared-memory parallel programming model, a parallel implementation of the proposed algorithm is presented. The implementation is general, portable and scalable on inexpensive, shared-memory, multi-core machines. Two realistic test systems, a medium-scale and a large-scale, are used for performance evaluation of the proposed method.

Structure preserving direct methods for transient stability analysis of power systems

A structure preserving network configuration is considered, along with many realistic types of active and reactive load models. A unified approach is developed and general energy Liapunov functions are accordingly constructed. Practical stability domains and their use for devising appropriate direct criteria are proposed. Implementation considerations are discussed and illustrated.

Active Management of Low-Voltage Networks for Mitigating Overvoltages Due to Photovoltaic Units

In this paper, the overvoltage problems that might arise from the integration of photovoltaic (PV) panels into low-voltage (LV) distribution networks is addressed. A distributed scheme is proposed that adjusts the reactive and active power output of inverters to prevent or alleviate such problems. The proposed scheme is model-free and makes use of limited communication between the controllers in the form of a distress signal only during emergency conditions. It prioritizes the use of reactive power, while active power curtailment is performed only as a last resort. The behavior of the scheme is studied using dynamic simulations on a single LV feeder and on a larger network composed of 14 LV feeders. Its performance is compared with a centralized scheme based on the solution of an optimal power flow (OPF) problem, whose objective function is to minimize the active power curtailment. The proposed scheme successfully mitigates overvoltage situations due to high PV penetration and performs almost as well as the OPF-based solution with significantly less information and communication requirements.

Reconstructing and tracking network state from a limited number of synchrophasor measurements

A method is proposed to reconstruct and track network state from a limited number of phasor measurement unit (PMU) data. To deal with the resulting unobservability, the state with bus powers and generator voltages closest to previously estimated values is computed. Those values, treated as pseudo-measurements, are obtained from the last reconstructed state, in a recursive manner. The method involves solving an optimization problem with linear constraints. It is scalable insofar as it accommodates from a few PMUs up to configurations ensuring full network observability. Reconstruction of only a region is possible. These and other features are demonstrated on the Nordic32 test system, with synchronized phasors obtained from detailed time simulation of a situation evolving towards instability. Suitable choices of PMU location and pseudo-measurements are also discussed.

Accelerated and Localized Newton Schemes for Faster Dynamic Simulation of Large Power Systems

This paper proposes two methods to speed up the demanding time-domain simulations of large power system models. First, the sparse linear system to solve at each Newton iteration is decomposed according to its bordered block diagonal structure in order to solve only those parts that need to be solved and update only submatrices of the Jacobian that need to be updated. This brings computational savings without degradation of accuracy. Next, the Jacobian structure is further exploited to localize the system response, i.e., involve only the components identified as active, with an acceptable and controllable decrease in accuracy. The accuracy and computational savings are assessed on a large-scale test system.

Power system observability and related functions Derivation of appropriate strategies and algorithms

Abstract Observability analysis deals with the adequacy of the available measurement configuration for state estimation purposes. This paper considers methods to explore observability and to face unobservable situations. More explicity, first, the problem of unobservable networks is examined; strategies currently used are discussed and a more general method is proposed, to build a complete and reliable database. Second, topological concepts derived from observability are used to enhance the reliability of the bad data analysis under stringent identification conditions. Third, a concrete algorithm for observability analysis is proposed.

Some Reflections on Model Predictive Control of Transmission Voltages

This paper deals with the application of algorithms inspired by model predictive control to solve voltage-related power system control problems in both normal and emergency operating conditions. In the first part of the paper, we identify critical issues for a practical implementation of this methodology, and analyze how far these requirements have been met so far. In the second part, we outline a voltage control scheme that hopefully addresses the above issues. The central idea of this scheme is a static optimization to determine target control values, followed by a dynamic optimization to produce a feasible transition, both carried out in the closed-loop mode of model predictive control.

Investigating state reconstruction from scarce synchronized phasor measurements

Synchronized phasor measurements can potentially track the system dynamics between two classical state estimations. However, in the PMU configurations available nowadays and in the near future, those measurements are too scarce for the whole system state to be estimated. Therefore, we investigate the possibility to reconstruct coherent, time-synchronized system states from the available PMU data. State reconstruction is formulated as an optimization problem. The objective is to minimize, in the space of bus powers, the distance between the reconstructed state and the last state estimate provided by a standard state estimator. PMU data are imposed as equality constraints. Furthermore, the placement of PMUs near generators is advocated for higher accuracy of state reconstruction. The performance and potential benefits of the approach are illustrated by processing snapshots obtained from detailed time simulation of a test system subject to a disturbance and corrective actions.