Accelerating the computation of critical eigenvalues with parallel computing techniques

Eigenanalysis of power systems is frequently used to study the effect and tune the response of existing controllers, or to guide the design of new controllers. However, recent developments in the area lead to the necessity of studying larger power system models, resulting from the interconnection of transmission networks or the joint consideration of transmission and distribution networks. Moreover, these models include new types of controls, mainly based on power electronic interfaces, which are expected to provide significant support in the future. The consequence is that the size and complexity of these models challenge the computational efficiency of existing eigenanalysis methods. In this paper, a procedure is proposed that uses domain decomposition and parallel computing methods, to accelerate the computation of eigenvalues in a selected region of the complex plane with iterative eigenanalysis methods. The proposed algorithm is validated on a small transmission system and its performance is assessed on a large-scale, combined transmission and distribution system

Co-optimisation of Planning and Operation forActive Distribution Grids

Given the increased penetration of smart grid technologies, distribution system operators are obliged to consider in their planning stage both the increased uncertainty introduced by non-dispatchable distributed energy resources, as well as the operational flexibility provided by new real-time control schemes. First, in this paper, a planning procedure is proposed which considers both traditional expansion measures, e.g. upgrade of transformers, cables, etc., as well as real-time schemes, such as active and reactive power control of distributed generators, use of battery energy storage systems and flexible loads. At the core of the proposed decision making process lies a tractable iterative AC optimal power flow method. Second, to avoid the need for a real-time centralised coordination scheme (and the associated communication requirements), a local control scheme for the operation of individual distributed energy resources and flexible loads is extracted from offline optimal power flow computations. The performance of the two methods is demonstrated on a radial, low-voltage grid, and compared to a standard local control scheme

Virtual Induction Machine Strategy for Converters in Power Systems with Low Rotational Inertia

This paper presents a novel comprehensive control strategy for grid-connected Voltage Source Converters (VSCs) in power systems with low rotational inertia. The proposed model is based on emulating the physical properties of an Induction Machine (IM) and taking advantage of its inherent grid-friendly properties, i.e. self-synchronization, virtual inertia, power and frequency oscillation damping. For that purpose, a detailed mathematical model of the IMs working principles is derived, which includes the possibility of obtaining the unknown grid frequency without a dedicated synchronization unit, but rather via processing the voltage and current magnitude measurements at the converter output. This eliminates the need for an inherently nonlinear phase-locked loop, characteristic for virtual synchronous machines, while simultaneously preserving the synchronization and damping properties of a conventional electrical machine. Several case studies are presented that validate the mathematical principles of the proposed model and conclusions on VSC performance are drawn

A Centralised Control Method for Tackling Unbalances in Active Distribution Grids

Traditional distribution network operators are gradually being transformed to system operators, using modern technologies to ensure a secure and efficient operation in a rapidly changing and uncertain environment. One of their most challenging tasks is to tackle the unbalanced operation of low-voltage networks, traditionally caused by unequal loading and structural asymmetries, and exacerbated by the increased penetration of single-phase distributed energy resources. This paper proposes a centralized operation scheme based on a multi-period optimal power flow algorithm used to compute optimal set-points of the controllable distributed energy resources located in the system. The algorithm reduces the operational cost while satisfying the appropriate security and power quality constraints. Furthermore, the computational tractability of the algorithm and the incremental cost of tackling imbalances in the network are addressed. Finally, the performance of the proposed method is tested on an unbalanced low-voltage distribution network

Stability Performance of Power Electronic Deviceswith Time Delays

This paper deals with the impact of time delays on small-signal stability of power systems with an all converter-interfaced generation. For this purpose, a delay differential algebraic equation model of the voltage source converter and its control scheme is developed. The regulation is based on replicating the dynamical properties of a synchronous machine through appropriate controller configuration. Therefore, a virtual inertia emulation is included in the active power control loop. A transcedental nature of the characteristic equation is resolved by implementing the Chebyshev's discretization method and observing a finite number of critical, low-frequency eigenvalues. Based on the proposed approach, a critical measurement delay is evaluated. Furthermore, a bifurcation analysis of the droop gains and inertia constant is conducted. Stability regions and optimal parametrization of the voltage source converter controls are evaluated and discussed

TDNetGen: An open-source, parametrizable, large-scale, transmission and distribution test system

In this paper, an open-source MATLAB toolbox is presented that is able to generate synthetic, combined transmission and distribution network models. These can be used to analyse the interactions between transmission and multiple distribution systems, such as the provision of ancillary services by active distribution grids, the co-optimization of planning and operation, the development of emergency control and protection schemes spanning over different voltage levels, the analysis of combined market aspects, etc. The generated test-system models are highly customizable, providing the user with the flexibility to easily choose the desired characteristics, such as the level of renewable energy penetration, the size of the final system, etc

Power System Dynamic Simulations Using a Parallel Two-Level Schur-Complement Decomposition

As the need for faster power system dynamic simulations increases, it is essential to develop new algorithms that exploit parallel computing to accelerate those simulations. This paper proposes a parallel algorithm based on a two-level, Schur-complement-based, domain decomposition method. The two-level partitioning provides high parallelization potential (coarse- and fine-grained). In addition, due to the Schur-complement approach used to update the sub-domain interface variables, the algorithm exhibits high global convergence rate. Finally, it provides significant numerical and computational acceleration. The algorithm is implemented using the shared-memory parallel programming model, targeting inexpensive multi-core machines. Its performance is reported on a real system as well as on a large test system combining transmission and distribution networks

Contribution of distribution network control to voltage stability: A case study

A case study dealing with long-term voltage instability in systems hosting active distribution networks (DN) is reported in this paper. It anticipates future situations with high penetration of dispersed generation (DG), where the latter are used to keep distribution voltages within desired limits, in complement to load tap changers. The interactions between transmission and active DN are investigated on a 3108-bus test system. It involves transmission grid, large generators, and 40 DN, each with DG steered by a controller inspired by model predictive control. The reported simulations show the impact of distribution network voltage restoration, as well as the benefit of load voltage reduction actuated by the dispersed generators

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

Optimized Local Control for Active Distribution Grids using Machine Learning Techniques

Modern distribution system operators are facing a changing scenery due to the increasing penetration of distributed energy resources, introducing new challenges to system operation. In order to ensure secure system operation at a low cost, centralized and decentralized operational schemes are used to optimally dispatch these units. This paper proposes a decentralized, real-time, operation scheme for the optimal dispatch of distributed energy resources in the absence of extensive monitoring and communication infrastructure. This scheme uses an offline, centralized, optimal operation algorithm, with historical information, to generate a training dataset consisting of various operating conditions and corresponding distributed energy resources optimal decisions. Then, this dataset is used to design the individual local controllers for each unit with the use of machine learning techniques. The performance of the proposed method is tested on a low-voltage distribution network and is compared against centralized and existing decentralized methods