Distributed voltage control in electrical power systems

Voltage instability stems from the attempt of load dynamics to restore power consumption beyond the capability of the combined transmission and generation system. Discrete event controllers such as load tap changing transformers (LTCs), electronically controlled HVDC lines and switched capacitor banks can locally maintain the voltage but following a major disturbance that causes a strong decrease in the voltages, there are some interaction between LTCs action and up to now there has been relatively little attention paid to coordination between important components in voltage stability using message exchange between them and applying distributed control and taking discrete events into account. So, this study aims at voltage stability enhancement by using coordinated control of the discrete event controllers by using message exchange between the different local control agents. Various approaches for coordinating local controllers (e.g. distributed model predictive controllers) will be investigated. The influence of the discrete event driven local voltage controllers on remote locations of the network has to be investigated in a hybrid systems model framework

A novel technique for load frequency control of multi-area power systems

In this paper, an adaptive type-2 fuzzy controller is proposed to control the load frequency of a two-area power system based on descending gradient training and error back-propagation. The dynamics of the system are completely uncertain. The multilayer perceptron (MLP) artificial neural network structure is used to extract Jacobian and estimate the system model, and then, the estimated model is applied to the controller, online. A proportional–derivative (PD) controller is added to the type-2 fuzzy controller, which increases the stability and robustness of the system against disturbances. The adaptation, being real-time and independency of the system parameters are new features of the proposed controller. Carrying out simulations on New England 39-bus power system, the performance of the proposed controller is compared with the conventional PI, PID and internal model control based on PID (IMC-PID) controllers. Simulation results indicate that our proposed controller method outperforms the conventional controllers in terms of transient response and stability

Voltage coordination in multi-area power systems via distributed model predictive control

Power systems are nowadays becoming more and more interconnected, and controlled by several TSOs (Transmission System Operators), in order to ensure a reliable and economical supply and distribution of electric power. These (interconnected) electrical power networks are often considered as the most complex man-made dynamical systems ever. For example, according to the dataset provided by the ENTSO-E (European Network of Transmission System Operators for Electricity) for static studies (calculation of the AC load flow), the European interconnected power grid consists of approximately 4300 buses, 6300 lines and 1100 transformers together with their loads, distribution systems and generations in-feeds (in different voltage levels of 380 kV, 220 kV and 150 kV). The proper control of such a large-scale interconnected power system is a very challenging problem due to the various continuous and discrete dynamics evolving in the system and their complicated interactions. Each local control agent (CA), corresponding to an area operated by one TSO, tries to achieve local improvement. However, it happens frequently that a local initiating disturbance in one area triggers some local control actions in its own area which in turn triggers further disturbances in the neighboring areas causing some undesirable control actions by their neighbors, and eventually a cascade of possibly wrong control actions lead the overall system to a final collapse. One important class of power system instability is voltage instability, which actually arises from the inability of combined generation-transmission systems to deliver the power requested by (dynamical recovery) voltage-dependent loads. Such a voltage instability, if not corrected properly, due to a cascade of events, can eventually lead to voltage collapse (abnormally low voltages in a major portion of the system) often resulting in blackouts or separation of the system into separate unsynchronized islands. The societal impacts and financial costs/losses caused by blackouts are significantly huge. The voltage in electrical power systems is, in nature, a ``local" variable unlike frequency being a ``global" variable. This means that, in multi-area power systems, only areas that are electrically close together interact with each other for voltage, and there is no need to involve distant areas with negligible common interest in solving a local optimization problem. The latter promotes the decomposition approaches for voltage control, where the voltage control still remains a prerogative of the local utilities. This thesis focuses on long-term voltage instability - in the order of several minutes after a major disturbance. The driving force of such instability, following a disturbance, is the process of load restoration, where the dynamics of recovering loads directly as well as some control mechanism such as LTCs (Load Tap Changing transformers) indirectly (by restoring the distribution-side voltages of the corresponding voltage-dependent loads), try to locally restore the load powers to the pre-disturbance values. The long-term voltage instability often occurs when LTCs try to restore the distribution side voltages of the connected buses, while the maximum power that the transmission system can provide to loads is reduced by the reactive power capability limits of generators, mainly enforced by OXLs (Over eXcitation Limiters). It seems rather intuitive, then, to seek some way of anticipating what will be the future behavior of a power system, by employing controllers which can look ahead in time. The long-term voltage control becomes even a more complex and harder problem in large-scale multi-area power system, each controlled by an independent TSO. The reason is that, for example, an arbitrary LTC move in one area can trigger undesirable LTC move(s), OXL activations in other areas, and such complicated global interactions may eventually lead to a blackout in the form of a voltage collapse. In order to avoid such a collapse in large-scale multi-area power systems, the local control actions taken by each CA, must be coordinated with those of (adjacent) neighbors. This coordination requires communications between neighboring CAs. This thesis proposes an efficient distributed Model Predictive Control (MPC) paradigm which combines two concepts of ``looking-ahead" and ``coordination". The proposed MPC-based control scheme relies on the communication of planned local control actions among neighboring CAs, each possibly operated by an independent TSO. Modelica, a free of charge object-oriented language, is used to develop a much-faster-than-real-time simulator, providing an hybrid framework for effectively modeling and simulating power systems. Modelica facilitates the development of tools to generate very efficient codes for modeling of compositional physical systems such as electrical power networks, by relaxing the causality constraint of components, and focusing only on the topology of the overall system. In this thesis, the dynamic models for anticipation, are derived by considering each area as a hybrid dynamical system, using DAEs to describe piecewise continuous dynamics, and the set of events of hybrid automata representing the discrete logical controllers. This hybrid modeling framework captures the complex interactions between continuous and discrete dynamics. The ``looking-ahead" voltage controller can anticipate, within the prediction horizon window, for example, the activation of OXLs, moving towards reaching the maximum physical tap limits for LTCs, and deviating too much from the prescribed voltage bounds for buses. The controller will then efficiently use these anticipations, by selecting a control sequence that does not cause the above-mentioned constraint violations. The first input of the best control sequence selected by each local MPC, at each discrete time instant, will be applied to the local system until the next time instant, where the local optimization repeats again selecting the new best control action. Each CA, knowing a local model of its own area, as well as a reduced-order Quasi Steady-State (QSS) models of its immediate neighboring areas, and assuming a simpler equivalent PV model for the distant areas, performs a greedy local optimization over a finite window in time, communicating its planned control input sequence to its immediate neighbors only. The ``communicating" voltage controller enables each CA to coordinate its own local action with what its immediate neighbors are planning to do, assuming a QSS model for predicting how control actions of neighbors influence the interacting variables. The good performance of the proposed real-time model-based feedback coordinating controller, following major disturbances, is illustrated using time-domain simulation of the well-known realistic Nordic32 test system, assuming worst-case conditions. Robustness of the proposed method against measurement inaccuracies, modeling errors as well as the uncertainty of the load behavior has also been illustrated. This thesis considers two cases where, in the first reasonably sized network, a local CA, knows the complete model of the overall system, while, in the second realistic sized system, it employs reduced-order QSS models for immediate neighbors, and assumes a simpler equivalent PV model for the distant areas. Simulation results illustrates the significant achievements obtained when the proposed model-based coordinating control is applied to different systems under some severe disturbances. This thesis compares the above-mentioned simulation results with scenarios where a purely decentralized uncoordinated deadband control, as the current practice for LTCs, is applied, or where a decentralized uncoordinated MPC approach with no communication is applied. In this way it becomes possible to identify the two afore-mentioned distinct contributions of the proposed model-based coordinating approach namely ``looking-ahead" and ``communication", since the decentralized deadband approach lacks both anticipation and coordination, and the decentralized MPC approach ignores the communications with neighbors

Anticipating and Coordinating Voltage Control for Interconnected Power Systems

This paper deals with the application of an anticipating and coordinating feedback control scheme in order to mitigate the long-term voltage instability of multi-area power systems. Each local area is uniquely controlled by a control agent (CA) selecting control values based on model predictive control (MPC) and is possibly operated by an independent transmission system operator (TSO). Each MPC-based CA only knows a detailed local hybrid system model of its own area, employing reduced-order quasi steady-state (QSS) hybrid models of its neighboring areas and even simpler PV models for remote areas, to anticipate (and then optimize) the future behavior of its own area. Moreover, the neighboring CAs agree on communicating their planned future control input sequence in order to coordinate their own control actions. The feasibility of the proposed method for real-time applications is explained, and some practical implementation issues are also discussed. The performance of the method, using time-domain simulation of the Nordic32 test system, is compared with the uncoordinated decentralized MPC (no information exchange among CAs), demonstrating the improved behavior achieved by combining anticipation and coordination. The robustness of the control scheme against modeling uncertainties is also illustrated

Dynamic optimisation for environomic power dispatch in microgrids

As a result of the increasing number of distributed energy resources (DER) in the electrical grid and their commitment to future market participation, control strategies for the optimal operation of DER gain importance. For this scenario a microgrid is a promising approach and forms a solution to this challenge. Microgrids are subsystems of the distribution grid including distributed generation (DG) units, storage devices and controllable loads, and can operate either connected or isolated from the utility grid. Ensuring a smooth, reliable and economic operation of a microgrid requires an energy management system that dynamically fits the production to the consumption in combination with storage. Quick response of the energy management strategy is crucial for a microgrid as compared to a conventional energy system. In this paper, a formulation of the environomic power dispatch approach in microgrids is proposed which uses multiobjective optimisation. The application aims to fulfill the time varying energy demand while minimising the costs and emissions of the local production and imported energy from the utility grid. With the introduction of a storage device, stored energy is controlled to balance the power generation of renewable sources, cover the overall microgrid demand and to optimise the overall power exchange between utility grid and microgrid. Operational constraints such as generator limits, start-up, operation and maintenance costs and the intermittency of renewable energy sources (RES) are to be satisfied. A representative microgrid structure is studied as an example and some simulation results are presented to demonstrate the performance of the microgrid environomic power dispatch approach

A Three-Level Single Stage A-Source Inverter With the Ability to Generate Active Voltage Vector During Shoot-Through State

Single-stage boosting capability of impedance network (IN) inverters makes this family of inverters an attractive choice for DC/AC applications with low input DC voltage. A specific time of shoot-through (ST) state is required to achieve the required voltage gain. Conventionally ST state and zero output voltage vector should be applied simultaneously. This constraint limits the modulation index and increases the voltage stress of the semiconductor devices, particularly for applications requiring a high boosting factor. In this paper, as the boosting stage for a three-level inverter, a new modified configuration of A-source IN with two series outputs is proposed and connected to a 10-switches three-level inverter. Besides generating two outputs by a single IN, the proposed DC/AC inverter is able to apply an active voltage vector during the ST state. This capability improves the DC/AC voltage gain, increases the modulation index, and decreases the required ST time. The operation principles are described, and the steady-state relations are derived. It is compared with other magnetically coupled INs in terms of boost factor and voltage stress of switches. Considering the 10-switches three-level inverter as the front-end inverter, an adopted maximum boost strategy using the space vector modulation is developed targeting minimum ST time. Finally, a laboratory prototype of the converter is developed, and several tests are carried out. The results validate the given theories and simulations.© The Authors. Published by IEEE. This work is licensed under a Creative Commons Attribution 4.0 License. For more information, see https://creativecommons.org/licenses/by/4.0/fi=vertaisarvioitu|en=peerReviewed

Load frequency control for multi-area power systems : a new type-2 fuzzy approach based on Levenberg–Marquardt algorithm

In this study, a new fuzzy approach is proposed for load frequency control (LFC) of a multi-area power system. The main control system is constructed by use of interval type-2 fuzzy inference systems (IT2FIS) and fractional-order calculus. In designing the controller, there is no need for the system dynamics, therefore the system Jacobian is obtained by a multilayer perceptron neural network (MLP-NN). Uncertainties are modeled by IT2FIS, and for training fuzzy parameters, Levenberg Marquardt algorithm (LMA) is used, which is faster and more robust than gradient descent algorithm (GDA). The system stability is studied by Matignon’s stability method under time-varying disturbances. A comparison between the proposed controller with type-1 fuzzy controller on the New England 39-bus test system is also carried out. The simulations demonstrate the superiority of the designed controller

SWIFT: achter het stuur van slimme windmolenparken

Welke ‘slimme technieken’ kunnen helpen om windmolenparken efficiënter aan te sluiten op de bestaande elektriciteitsnetten? Dat is de hamvraag in het onderzoeksproject ‘SWIFT’ dat begin 2013 van start ging. De onderzoekers bestuderen verschillende technieken voor ‘actief netbeheer’ die vooral toelaten om windmolens zo snel mogelijk aan te sluiten, tegen een zo laag mogelijke kost. Er zijn ook uitgebreide praktijktests gepland in de Haven van Antwerpen