• Energy Research

The appropriate control and management of reactive power is of great relevance in the electrical reliability, stability, and security of power grids. This issue is considered in order to increase system efficiency and to maintain voltage under the acceptable value range. In this regard, novel technologies as FACTS, renewable energies, among others, are varying conventional grid behavior leading to unexpected limit capacity reaching due to large reactive power flow. Thus, optimal planning of this must be considered. This paper proposes a new application for a simple and easy implementation optimization algorithm, called Rao-3, to solve the constrained non-linear optimal reactive power dispatch problem. Moreover, the integration of solar and wind energy as the most applied technologies in electric power systems are exploited. Due to the continuous variation and the natural intermittence of wind speed and solar irradiance as well as load demand fluctuation, the uncertainties which have a global concern are investigated and considered in this paper. The proposed single-objective and multi-objective deterministic/stochastic optimal reactive power dispatch algorithms are validated using three standard test power systems, namely IEEE 30-bus, IEEE 57-bus, and IEEE 118-bus. The simulation results show that the proposed optimal reactive power dispatch algorithms are superior compared with two recent algorithms (Artificial electric field algorithm (AEFA) and artificial Jellyfish Search (JS) algorithm) and other optimization algorithms used for solving the same problem.

Wind power is increasing rapidly and specially offshore wind. Offshore wind offers certain advantages as more constant wind and additional space without large restriction. However, deep-waters require floating technologies. A key drawback of offshore wind is the reduced windows for operation and maintenance. Therefore, the use of optimal control algorithms that ensure the correct operation of the wind farm is essential. Offshore wind farms are usually oriented towards a defined direction of wind flow, so upstream turbines tend to provide more active power, carrying higher fatigue load, which results in uneven distribution of fatigue across the wind farms. Loads must be distributed among the members of the farm, to extend the farm and turbines life and reduce possible maintenance or breakage costs. Taking into account wake effects as well as hydrodynamic impacts which add additional motion and stress to the system, this paper presents a wind farm Model Predictive Controller (MPC) in order to optimize the loads of each wind turbine for life-extension. The results of the control show how the power generation is met and the load distribution are better balanced reducing system stress. 

AbstractDuring the last years wind power has emerged as one of the most important sources in the power generation share. Due to stringent Grid Code requirements, wind power plants (WPPs) should provide ancillary services such as fault ride-through and damping of power system oscillations to resemble conventional generation. Through an adequate selection of input–output signal pairs, WPPs can be effectively used to provide electromechanical oscillations damping. In this paper, different analysis techniques considering both controllability and observability measures and input–output interactions are compared and critically examined. Recommendations are drawn to select the best signal pairs available from WPPs to contribute to power oscillations damping. Control system design approaches including single-input single-output and multivariable control are considered. The recommendation of analysis techniques is justified through the tools usage in a test system including a WPP.

Recently, the concept of wind power plant has been introduced as a result of the increment of wind power penetration in power systems. A wind power plant can be defined as a wind farm, which is expected to behave similar to a conventional power plant in terms of power generation, control and ancillary services. Transmission system operators are requiring wind power generation to help to power system with some ancillary services such as fault ride through or power system stabilizer capability. Therefore, it is important to study the power system stabilizer capability of wind power plants. In this paper, a comparison of various power system stabilizer schemes is presented. The effect of the distance from the tie line to the wind farm on the controller response and the influence of wind power plants proximity to synchronous generators are also evaluated. These studies show that wind power plants have promising power system stabilizer capability even using local input signals. However, the location of the wind power plant on the power system is a critical factor. Copyright © 2012 John Wiley & Sons, Ltd.

The high-penetration of Distributed Energy Resources (DER) in low voltage distribution grids, mainly photovoltaics (PV), might lead to overvoltage in the point of common coupling, thus, limiting the entrance of renewable sources to fulfill the requirements from the network operator. Volt-var is a common control function for DER power converters that is used to enhance the stability and reliability of the voltage in the distribution system. In this study, a centralized algorithm provides local volt-var control parameters to each PV inverter, which are based on the electrical grid characteristics. Because accurate information of grid characteristics is typically not available, the parametrization of the electrical grid is done using a local power meter data and a voltage sensitivity matrix. The algorithm has different optimization modes that take into account the minimization of voltage deviation and line current. To validate the effectiveness of the algorithm and its deployment in a real infrastructure, the solution has been tested in an experimental setup with PV emulators under laboratory conditions. The volt-var control algorithm successfully adapted its parameters based on grid topology and PV inverter characteristics, achieving a voltage reduction of up to 25% of the allowed voltage deviation.

The continuing increase of wind energy penetration into power systems, in combination with the retirement of conventional generation, raises new challenges for the maintenance of power system stability. This paper presents a comprehensive review of wind power plant capabilities to provide frequency support and the corresponding methods available in the published literature are thoroughly analysed and compared. The topic is covered from different perspectives giving a comprehensive overview on the work carried out in this field. In addition, the integration of energy storage technologies and dispatching of wind farms during frequency deviations are thoroughly discussed. Finally, technical challenges, future research lines and general recommendations are provided.

Energy management systems (EMS) are vital supervisory control tools used to optimally operate and schedule Microgrids (MG). In this paper, an EMS algorithm based on mixed-integer nonlinear programming (MINLP) is presented for MG in islanding mode considering different scenarios. A local energy market (LEM) is also proposed with in this EMS to obtain the cheapest price, maximizing the utilization of distributed energy resources. The proposed energy management is based on LEM and allows scheduling the MG generation with minimum information shared sent by generation units. Load demand management is carried out by demand response concept to improve reliability and efficiency as well as to reduce the total cost of energy (COE). Simulations are performed with real data to test the performance and accuracy of the proposed algorithm. The proposed algorithm is experimentally tested to evaluate processing speed as well as to validate the results obtained from the simulation setup on a real MG Testbed. The results of the EMS–MINLP based on LEM are compared with a conventional EMS based on LEM. Simulation and experimental results show the effectiveness of the proposed algorithm which provides a reduction of 15% in COE, in comparison with conventional EMS.

Water and energy are becoming more and more important in agriculture, urban areas and for the growing population worldwide, particularly in developing countries. To provide access to water it is necessary to use appropriate pumping systems and supply them with enough energy for operation. Pumps powered by solar photovoltaic energy are complex electromechanical systems that include hydraulic equipment, electrical machines, sensors, power converters, and control units. Therefore, solar photovoltaic pumping systems are associated with various fields of science and engineering. In remote, less-populated areas without electricity, where it is either challenging to connect to the grid or it is not possible, solar photovoltaic water pumping systems can play a significant role. To see whether solar photovoltaic pumping systems may be a practical, viable, and affordable method of pumping water it is necessary to study different aspects of their operation. The goal of this current article is to evaluate and outline recent research and advancement in the field of solar photovoltaic pumping systems. The major focus is on the standalone photovoltaic pumping system’s components, factors that affect system efficiency, performance evaluation, system optimization, and the potential for integration with modern control techniques. The main objective of this article is to give a broader overview of solar photovoltaic technologies for researchers, engineers, and decision-makers.

Transmission system operators are increasingly demanding that wind power plants (WPPs) contribute to enhance stability of power systems. When WPPs act as power system stabilizers(PSSs), the control and measured signals used to damp the oscillations may be located far away fromthe point where the oscillations are originated, typically at the synchronous generators. The use of only local measurements would imply a more robust system not requiring fast communication systems. The output signal used by the PSS in a WPP can be active or reactive power. The optimal combination of input and output to improve the system performance requires a detailed analysis. In this paper, a novel criterion to select input-output signals used by a PSS based on WPPs is presented. Unlike previous results, the proposed criterion considers explicitly local and remote signals in the analysis. Using fundamental design limitations and controllability and observability concepts, the criterion is able to identify the most adequate pair of input-output local signals without designing the controller. The application of the proposed selection criterion is illustrated in a three-synchronous-machine system with a WPP connected.