Frequency and voltage partitioning in presence of renewable energy resources for power system (example: North Chile power network)

This paper investigates techniques for frequency and voltage partitioning of power network based on the graph-theory. These methods divide the power system into distinguished regions to avoid the spread of disturbances and to minimize the interaction between these regions for frequency and voltage control of power system. In case of required active and reactive power for improving the performance of the power system, control can be performed regionally instead of a centralized controller. In this paper, renewable energy sources are connected to the power network to verify the effect of these sources on the power systems partitioning and performance. The number of regions is found based on the frequency sensitivity for frequency partitioning and bus voltage for voltage partitioning to disturbances being applied to loads in each region. The methodology is applied to the north part of Chile power network. The results show the performance and ability of graph frequency and voltage partitioning algorithm to divide large scale power systems to smaller regions for applying decentralized controllers.Peer ReviewedPostprint (published version

Stochastic Distributed Control for Arbitrarily Connected Microgrid Clusters

Due to the success of single microgrids, the coming years are likely to see a transformation of the current electric power system to a multiple microgrid network. Despite its obvious promise, however, this paradigm still faces many challenges, particularly when it comes to the control and coordination of energy exchanges between subsystems. In view of that, in this paper we propose an optimal stochastic control strategy in which microgrids are modeled as stochastic hybrid dynamic systems. The optimal control is based on the jump linear theory and is used as a means to maximize energy storage and the utilization of renewable energy sources in islanded microgrid clusters. Once the gain matrices are obtained, the concept of #-suboptimality is applied to determine appropriate levels of power exchange between microgrids for any given interconnection pattern. It is shown that this approach can be efficiently applied to large-scale systems and guarantees their connective stability. Simulation results for a three microgrid cluster are provided as proof of concept

Jump Linear Quadratic Control for Microgrids with Commercial Loads

Due to the aging power-grid infrastructure and increased usage of renewable energies, microgrids (μGrids) have emerged as a promising paradigm. It is reasonable to expect that they will become one of the fundamental building blocks of a smart grid, since effective energy transfer and coordination of μGrids could help maintain the stability and reliability of the regional large-scale power-grid. From the control perspective, one of the key objectives of μGrids is load management using local generation and storage for optimized performance. Accomplishing this task can be challenging, however, particularly in situations where local generation is unpredictable both in quality and in availability. This paper proposes to address that problem by developing a new optimal energy management scheme, which meets the requirements of supply and demand. The method that will be described in the following models μGrids as a stochastic hybrid dynamic system. Jump linear theory is used to maximize storage and renewable energy usage, and Markov chain theory is applied to model the intermittent generation of renewable energy based on real data. Although the model itself is quite general, we will focus exclusively on solar energy, and will define the performance measure accordingly. We will demonstrate that the optimal solution in this case is a state feedback law with a piecewise constant gain. Simulation results are provided to illustrate the effectiveness of such an approach

Teaching sustainable resource management in uncertain environment

Dynamic evolutions of resource stocks with stochastic elements in the transition equation are in general very difficult to master. Their handling requires a deep understanding of control theory, probability theory and sometimes even of game theory due to strategic interaction of 'agents'. But without strong mathematical backgrounds, students from adjacent research fields have a hard time with control theory. The same is true for probability theory and game theory. One way to avoid this problem is to change the aim: instead of target function optimization, guarantee the continuance of the system within certain boundaries. The latter relates to Viability theory. Unfortunately, even Viability theory requires more mathematics than the 'average' student is prepared for. The paper at hand will demonstrate how Excel can help here. Excel is applied since it is a widespread tool and most students are familiar with its basic features. Therefore students can concentrate on how to implement a dynamic system in a spreadsheet and how to simulate probability distributions and approximate the distribution of the target function - given different control rules. This enables them to assess opportunities and risks associated with these control rules. One topic appropriate to demonstrate the idea is renewable resource management. As many studies state, there is a deficit in sustainable learning not only in economics (Salemi and Siegfried 1999; Walstad and Allgood 1999) , but particular in system dynamic models (Moxnes, E. 2000; Pala and Vennix 2005). This is due to the complexity associated with long run- and feedback effects, and the complexity becomes even harder when stochastic development is included. The purpose of this paper will be to inspire students and to encourage them to solve stochastic dynamic problems later on their own with the simple tools at hand presently.Resource /Energy Economics and Policy,

Design of a kite controller for airborne wind energy

Airborne wind energy is a field of technology being developed to make use of the vast, renewable wind power resource which is above the reach of traditional wind turbines, without the need for a large tower. Much analytical research has been undertaken in recent years to better understand the problem space. However, there are relatively few working systems that demonstrate their functioning and can be compared with simulations and theory. Off-grid power systems still rely heavily on diesel generators, so devices that tap renewable energy sources with similar ease of deployment and lower cost of energy would help this sector to reduce its reliance on expensive, polluting, fossil fuels. The development of these systems is often performed by teams with business interests leaving little open access content available regarding the design process of such devices or the data that they provide. A kite control pod has been designed for the remote control of a standard kitesurfing kite and a prototype has been demonstrated stably flying such a kite on a fixed length tether. This pod and kite would be tethered to a winch and as the kite flies across the wind, the lift force generated is applied to the winch which is reeled out and electrical power generated. Once fully extended, the tether would be reeled in with the kite de-powered, using some of the generated energy, stored in a battery. This system can then be used as a test bed for the further development of a compact, autonomous, airborne wind energy system for off-grid applications

Control of Wave Energy Converters for Maximum Power Absorption with Time Domain Analysis

A discrete control of latching is used to increase the bandwidth of the efficiency of the Wave Energy Converters (WEC) in regular and irregular seas. When latching control applied to WEC it increases the amplitude of the motion as well as absorbed power. It is assumed that the exciting force is known in the close future and that body is hold in position during the latching time. A heaving vertical-cylinder as a point-absorber WEC is used for the numerical prediction of the different parameters. The absorbed maximum power from the sea is achieved with a three-dimensional panel method using Neumann-Kelvin approximation in which the exact initial-boundary-value problem is linearized about a uniform flow, and recast as an integral equation using the transient free-surface Green function. The calculated response amplitude operator, absorbed power, relative capture width, and efficiency of vertical-cylinder compared with analytical results

Collective Action and Social Innovation in the Energy Sector: A Mobilization Model Perspective

This conceptual paper applies a mobilization model to Collective Action Initiatives (CAIs) in the energy sector. The goal is to synthesize aspects of sustainable transition theories with social movement theory to gain insights into how CAIs mobilize to bring about niche-regime change in the context of the sustainable energy transition. First, we demonstrate how energy communities, as a representation of CAIs, relate to social innovation. We then discuss how CAIs in the energy sector are understood within both sustainability transition theory and institutional dynamics theory. While these theories are adept at describing the role energy CAIs have in the energy transition, they do not yet offer much insight concerning the underlying social dimensions for the formation and upscaling of energy CAIs. Therefore, we adapt and apply a mobilization model to gain insight into the dimensions of mobilization and upscaling of CAIs in the energy sector. By doing so we show that the expanding role of CAIs in the energy sector is a function of their power acquisition through mobilization processes. We conclude with a look at future opportunities and challenges of CAIs in the energy transition.This research was conducted under the COMETS (Collective action Models for Energy Transition and Social Innovation) project, funded by the Horizon 2020 Framework Program of the European Commission, grant number 837722

State of the Art in the Optimisation of Wind Turbine Performance Using CFD

Wind energy has received increasing attention in recent years due to its sustainability and geographically wide availability. The efficiency of wind energy utilisation highly depends on the performance of wind turbines, which convert the kinetic energy in wind into electrical energy. In order to optimise wind turbine performance and reduce the cost of next-generation wind turbines, it is crucial to have a view of the state of the art in the key aspects on the performance optimisation of wind turbines using Computational Fluid Dynamics (CFD), which has attracted enormous interest in the development of next-generation wind turbines in recent years. This paper presents a comprehensive review of the state-of-the-art progress on optimisation of wind turbine performance using CFD, reviewing the objective functions to judge the performance of wind turbine, CFD approaches applied in the simulation of wind turbines and optimisation algorithms for wind turbine performance. This paper has been written for both researchers new to this research area by summarising underlying theory whilst presenting a comprehensive review on the up-to-date studies, and experts in the field of study by collecting a comprehensive list of related references where the details of computational methods that have been employed lately can be obtained