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Requirements for Smart Grid simulation tools
Abstract
Due to the ongoing changes in the power systems and their evolution towards Smart Grids they will become tremendously complex. Those systems will contain many different components and actors that are connected among each other and located on different technological as well as conceptual levels. Analyzing the influences and impacts of new components or changes of parameters becomes more and more challenging. For that reason the importance of simulation is continuously increasing. However, Smart Grids impose new requirements on supporting tools that today's technologies are no longer suitable for. In this paper such requirements from selected Smart Grid use cases and projects are analyzed and discussed.
... Few observational studies explore how corruption influences IT-related variables despite corruption being suggested to inhibit e-government and to "make it unlikely for e-government to progress beyond basic information publishing" [75]. Despite fewer studies looking at corruption as an independent variable, anecdotal and case study evidence supports the view that corruption inhibits the potential of IT to render change in government administrations of developing countries. ...
... Formal Specification [16]: In complex system and software engineering, formal systems are used to model the interactivity of different components. In smart grid applications, a lot of effort has been on the practical aspects, therefore, attention is lacking on formalism [74,75]. ...
... How can this simulation challenge be resolved? Co-simulation is a very promising option here [3]; it allows to split the overall system into subsystems, where each subsystem is addressed by a specialized tool. A master algorithm then orchestrates the overall simulation (time stepping, data exchange, signal transformations, initialisation). ...
... A crucial concept in the coupling of continuous-time simulation models is the correct handling of the bidirectional data exchange. This aspect has been in the focus of research in the co-simulation of various systems [3], [8]- [10]. For highly dynamic systems, such a coupling is typically conducted iteratively, including several prediction and correction cycles, to arrive at a stable state of the system. ...
... Using buildings as a controllable load implies the adoption of smart devices and EMS that can respond to a communication signal from system operators. However, the assessment of the benefits of the large-scale adoption of controllable load and building DR measures requires long testing cycles and considerable investment [8]. ...
... This section describes the state of the art for smart grid cosimulation frameworks. The selected frameworks presented have been analysed on the basis of the requirements for smart grid simulation tools reported in [8] and detailed in Table 1. ...
This paper describes an open source smart grid software infrastructure for co-simulation between cloud-based energy management systems and a building energy model. The core component of the infrastructure is an API, which provides a protocol abstraction as a decoupling mechanism between the control algorithms and the building, thereby facilitating the development and testing of intelligent controllers. The open-source infrastructure can be utilised for the development and benchmarking of smart grid demand response algorithms aimed at reducing the energy consumption and the carbon footprint of buildings, while facilitating the integration of renewable energies into the power system.
... The power network simulator analyzes the operations, price forecasting, power flow, network planning shortcircuit, over-voltage, frequency, etc. In contrast, the communication simulator is used for implementing/testing/analyzing new communication protocols and technologies [12]. These are some of the simulation tools which are used widely. ...
... In [5], we introduce a Hybrid Simulator Architecture which was applied in the Integrated Co-Simulation of Power and ICT Systems for Real-Time Evaluation (INSPIRE) platform and applied it in [4] and [6]. An overview of related work is given in [7]. ...
The use of Information and Communication Technology (ICT)-based power system applications increases continually which poses new engineering challenges regarding the development, validation and management of both - the applications and the intertwined infrastructures. In this paper the need for a joint analysis of power and ICT systems for evaluating smart grid applications is discussed and a systematic validation approach is proposed. After reviewing state of the art validation techniques, a newly developed Wide-Area Monitoring, Protection and Control (WAMPAC) system is introduced. Its extensive use of wide-area communication and the combination of centralized and decentralized decision making stress the complexity of such a cyber-physical system, where the interdependency between the power system and the ICT domains are challenging to validate. Deduced from these requirements, a validation concept is proposed that comprises (i) the usage of a comprehensive smart grid reference model, (ii) a systematic and objectively verifiable generation of scenarios, and (iii) a single and multi-domain validation process using analytical, simulative and experimental techniques. For the latter, a composition of analyses using co-simulation, Hardware-in-the-Loop (HiL) simulations and an empirical test bed is outlined.
... However, the development of smart grids solutions and technologies urge for a more integrated simulation approach covering all targeted areas [16]. Nowadays, the usage of simulation as development approach gets more of interest [17], [18]. ...
... In [27], requirements for future Smart Grid simulation tools are presented. In order to keep track with the current velocity of technical and societal changes to the energy system it is imperative for the development of future Smart Grid simulation tools to not "re-invent the wheel" but rather to reuse already existing models and simulators of relevant facets and subsystems. ...
... However, the development of smart grids solutions and technologies urge for a more integrated simulation approach covering all targeted areas [16]. Nowadays, the usage of simulation as development approach gets more of interest [17,18]. ...
Renewable energy sources are key enablers to decrease greenhouse gas emissions and to cope with the anthropogenic global warming. Their intermittent behaviour and limited storage capabilities present challenges to power system operators in maintaining the high level of power quality and reliability. However, the increased availability of advanced automation and communication technologies has provided new intelligent solutions to face these challenges. Previous work has presented various new methods to operate highly interconnected power grids with corresponding components in a more effective way. As a consequence of these developments the traditional power system is transformed into a cyber-physical system, a smart grid.
... However, to the best of our knowledge, the same approach has not been applied much in the domain of the smart grid domain. It is thus clear that there is a growing need to model the key components in a smart grid by means of an elegant formal framework among other tools such as noted previously (Rohjans et al. 2014). Such a prudent approach allows for a better understanding of the domain besides allowing for systems to be verified using the given specification. ...
Purpose
Smart grid can be considered as the next step in the evolution of power systems. It comprises of different entities and objects ranging from smart appliances, smart meters, generators, smart storages, and more. One key problem in modeling smart grid is that while currently there has previously been a considerable focus on the proof of concept aspect of smart grid, there have been very few modeling attempts and even lesser attempts at formalization. To the best of our knowledge, formal specification has not been applied previously in the domain of smart grid.
Methods
Using a state-based formal specification language namely Z (pronounced as ‘Zed’), we present a novel approach to formally modeling and specify smart grid components.
Results
The modeling exercise clearly demonstrates that Z is particularly suited for modeling various smart grid components.
Conclusions
The presented formal specification can be considered as a first step towards the modeling of smart grid using a Software Engineering formalism. It also demonstrates how formal specification can be used to model complex systems in general, and the smart grid, in particular.
... A document discussing the requirements of smart grid simulation tools, including grid constraints, markets, legislation, communication infrastructure, regulation, and legislation, can be consulted in [190], paving the path for development ways of future simulators. Also, a relevant list of smart grid simulation tools can be consulted in [191]. In many of these works, a multiagent approach is commonly applied. ...
This survey provides a comprehensive analysis on recent research related to optimization and simulation in the new paradigm of power systems, which embraces the so-called smart grid. We start by providing an overview of the recent research related to smart grid optimization. From the variety of challenges that arise in a smart grid context, we analyze with a significance importance the energy resource management problem since it is seen as one of the most complex and challenging in recent research. The survey also provides a discussion on the application of computational intelligence, with a strong emphasis on evolutionary computation techniques, to solve complex problems where traditional approaches usually fail. The last part of this survey is devoted to research on large-scale simulation towards applications in electricity markets and smart grids. The survey concludes that the study of the integration of distributed renewable generation, demand response, electric vehicles, or even aggregators in the electricity market is still very poor. Besides, adequate models and tools to address uncertainty in energy scheduling solutions are crucial to deal with new resources such as electric vehicles or renewable generation. Computational intelligence can provide a significant advantage over traditional tools to address these complex problems. In addition, supercomputers or parallelism opens a window to refine the application of these new techniques. However, such technologies and approaches still need to mature to be the preferred choice in the power systems field. In summary, this survey provides a full perspective on the evolution and complexity of power systems as well as advanced computational tools, such as computational intelligence and simulation, while motivating new research avenues to cover gaps that need to be addressed in the coming years.
... In the past individual domains like power grids, automation and control, as well as Information and Communication Technology (ICT) have been quite often analyzed independently [8]. In order to address the needs and requirements of evaluating smart grid systems more integrated simulation approaches and concepts covering the aforementioned domains are necessary [15]. Advanced simulation approaches as a helpful tool for research and development but also for education of smart grid systems gain more attention nowadays [16]- [18]. ...
Renewables are key enablers for the realization of a sustainable energy supply but grid operators and energy utilities have to mange their intermittent behavior and limited storage capabilities by ensuring the security of supply and power quality. Advanced control approaches, automation concepts, and communication technologies have the potential to address these challenges by providing new intelligent solutions and products. However, the validation of certain aspects of such smart grid systems, especially advanced control and automation concepts is still a challenge. The main aim of this work therefore is to introduce a hardware-in-the-loop co-simulation-based validation framework which allows the simulation of large-scale power networks and control solutions together with real-world components. The application of this concept to a selected voltage control example shows its applicability.
... Some of these simulation tools have been combined into simulation environments which allow the co-simulation of various domains of a complex system. An overview of the requested requirements of such tools is given in [27]. There, the integration of ofthe-shelf simulators for communication systems and electrical power systems into a over 1.5 years, information about the personal circumstances of the residents can be extracted with a high probability [7]. ...
As the penetration of intelligent and ICT-enabled household devices grows, the need for better understanding of their benefits and threats rises. On the one hand, these devices enable new smart grid applications, such as demand response, which have the potential to improve the usage of energy supply and eventually lead to minimizing the electricity costs. On the other hand, the fine-grained consumption readings can be exploited to reveal private information about the household such as the type of devices and inhabitants behavior. In this paper, we present a co-simulation framework that captures two important worlds of the smart grid, namely the communication world and power world. Real data as well as simulation models are used to simulate several home appliances. The power grid simulator OpenDSS is used to implement the home level power grid, and the data communication simulator OMNeT++ is used to control the behavior of the devices as well as to implement the data communication network. Through a case study, we show how it is possible to integrate privacy approaches inside demand response for a better privacy-preserving smart metering.
... Depending on the particular requirements, the adequate simulator should be chosen. A significant number of commercially developed simulation tools are also available [4], [5]. Advanced simulators can simulate smart grids and offer the possibility to address different control strategies, communication links among elements, etc. ...
... However, to the best of our knowledge, the same approach has not been applied much in the domain of the smart grid domain. It is thus clear that there is a growing need to model the key components in a smart grid by means of an elegant formal framework among other tools such as noted previously [156]. Such a prudent approach allows for a better understanding of the domain besides allowing for systems to be verified using the given specification. ...
A smart grid can be considered as a complex network where each node represents a
generation unit or a consumer, whereas links can be used to represent transmission
lines. One way to study complex systems is by using the agent-based modeling (ABM)
paradigm. An ABM is a way of representing a complex system of autonomous agents
interacting with each other. These models can well depict a smart grid in terms of
its various components, their behaviors, and communication among them for energy
distribution and management.
This research carries out an in-depth study of the modeling and simulation of
smart grid from an agent-based and complex system perspective. It begins by systematically review the literature of smart grid from two core directions i.e. ABM
and Complex system. This study covers a large number of scientific literature, their
key contributions, and open research problems. Based on the review, we noted that
number of studies have been carried out in smart grid making use of ABM parading. However, to the best of our knowledge, none of these studies have focused on
the specification aspect of ABM. An ABM specification is important not only for
understanding but also for replication of the model.
In this study, we focus on development and specification of ABM for the smart
grid. We propose an ABM by using a combination of agent-based and complex
network-based approaches. For ABM specification, we use ODD and DREAM specification approaches. We analyze these two specification approaches via qualitatively
and quantitatively. Extensive experiments demonstrate that DREAM is a most useful approach as compared with ODD for modeling as well as for replication of models
for the smart grid.
... Experience from these different approaches shows that hybrid concepts, which integrate extensive simulation capabilities with real-world lab set-ups, allow for more comprehensive tests of novel smart grid components, especially before a roll-out to the field. Following the requirements for future smart grid simulation tools outlined in [14], the key for developing future smart grid simulation tools is to not "re-invent the wheel", but rather to re-use already established models and simulators. As such, the authors of this work aim to develop a flexible solution for hardware integration into CPES simulations, for practical smart grid applications with a focus on lab evaluation and certification of related components. ...
Modeling and simulation are essential for the development and assessment of new technologies for complex cyber-physical systems, both in academia and industry. One particular instance of such complex systems are novel energy systems. They comprise a variety of heterogeneous physical domains (electricity, thermal, gas, etc.), modeled as time continuous dynamic systems, and time discrete communication and control systems. Tools and solutions based on co-simulation concepts for such cyber-physical energy systems (CPES) have been developed in recent years. This paper focuses on the need for real-time hardware integration into CPES simulation, identified from recently conducted research projects. From those projects – presented as use cases – relevant actors are identified and their interaction and data exchange is discussed. Resulting requirements are presented for the CPES simulation and the hardware to be integrated. The handling of heterogeneous laboratory hardware is discussed and a simplification in the form of a hardware abstraction layer is proposed.
The development of smart energy systems infrastructure has been initiated with deployment of smart meters from the beginning of this millennium. The smart grids incorporated into a hybrid system with optimal energy mix are partly solution to the severe environmental problems, the scarcity of fossil fuels and the constant growth of energy needs. The optimal energy mix contains renewable energy sources, energy efficiency solutions, and energy storage options. In more complex multi energy systems the monitoring and control of the all energy flows (electricity, heat, gas) has been crucial for the evolution to the smart grids as a part of the wider smart energy systems infrastructure, especially in smart cities. In this paper the three step investment minimization problem of the total costs for the instalment of the smart energy system has been formulated. The results show yearly electricity and heat balance (and even hourly) obtained using HOMER software tool. The developed model together with available software can support the decision making in planning phase of the smart energy subsystem.
Smart grid and cloud computing architectures have been perfectly suiting each other naturally. As a result, over the years cloud computing architectures have dominated the implementations of smart grid applications to address computing needs. However, due to continuing additions of heterogeneous (sensing and actuating) devices, emergence of Internet of Things (IoT), and massive amount of data collected across the grids for analytics, have contributed to the complexity of smart grids, making cloud computing architectures no longer suitable to provide smart grid services effectively. Edge and Fog computing approaches have relieved the cloud computing architectures of problems related to network congestion, latency and locality by shift of control, intelligence and trust to the edge of the network. In this paper, a systematic literature review is used to explore the research trend of the actual implementations of edge and fog computing for smart grid applications. A total of 70 papers were reviewed from the popular digital repositories. The study has revealed that, there is significant increase in the number of smart grid applications that have exploited the use edge and fog computing approaches. The study also shows that, considerable number of the smart grid applications are related to energy optimizations and intelligent coordination of smart grid resources. There are also challenges and issues that hinder smooth adoption of edge and fog computing for smart grid applications, which include security, interoperability and programming models.
The complexity of energy systems is increasing continuously. The main driver for this is the number of components and systems that are involved in grid operation, optimization, and protection. Moreover, various interconnections among different components exist so that the behavior of one has impacts on many. This raises the requirement to thoroughly test and validate components and systems to be integrated in the overall infrastructure. In order to address the dependencies it is not sufficient to apply stand-alone approaches but to follow co-simulation. Furthermore, hard- and software have to be combined to large-scale simulation scenarios. Thus, real laboratory components have to be connected and integrated with software-based simulations. In this paper the authors present a low-cost and standard-compliant co-simulation approach that integrates controllers for real hardware devices with software simulators through the mosaik framework.
Power flow simulators are indispensible when simulating and assessing future energy system scenarios potentially comprising vast numbers of actors, devices, markets, environmental phenomena etc. While open source power flow simulators are an appealing choice – as they come free of charge – commercially available power flow simulation and optimization suites have the clear benefit of being well established and trusted by the industry. Open source implementations often lack validation against these “trusted” outputs. In this paper we will demonstrate and discuss the integration and exchange of different (commercial as well as open source) power flow simulators with the co-simulation framework mosaik for the sake of comparing and possibly benchmarking the output of open source simulators.
The large-scale integration of distributed energy resources into a complex cyber-physical system demands proper automation platforms for monitoring, control, optimization and reconfiguration, addressing intelligent energy systems. This paper discusses the use of multi-agent systems as a suitable solution to address this challenge by analyzing their benefits when applying them to the field of Smart Grids and surveying existing works and initiatives. The principles and use cases established in the MASGrid project illustrate the application of multi-agent technology in active power distribution systems.
The ever increasing deployment of photovoltaic systems and other distributed energy resources causes massive challenges for utility operators in terms of planning and operation. Through promising new intelligent methods, i.e., Smart Grids, existing infrastructure can be used in a more efficient way, allowing a higher penetration of distributed and renewable resources. Standardized and common communication systems are important keys to realize such intelligent methods. The IEC 61850 interoperability approach is one of the most promising solutions for multi-vendor information exchange in electric power systems today. However, many of today's photovoltaic inverters do not have an IEC 61850 capable interface. The main aim of this paper therefore is to present and discuss a cost effec-tive way of upgrading such inverters through a standard-compliant gateway device, which implements IEC 61850 functions, thus making the inverter's functionalities accessible and ready for the future Smart Grid.
Twin support vector machines (TWSVM) is based on the idea of proximal SVM based on generalized eigenvalues (GEPSVM), which determines two nonparallel planes by solving two related SVM-type problems, so that its computing cost in the training phase is 1/4 of standard SVM. In addition to keeping the superior characteristics of GEPSVM, the classification performance of TWSVM significantly outperforms that of GEPSVM. However, the stand-alone method requires the solution of two smaller quadratic programming problems. This paper mainly reviews the research progress of TWSVM. Firstly, it analyzes the basic theory and the algorithm thought of TWSVM, then tracking describes the research progress of TWSVM including the learning model and specific applications in recent years, finally points out the research and development prospects.
Interoperability of systems is not a cookie-cutter-function. There are various levels of interoperability between two systems ranging from no interoperability to full interoperability. In the technical domain, various models for levels of interoperability already exist and are used successfully to determine the degree of interoperability between information technology systems. However, such models are not yet established in the domain of conceptual modeling. This paper introduces a general model dealing with various levels of conceptual interoperability that goes beyond the technical reference models for interoperable solutions. The model is intended to become a bridge between the conceptual design and the technical design for implementation, integration, or federation. It should also contribute to the standardization of V&V procedures as well as to the documentation of systems that are designed to be federated. It is furthermore a framework to determine in the early stages of the federation development process whether meaningful interoperability between systems is possible. To this end, the scope of the model goes beyond the implementation level of actual standards, which focus on the exchange of data using standardized formats and interfaces. Another practical application of the model is, that it enhances the only recently published DoD Net-Centric Data Strategy for the Global Information Grid (GIG) and is directly applicable to derive necessary metadata to reach the DoD Data Goal to "enable Data to be understandable."
The objective of this paper is to discuss the design and implementation of a multi-agent system that provides intelligence to a distributed smart grid - a smart grid located at a distribution level. A multi-agent application development will be discussed that involves agent specification, application analysis, application design and application realization. The message exchange in the proposed multi-agent system is designed to be compatible with an IP-based network (IP = Internet Protocol) which is based on the IEEE standard on Foundation for Intelligent Physical Agent (FIPA). The paper demonstrates the use of multi-agent systems to control a distributed smart grid in a simulated environment. The simulation results indicate that the proposed multi-agent system can facilitate the seamless transition from grid connected to an island mode when upstream outages are detected. This denotes the capability of a multi-agent system as a technology for managing the microgrid operation.
For 100 years, there has been no change in the basic structure of the electrical power grid. Experiences have shown that the hierarchical, centrally controlled grid of the 20th Century is ill-suited to the needs of the 21st Century. To address the challenges of the existing power grid, the new concept of smart grid has emerged. The smart grid can be considered as a modern electric power grid infrastructure for enhanced efficiency and reliability through automated control, high-power converters, modern communications infrastructure, sensing and metering technologies, and modern energy management techniques based on the optimization of demand, energy and network availability, and so on. While current power systems are based on a solid information and communication infrastructure, the new smart grid needs a different and much more complex one, as its dimension is much larger. This paper addresses critical issues on smart grid technologies primarily in terms of information and communication technology (ICT) issues and opportunities. The main objective of this paper is to provide a contemporary look at the current state of the art in smart grid communications as well as to discuss the still-open research issues in this field. It is expected that this paper will provide a better understanding of the technologies, potential advantages and research challenges of the smart grid and provoke interest among the research community to further explore this promising research area.
The vision of a smart grid is predicated upon pervasive use of modern digital communication techniques to today's power system. As wide area measurements and control techniques are being developed and deployed for a more resilient power system, the role of communication network is becoming prominent. Power system dynamics gets influenced by the communication delays in the network. Therefore, extensive integration of power system and its communication infrastructure mandates that the two systems are studied as a single distributed cyber-physical system. This paper proposes a power/network co-simulation framework which integrates power system dynamic simulator and network simulator together using an accurate synchronization mechanism. The accuracy is tunable based on the time-scale requirements of the phenomena being studied. This co-simulation can improve the practical investigation of smart grid and evaluate wide area measurement and control schemes. As a case study an agent-based remote backup relay system is simulated and validated on this co-simulation framework.
In the future smart city, new information and communication technologies will enable a better management of the available resources. The future smart grid infrastructure is emerging as a complex system where fine-grained monitoring and control of energy generating and/or consuming entities within the electricity network is possible. This will result to better approaches that will boost energy efficiency. A simulation of a dynamic ecosystem such as the smart city, will enable us to test new concepts and resource-optimization approaches. Therefore we have analyzed, designed, and build a simulator based on software agents that attempts to create the dynamic behavior of a smart city. It simulates discrete heterogeneous devices that consume and/or produce energy, that are able to act autonomously and collaborate. The behavior of these devices and their groupings e.g. smart houses, has been modeled in order to map as near as possible the real behavior patterns of the respective physical objects.
The increase in renewable power generation causes an overall decrease in conventional power generation from large-scale and highly predictable fossil power plants. Aside from market-based provision of active power schedules, these power plants are crucial for the provision of short-term automatic ancillary services such as frequency and voltage control. Substituting these plants for renewable generation units requires the latter to be capable of providing these ancillary services in order to guarantee a reliable and stable power supply. In this paper we present an integrated approach for identifying distributed coalitions of agents representing units capable of providing frequency response reserve. We present a method for calculating the individual droop control parameters of each participating device taking into account opportunity costs, device specific reliabilities (e.g. for photovoltaic or wind installations) as well as the small-signal stability of such a coalition for frequency response reserve.
Smart Grids rely on the use of ICT for managing large numbers of active components and sensors to keep demand and generation of electricity at equilibrium while operating multiple resources within their operational limits. Due to the distributed nature of these resources, their heterogeneity as well as their sheer number, is a challenging task. Control strategies as well as novel paradigms need to be developed and thoroughly evaluated through extensive simulations. In order to yield scientifically sound and reliable results, these simulations have to rely on valid and (ideally) established models, e.g., from industry. Therefore, it is desirable to reuse these models as often as possible by combining them into new, potentially large-scale test scenarios. The introduced mosaik framework presents a flexible architecture as well as a powerful modeling and specification language to automate the process of composing existing models and simulation platforms into large-scale simulation scenarios.
This paper provides an overview of the Ecogrid EU project, which is a large-scale demonstration project on the Danish island Bornholm. It provides Europe a fast track evolution towards smart grid dissemination and deployment in the distribution network. Objective of Ecogrid EU is to illustrate that modern information and communication technology (ICT) and innovative market solutions can enable the operation of a distribution power system with more than 50% renewable energy sources (RES). This will be a major contribution to the European 20-20-20 goals. Furthermore, the proposed Ecogrid EU market will offer the transmission system operator (TSO) additional balancing resources and ancillary services by facilitating the participation of small-scale distributed energy resources (DERs) and small end-consumers into the existing electricity markets. The majority of the 2000 participating residential customers will be equipped with demand response devices with smart controllers and smart meters, allowing them to respond to real-time prices based on their pre-programmed demand-response preferences.
Open source software has a leading role in research on simulation technology for electrical power systems. Research simulators demonstrate new features for which there is nascent but growing demand not yet provided for by commercial simulators. Of particular interest is the inclusion of models of software-intensive and communication-intensive controls in simulations of power system transients. This paper describes two features of the ORNL power system simulator that help it meet this need. First is its use of discrete event simulation for all aspects of the model: control, communication, and electro-mechanical dynamics. Second is an interoperability interface that enables the ORNL power system simulator to be integrated with existing, discrete event simulators of digital communication systems. The paper concludes with a brief discussion of how these aspects of the ORNL power system simulator might be inserted into production-grade simulation tools.
This article discusses recent trends in Smart Grid technology. Three selected aspects are (1) distributed information technology (IT), used for smart metering and multi-agent based controls, (2) big-data, resulting out of metering, sensors and other IT-enabled sources of information, and (3) an intelligent demand side, where demand response serves as contribution to grid services. New elements in the grid, most notably large numbers of fluctuating renewable energy sources, and new functionality like markets make it necessary to introduce methods and technologies from other domains that already faced such changes.
The increase in renewable power generation causes an overall decrease in conventional power generation from large-scale and highly predictable fossil power plants. Aside from market-based provision of active power schedules, these power plants are crucial for the provision of short-term automatic ancillary services such as frequency and voltage control. Substituting these plants for renewable generation units requires the latter to be capable of providing these ancillary services in order to guarantee a reliable and stable power supply. In this paper we present an integrated approach for identifying distributed coalitions of agents representing units capable of providing frequency response reserve. We present a method for calculating the individual droop control parameters of each participating device taking into account opportunity costs, device specific reliabilities (e.g. for photovoltaic or wind installations) as well as the small-signal stability of such a coalition for frequency response reserve.
The EcoGrid EU is a large-scale demonstration on the Danish island Bornholm. The aim is to demonstrate a Smart Grids solution to operate a power system with more than 50 % renewable energy, including a mix of variable distributed energy resources (i.e. wind, solar, biomass, biogas, and CHP) and energy storage technologies such as heat pumps, district heating and batteries from EVs. Out of the 28 000 electricity customers on Bornholm, 2000 residential consumers will participate with flexible demand. A major part of the participants will be equipped with residential demand response devices with intelligent controllers, enabling customers to respond to real-time prices and allow users to pre-program their automatic demand-response preferences. This paper presents the concept of a real-time market and information architecture, which gives numerous small end-users and local producers of distributed energy new options for offering TSO additional balancing and ancillary services.
The smart power grid will extensively rely on networked control to increase efficiency, reliability, and safety; to enable plug-and-play asset integration, such as in the case of distributed generation and alternative energy sources; to support market dynamics as well as reduce peak prices and stabilize costs when supply is limited. In turn, network control requires an advanced communication infrastructure with support for security and real-time communication. This paper reviews the major challenges in smart grid communication, and proposes PowerNet, a system of heterogeneous yet interoperable networks that provides adequate levels of realtime performance, reliability, and security, and that exploits current investments in software and hardware. Smart grid communication involves disparate designs and complex issues, and it can be effectively evaluated through co-simulation. The paper describes a co-simulator that combines extensive support for power device models and for communication models, and highlights current work in the area.
Nowadays, research, politics, and utilities are on the move to create the new power distribution and transmission grid, the so called Smart Grid. Over the last years, various projects and initiatives have started to provide first results and the topic has changed form a research and development oriented one to being used in daily utility practice. But one particular aspect is that the focus most of the times lies with the electric side of the commodities and energy supply only. From a system point of view, it would be beneficial also to cover the aspects of gas and water in the Smart Grid, too. This paper discusses the idea of a holistic System-of-a-System (SoS) aspect with special regards to the Information and Communication Technologies (ICT) and automation concepts applied. It outlines the applicability of the existing electrotechnical and automation standards within the future critical infrastructure.
In order to reduce CO2 emissions renewable and distributed energy resources need to be integrated into the electric energy systems. The transformation of the electricity grids into a “Smart Grid” is required. In order to realise this change appropriate components and the corresponding management and automation concepts have to be developed. However, a holistic and standard-based design and test environment for automation and control devices covering the whole development process in Smart Grid systems is currently missing.
The core aim of this article is to introduce and present a development, test and validation environment for automation and control devices from an information and communication point of view using the real-time hardware-in-the-loop approach. A special focus of this work will be on the validation of DER control functions under realistic conditions using real-time Controller-Hardware-in-the-Loop (CHIL) tests as appropriate method.
This paper describes a co-simulation framework for analyzing the interactions between advanced power systems and the digital communication networks that are used to monitor and control those systems. This analysis capability is critical to the successful design, verification, and operation of such systems as both the influences from each side will be considered. The framework, named VPNET, harnesses two tools - the Virtual Test Bed (VTB) for dynamic simulation of the multi-physics power system and OPNET for realistic representation of the communications network, including a wide range of protocols. Each part of the VPNET co-simulation framework is explained in detail, including strengths, weaknesses and challenges. The capabilities of VPNET are illustrated through a case study.
Autonomous power systems for villages and regions exploiting local renewable energy sources has a large potential with many sites throughout the world where such systems will provide energy at lower costs than conventional diesel-only systems. The system configurations of these systems will often be complex due to the mix of generation and desire to optimise the utilisation of the renewable energy potential. It involves the control of systems with large amounts intermittent power production, interaction with conventional types of generation and often also control of the consumption and energy storage. During the feasibility, design and evaluation phases of projects that implement such systems it is essential to be able to reliably assess the technical performance of the system. The simulation package, IPSYS, has been developed as tool for analysing such systems. The emphasis has been the ability to calculate the performance in terms of e.g. fuel consumption as well as the active and reactive power flows and grid voltage levels. IPSYS also includes modelling of thermal systems that can have waste heat as input and thermal desalination units as output and a freshwater balance where the freshwater is produced by the thermal units or by electrical driven units to meet a certain demand. Another key feature of IPSYS is the modelling of the supervisory control of the complete system. IPSYS allows for very flexible modelling of the supervisory system controller. IPSYS has been developed to allow time steps down to few seconds in order to allow accurate modelling of the control of the system. The component models can also supply many signals that the controllers can access and new components or modification of existing components are easily included in the package. This is combined with the feature that change of controller modules is done in the setup files. This means that the package does not need to be recompiled in order to include new controllers. The paper will present a simple case illustrating the main features of IPSYS (multi bus bars, multi domains, multi controllers). It will further show results from a large simulation case that is currently being used to investigate and compare the performance of IPSYS with other simulation packages.
Co-Simulation is a general approach to simulate coupled technical systems. In a master-slave concept the slaves simulate sub-problems whereas the master is responsible for both coordinating the overall simu-lation as well as transferring data. To unify the inter-face between master and slave the FMI for Co-Simulation was developed. Using FMI a master was implemented with simple and advanced algorithms which can be applied depending on the properties of the involved slave simulators. The master was tested amongst others by coupling with SimulationX.
The implementation of highly realistic real-time, massive, online, multi-time frame simulations is proposed as a means for building a common vision of smart grid functions among politicians, regulators, managers, operators, engineers, and technicians. These massive simulations will include hundreds of participants that play roles of reliability coordinators, transmission operators, distribution operators, power plant operators, and substation operators. These highly visible drills can demonstrate how the new smart grid systems, people, and processes can all work together economically and reliably. The industry, especially smart grid system designers, can get feedback from low cost, safe, and easily configurable simulations instead of waiting for expensive and hardwired deployments. Direct load control of millions of customer appliances is identified as a silver bullet to build self-healing and maximal flow smart grids that can accommodate large penetrations of intermittent wind and solar generation and rapid load growth due to plug-in electric vehicles. The paper recommends that up to 50% of load be controlled with minimal inconvenience to customers to potentially enhance angle, voltage, frequency, and thermal stability. An expert operator decision model is described with a view to helping system developers build operator-centered and friendly smart grid control systems.
Industrialization and economic development have historically been associated with man's ability to harness natural energy resources to improve his condition. Based on this definition, two industrial revolutions occurred in the 18th and 19th centuries, where natural resources such as coal (first revolution) and petroleum (second revolution) were widely exploited to produce levels of energy far beyond what could be achieved by human or animal muscle power. Furthermore, modern power distribution systems made abundant energy reliably available and relatively independent from the plant location. More than two centuries of past industrialization exploited nonrenewable energy resources, however, often with undesirable side effects such as pollution and other damage to the natural environment. In the second half of the 20th century, extraction of energy from nuclear processes grew in popularity, relieving some demands on limited fossil fuel reserves, but at the same time, raising safety and political problems. Meeting the global demand for energy is now the key challenge to sustained industrialization.
Exciting yet challenging times lie ahead. The electrical power industry is undergoing rapid change. The rising cost of energy, the mass electrification of everyday life, and climate change are the major drivers that will determine the speed at which such transformations will occur. Regardless of how quickly various utilities embrace smart grid concepts, technologies, and systems, they all agree onthe inevitability of this massive transformation. It is a move that will not only affect their business processes but also their organization and technologies.
Providing, operating and maintaining the infrastructure for continuously growing and changing electric energy systems are the technological key challenges for our society in the next years and decades. Multi-Agent Systems represent a promising approach able to realize/implement the above described functionalities and services in a power distribution network. In this paper, we present an automation agent approach and the related system architecture for handling such dynamic networks. On the one side, an agent provides monitoring and diagnostics abilities required for the robust functioning of components in the distributed environment. On the other side, to coordinate energy consumption, keep nodal voltages within predefined bounds and avoid overstressing of equipment, the system also provides anticipation services. Monitoring customer demands and applying statistical methods incorporated as behaviors in the related agents, the system is able to forecast network behavior and optimize its performance. Moreover, due to its vital importance, the system offers to the human user a complete overview of the agent's activities as well as a possibility to supervise its actions through an adequate Human Machine Interface (HMI). The presented approach is currently in the development phase and will be tested in the AIT power distribution laboratory.
Communication Infrastructure for the Smart Grid: A Co-Simulation Based Study on Techniques to Improve the Power Transmission System Functions with Efficient Data Networks
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