Peter Palensky

Interfacing Power System and ICT Simulators: Challenges, State-of-the-Art, and Case Studies

With the transition toward a smart grid, the power system has become strongly intertwined with the information and communication technology (ICT) infrastructure. The interdependency of both domains requires a combined analysis of physical and ICT processes, but simulating these together is a major challenge due to the fundamentally different modeling and simulation concepts. After outlining these challenges, such as time synchronization and event handling, this paper presents an overview of state-of-the-art solutions to interface power system and ICT simulators. Due to their prominence in recent research, a special focus is set on co-simulation approaches and their challenges and potentials. Further, two case studies analyzing the impact of ICT on applications in power system operation illustrate the necessity of a holistic approach and show the capabilities of state-of-the-art co-simulation platforms.

Cosimulation of Intelligent Power Systems: Fundamentals, Software Architecture, Numerics, and Coupling

Smart grids link various types of energy technologies-such as power electronics, machines, grids, and markets-via communication technology, which leads to a transdisciplinary, multidomain system. Simulation packages for assessing system integration of components typically cover only one subdomain, while simplifying the others. Cosimulation overcomes this by coupling subdomain models that are described and solved within their native environments, using specialized solvers and validated libraries. This article discusses the state of the art and conceptually describes the main challenges for simulating intelligent power systems. This article, part 1 of 2 on this subject, covers fundamental concepts. Part 2 will appear in a future issue of IEEE Electrification Magazine and cover applications.

Towards a classification scheme for co-simulation approaches in energy systems

Simulations become more and more crucial in the field of future energy systems. This is caused by the increasing complexity of energy systems that consist of a variety of subsystems such as supply infrastructures, production, consumption, markets, communication, meteorology etc. Co-simulation tools provide the possibility to combine models of these subsystems and run them in a coordinated simulation. However, such simulations become more and more complex, making it improbable that the user of a simulation is the same person that develops the simulation system. To facilitate the communication between users and developers of co-simulation tools and to help the user to find the suitable software for his purpose, the authors suggest a typification of co-simulation tools. This is done by identifying the most relevant attributes each specified by a set of possible configurations. The utilization of the developed schemed is demonstrated by applying it to the mosaik co-simulation framework.

Multi-Agent System based voltage support by distributed generation in smart distribution network

This paper proposes distributed voltage support method for power distribution network with distributed generation using Multi-Agent System (MAS). A problem of reactive power dispatch in distribution network was considered. Contract-Net-Protocol (CNP) based scheme was used for communication and coordination between agents. A co-simulation based framework including power system simulator and agent environment was developed using socket communication to validate the proposed MAS based approach. For final validation of proposed method, modified IEEE 13 bus system with distributed generation was used. Results show the effectiveness of MAS based distributed approach for voltage support using distributed generation.

Simulation-based validation of smart grids - status quo and future research trends

Smart grid systems are characterized by high complexity due to interactions between a traditional passive network and active power electronic components, coupled using communication links. Additionally, automation and information technology plays an important role in order to operate and optimize such cyber-physical energy systems with a high(er) penetration of fluctuating renewable generation and controllable loads. As a result of these developments the validation on the system level becomes much more important during the whole engineering and deployment process, today. In earlier development stages and for larger system configurations laboratory-based testing is not always an option. Due to recent developments, simulation-based approaches are now an appropriate tool to support the development, implementation, and roll-out of smart grid solutions. This paper discusses the current state of simulation-based approaches and outlines the necessary future research and development directions in the domain of power and energy systems.

Combined data integrity and availability attacks on state estimation in cyber-physical power grids

This paper introduces combined data integrity and availability attacks to expand the attack scenarios against power system state estimation. The goal of the adversary, who uses the combined attack, is to perturb the state estimates while remaining hidden from the observer. We propose security metrics that quantify vulnerability of power grids to combined data attacks under single and multi-path routing communication models. In order to evaluate the proposed security metrics, we formulate them as mixed integer linear programming (MILP) problems. The relation between the security metrics of combined data attacks and pure data integrity attacks is analyzed, based on which we show that, when data availability and data integrity attacks have the same cost, the two metrics coincide. When data availability attacks have a lower cost than data integrity attacks, we show that a combined data attack could be executed with less attack resources compared to pure data integrity attacks. Furthermore, it is shown that combined data attacks would bypass integrity-focused mitigation schemes. These conclusions are supported by the results obtained on a power system model with and without a communication model with single or multi-path routing.

Stochastic battery model for aggregation of thermostatically controlled loads

The potential of demand side as a frequency reserve proposes interesting opportunity in handling imbalances due to intermittent renewable energy sources. This paper proposes a novel approach for computing the parameters of a stochastic battery model representing the aggregation of Thermostatically Controlled Loads (TCLs). A hysteresis based non-disruptive control is used using priority stack algorithm to track the reference regulation signal. The parameters of admissible ramp-rate and the charge limits of the battery are dynamically calculated using the information from TCLs that is the status (on/off), availability and relative temperature distance till the switching boundary. The approach builds on and improves on the existing research work by providing a straight-forward mechanism for calculation of stochastic parameters of equivalent battery model. The effectiveness of proposed approach is demonstrated by a test case having a large number of residential TCLs tracking a scaled down real frequency regulation signal.

Reserve Capability Assessment Considering Correlated Uncertainty in Microgrid

This paper presents a novel approach of assessing the required reserve capability in order to meet the forecast uncertainty dynamics in microgrid. The historical data of forecast variables is used to generate energy balance scenarios. The dynamics of these scenarios are represented as instances between capacity, ramp-rate and ramp-duration variables. A polytopic model is used to enclose these instances with its surface defining the worst case scenarios. This approach captures the correlated nature of the dynamics and provides a compact representation. In relevance, the capability of the generators and the power import from the grid are modeled as convex envelopes. A vertex based method is proposed that allocates the polytope among the resource envelopes. During this process, the operational cost is minimized while considering the resource location and the network constraints. The proposed method is examined for a microgrid test case based on the CIGRE medium voltage network. The results show new insights in the allocated demand and reserve capabilities. As an additional result, it is observed that the reserve requirements can be decreased by allocating reserves for each time instance separately as compared to the fixed percentage of load approach.

Multi-objective reactive power dispatch in distribution networks using modified bat algorithm

Integration of distributed generation in power system challenges operation and management of power distribution network. This paper presents Modified Bat Algorithm for Optimal Reactive Power Dispatch (OPRF) of distributed generation for voltage support in distribution network. An objective function with constraints of voltage, DG reactive power, thermal limits of lines is presented. A modified IEEE 37 node test feeder with variable generation was used to validate the proposed algorithm. A co-simulation setup was used in which electric grid was developed in Power system tool (DigSILENT PowerFactory) and Modified Bat Algorithm was developed in Python. Results showed that Modified Bat Algorithm is quite effective for voltage profile improvement and loss minimization.

Effective metering data aggregation for smart grid communication infrastructure

Advanced metering infrastructure (AMI) systems have been developed to perform automated meter reading, reduce peak loads, and use energy efficiently. Two issues exist regarding this system. The first issue is the communication and handling of consumer data concerning electricity collected by power utilities. The second issue is the management of communication network resources and scheduling of metering to avoid congestions and communication errors. The major device for addressing these two issues is a concentrator that acts as a data relay point in an AMI system. The concentrator collects data from the meter and sends them through communication networks. This study discusses the aggregation methods of the concentrator with respect to the aforementioned two issues and proposes a method to reduce network utilization and message size on a server. The method concatenates small smart metering messages sent from relevant meters. The traditional method aggregates and concatenates messages without numerical processing. The proposed method processes messages at the concentrator to reduce total message size and calculation cost on the server. Moreover, the method that combines the traditional and proposed methods was evaluated by considering a real-world case. These methods were simulated by using an ns-3 network simulator to evaluate their efficiency in sending messages concerning the volume of power consumption to the server. The results of the simulations show that the proposed methods reduce message size by as much as 98.5% in some cases and, by means of the concentrator, shorten the communication time between meters and the server. The proposed method can help to reduce loads on networks and servers.