Showing papers by "Geza Joos published in 2020"

Design and Real-Time Implementation of a Centralized Microgrid Control System With Rule-Based Dispatch and Seamless Transition Function

Abstract: With reference to the newly released microgrid standards, design and real-time implementation of a centralized microgrid control system is presented in this article. In the grid-connected mode, the utility grid will provide the voltage and frequency reference at the point of connection. The assets within the microgrid will follow power command references provided by the control system. In the islanded mode, the energy storage system (ESS) can provide the voltage and frequency reference to all other generators. Based on the state-of-charge of the ESS, a rule-based dispatch is proposed, with priority given to diesel generator and then the storage in the middle state of charge range. To alleviate power fluctuations, meet smooth planned islanding requirement, and compensate for the feeder losses ignored in dispatch algorithm, a supplementary slack-bus power control based on closed-loop feedback and first-order filter is proposed. The potential of the storage system in firming short-time power fluctuation and providing long-term load shifting capabilities is exploited. An emergency dispatch function for unplanned islanding considering the speed of response limitation of a diesel generator is also proposed. The proposed control strategy is implemented and tested on a controller hardware-in-the-loop test bench. It demonstrates the capability of the control system to reduce load shedding and renewable curtailment, and to implement power management at the point of interconnection.

Spatio-Temporal Flexibility Management in Low-Carbon Power Systems

Abstract: The deepening penetration of renewable power generation is challenging how the minute balancing of supply and demand is carried out by power system operators. Several proposals to short-term operational planning rely on robust optimization to offer guarantees on the ability of the operator to meet a wide array of possible scenarios. The main downside of these approaches is their conservative results whose operating costs and/or carbon footprint may be sub-economical. Such results come by because these approaches immunize their solutions for the required level of security against realizations of potential events within their uncertainty set. Moreover, these approaches also often ignore the inherent time and spatial couplings of wind and solar generation variability. In this article, we seek to reduce the conservativeness of the robust solution by proposing the concept of spatio-temporal flexibility requirement envelopes. We show how it is able to efficiently capture and model the temporal trends and spatial correlation of multisite renewable generation and load. A mathematical program for energy scheduling is also developed using the projections of this envelope. We showcase the use and advantages of spatio-temporal flexibility requirement envelopes and their associated scheduling approach in a microgrid and on a modified IEEE Reliability Test System.

Adaptive Coordination for Power and SoC Limiting Control of Energy Storage in an Islanded AC Microgrid With Impact Load

Abstract: Isochronous controlled battery energy storage system (ESS) can maintain constant frequency in an islanded ac microgrid, but its power and state of charge (SoC) may go beyond limit due to intermittent renewable energy resources and impact load change. This paper introduces a control strategy integrated with bang-bang and backlash mechanism to coordinate distributed energy resources (DERs). When overloading will take place, ESS will change from isochronous control to droop control, with droop gain varying based on bang-bang control, by which the overloaded power will be spontaneously transferred from ESS to other DERs. Moreover, frequency will be automatically restored when impact load disappears, which eliminates the effort of secondary frequency control. When SoC of ESS comes to limit, the diesel generator will change from droop control to isochronous control, whereas ESS will adopt virtual inertia and grid-supporting droop control to help stabilize frequency. A backlash mechanism is also employed to latch the control mode near SoC limit. Comprehensive tests on real-time simulator demonstrated the effectiveness of the proposed control strategy.

PMU Signals Responses-Based RAS for Instability Mitigation Through On-The Fly Identification and Shedding of the Run-Away Generators

Abstract: This paper presents a new method of instability detection and subsequent stabilization of the power system network using a proposed multi-shot remedial action scheme (RAS) that can extemporaneously detect critical generators based on the dynamic states of generator computed from the terminal phasor measurement units. The instability detector is a moving window classifier that predicts impending instability using rate of change of individual generator transient energy indices evaluated from the d–q axis voltage as well as conventional severity indices based on generator angle and frequency. A comparative performance analysis of a spectral feature based ensemble decision tree classifier with a multivariate long short-term memory network is also presented. The proposed RAS identifies critical generators through individual machine transient energy formulation and recursive coherency matrix, evaluated solely from system-wide generator dynamic states, and maintains stability by tripping adaptively the run-away generators. Performance evaluation of the proposed scheme has been made on IEEE 39-bus network and it has been demonstrated that the proposed RAS is robust with regards to instability prediction and it can effectively identify critical generators and stabilize the network by tripping the same.

Decision tree-based optimization for flexibility management for sustainable energy microgrids

Abstract: In this paper, we apply a flexibility based operational planning paradigm to microgrid energy dispatch. The classic energy dispatch problem with energy storage and dispatchable thermal generation assets requires the solution of mixed-integer optimization problems. Such approaches are not amenable to most remote microgrids and practical field microgrid implementations, where controls are rule-based and typically implemented by programmable logic controllers. Albeit such rule-based dispatch controls are always feasible, they cannot optimize fully over the availability of renewable generation and asset capacities of microgrids, especially energy storage. In this paper we propose a systematic method to generate the microgrid dispatch rule base with the objective of matching as much as possible the control performance obtained by full mixed-integer optimization. To achieve this we develop a rigorous control mapping method based on decision trees. The numerical results demonstrate that the decision tree-based dispatch strategy can provide feasible and near optimal dispatch decisions for microgrids. Its computational efficiency is very high, a feature promising for real-time in-field implementation.

A Rule Based EMS for Fast Charging Station with CHIL Implementation

Abstract: Fast charging station caters to the need for high power requirement for electric vehicles (EVs) charging in a short duration. Integration of local distributed generation resources can reduce the impact of the fast charging station on the grid. However, the intermittency of the distributed generation calls in for energy management system. This paper envisages the development of a rule based-modal control design for the energy management system (EMS) of a multi charger level 3 (50 kW) DC fast charging station (FCS). The paper presents the offline and controller hardware in the loop (CHIL) validation of the implemented design. Finally, three scenarios with respect to available grid energy are explored including the study of power sizing of ESU in order to provide a system level optimization for the performance of the EMS.

A Modular Generic Microgrid Controller Adaptive to Different Compositions

Abstract: In this paper, a modular generic microgrid controller adaptive to different compositions and applications is presented. The rule-based dispatch strategy is designed to maintain power balance, follow the power reference at the point of interconnection, while reducing renewable generation curtailment and load shedding. The main feature of the controller is the modular architecture and the adaptivity to the removal or addition of assets. When assets are removed from microgrids, the dispatch strategy can adapt to this variation by setting their power constraints as zero. When more assets of the same type are added, they can be aggregated as one group and managed with a weighted and queuing algorithm to distribute power among the group members.

Harmonic Analysis Considerations for SVS Design

Abstract: Static Var System (SVS) installations are prevalent and play an important role in voltage regulation and stabilization. A design concern for SVS installations is the introduction of harmonics due to inherent operation and amplification of existing power system harmonic distortion. Analysis of the harmonic interaction between proposed SVS installations and the power system is important. This paper presents information and guidelines for SVS design with specific emphasis on harmonic analysis. The main topics addressed are the design input data, the measurement requirements and the impact on SVS design configuration and component rating.

Regression-Based Wintertime Energy Consumption Prediction for Cold Load Pick-Up Management

Abstract: Thermostatically Controlled Loads (TCL) have a significant impact on Cold Load Pick-up (CLPU) during distribution system service restoration. Widespread deployment of smart meter devices opens up new opportunities for data-driven load modelling. In this paper, we compare several linear regression approaches to robust short term prediction of hourly energy consumption as a function of the outdoor temperature during the low-temperature season. The goal is to estimate the energy that will not be delivered during an outage for the purpose of a further estimation of the CLPU peak and duration for consumers with TCLs. The prediction is based on smart meter load data and outdoor temperature data. The performance of the proposed regression approaches is analyzed for 25 residential homes from real measured data. Prediction is performed on an hourly basis. The quality of the regression results is compared with the Naive forecast benchmark method. The results show that autoregression approach outperforms the other methods, however, since this approach is highly depended on the existence of the sequence of the previous load measurements, as an alternative approach, ENS prediction is successfully performed using only temperature data.