Ramon Zamora

Real-Time Implementation of Intelligent Reconfiguration Algorithm for Microgrid

Microgrids with renewable distributed generation and energy storage offer sustainable energy solutions. To maintain the availability of energy to the connected loads, considering priority and to interrupt the smallest portion of the microgrid under any abnormal conditions, reconfiguration is critical to restore service to a section or to meet some operational requirements of dropping minimum loads. Reconfiguration is the process of modifying the microgrids topological structure by changing the status (open/close) of the circuit breakers or switches. In this work, constraints are the power balance equation and power generation limits, and we assumed that the system is designed with the entire planning and operational control criterion to meet the voltage violation and line overloading constraints. This paper offers novel real-time implementation of intelligent algorithm for microgrid reconfiguration. Intelligent algorithm is based on the genetic algorithms and has been tested on two test systems including shipboard power system and modified Consortium for Electric Reliability Technology Solutions (CERTS) microgrid. Real-time test bed utilizes real-time digital simulator and commercial real-time controllers from Schweitzer Engineering Lab. Reconfiguration algorithm has been implemented in the real time using real-time test bed, e.g., microgrid system, and satisfactory results were obtained.

Energy management and control algorithms for integration of energy storage within microgrid

This paper discusses energy management and control algorithms of microgrid with energy storage. Specific management framework within microgrid presented here includes: a) help prioritizing the renewable energy sources (RES) to provide power to local loads, b) manage battery to avoid deep-discharging and overcharging, c) maintain dc link voltage at a specified value, and d) regulate ac voltage buses at nominal voltage and frequency. The system analyzed here is adopted from Consortium for Electric Reliability Technology Solutions (CERTS) microgrid test bed. While the generation priority is from RES, the system also has a thermal generation unit to compensate for renewable energy variability and intermittency. Depending on battery state of charge (SOC) and power difference between photovoltaic (PV) and the load, the energy management can work with several modes: charging, discharging, export power, import power, and halt. The system is simulated in PSCAD platform and shows that energy management and control algorithms work as expected.

Energy management and control for islanded microgrid using multi-agents

This paper presents a multi-agent system for realtime operation of simulated microgrid using the Smart-Grid Test Bed at Washington State University. The multi-agent system (MAS) was developed in JADE (Java Agent DEvelopment Framework) which is a Foundation for Intelligent Physical Agents (FIPA) compliant open source multi-agent platform. The proposed operational strategy is mainly focused on using an appropriate energy management and control strategies to improve the operation of an islanded microgrid, formed by photovoltaic (PV) solar energy, batteries and resistive and rotating machines loads. The focus is on resource management and to avoid impact on loads from abrupt variations or interruption that changes the operating conditions. The management and control of the PV system is performed in JADE, while the microgrid model is simulated in RSCAD/RTDS (Real-Time Digital Simulator). Finally, the outcome of simulation studies demonstrated the feasibility of the proposed multi-agent approach for real-time operation of a microgrid.

Active power management in multiple microgrids using a multi-agent system with JADE

This paper presents a Multi-Agent System (MAS) to model and enable an active power management in a multiple microgrids system consisting of batteries, photovoltaic and diesel micro sources in islanded or grid-connected operation. The multi-agent system was developed in JADE (Java Agent DEvelopment Framework), a Foundation for Intelligent Physical Agents (FIPA) and a compliant open source multi-agent platform. All the six case studies presented in this paper were modeled using JADE. The cases were chosen considering the real life possible scenarios, such as: discharging the battery (boost mode), energy export from the microgrid, charging the battery (buck mode), energy import from diesel generator, energy import from the grid and the system halt. However, considering that the results for the first two cases can demonstrate the performance and features of the proposed MAS, this paper focuses on the results of these cases. The results demonstrate the effectiveness of the proposed control algorithms, necessary for coordinated control and power management, and show the possibility of autonomous built-in operation of a microgrid with a multi-agent system using JADE.

Real time implementation of microgrid reconfiguration

Reconfiguration is a control action including topology changes, load/ generation shedding and other measures to redirect power flow to the remaining unaffected loads in a microgrid. In this paper, genetic algorithm (GA) and graph theory based methodologies were used to reconfigure a network, satisfying the operational requirements and priorities of loads. Applications of the GA for reconfiguration were implemented in MATLAB and tested on 8-bus shipboard power system (SPS) and modified CERTS microgrids with consideration of distributed generation and islanding operation. Satisfactory simulations results were obtained for several possible test case scenarios in a real-time and non-real-time case study.

Impact of distributed generation with storage on electric grid stability

Penetration of distributed generation (DG) has significantly increased over the last few decades. Several states in USA have set their own target to meet significant percentage of DG penetration over the years. These requirements will have impacts on grid reliability and operational requirements given inherent intermittency for some of the DG. Energy storage integrated with DG has been proposed as a solution by several researchers to provide greater levels of flexibility and reliability. Energy storage will have impact on electric grid in several other ways including stability. This work addresses the impact of DG with storage on transient stability of the electric grid system. DG based on wind energy and biomass have been modeled based on synchronous and induction generators. Wind based DG has been modeled as both the fixed and variable speed wind energy farms. Battery and ultra-capacitor have been modeled as storage with suitable power electronics interface. MATLAB/ Simulink and PSS/E have been used as a tool for this study. Transient stability of the test systems has been assessed for different types and locations of faults as well as for different penetration levels of the DGs, with and without the energy storage devices. Transient stability have been analyzed in terms of generator rotor speed deviation, rotor angle and terminal voltage of the DGs. Results indicate that the presence of DGs and storage devices enhances the transient stability of the system in most of the cases. This work also identifies the lack of dynamic model for storage in most of the commercial available tools.

Multi-Layer Architecture for Voltage and Frequency Control in Networked Microgrids

Networked microgrid can operate in different possible configurations including: islanded microgrid, a grid-connected microgrid without a tie-line converter, a grid-connected microgrid with a tie-line converter, and networked microgrids. These possible alternative configurations and intermittent renewable energy offer challenges in designing control and management algorithms for voltage, frequency, and power in all possible operating scenarios. In this paper, a novel multi-layer architecture for control algorithm is designed based on large-signal model that enables microgrid to operate in wide range of operating points. Goals of the designed controls are to regulate voltage magnitude and frequency, as well as output power of the distributed generations. Local controls also integrate with a microgrid level energy management system or microgrid central controller (MGCC) for power and energy balance for the microgrid in islanded, grid-connected, or networked microgrid mode. The MGCC coordinates the lower level controls in centralized manner. In this paper, with the communication network failure, local lower level droop control will be activated. Designed control algorithm works with high R/X ratio and simulation results indicate satisfactory performance.

Real time implementation of intelligent reconfiguration algorithm for microgrid

Microgrids with renewable distributed generation and energy storage offer sustainable energy solutions. To maintain the availability of energy to the connected loads, considering priority and to interrupt the smallest portion of the microgrid under any abnormal conditions, reconfiguration is critical to restore service to a section or to meet some operational requirements of dropping minimum loads. Reconfiguration is the process of modifying the microgrids topological structure by changing the status (open/close) of the circuit breakers or switches. In this work, constraints are the power balance equation and power generation limits, and we assumed that the system is designed with the entire planning and operational control criterion to meet the voltage violation and line overloading constraints. This paper offers novel real-time implementation of intelligent algorithm for microgrid reconfiguration. Intelligent algorithm is based on the genetic algorithms and has been tested on two test systems including shipboard power system and modified Consortium for Electric Reliability Technology Solutions (CERTS) microgrid. Real-time test bed utilizes real-time digital simulator and commercial real-time controllers from Schweitzer Engineering Lab. Reconfiguration algorithm has been implemented in the real time using real-time test bed, e.g., microgrid system, and satisfactory results were obtained.

Design of a fuel cell-based battery extender auxiliary power unit for a vehicular microgrid

Fuel cell-based power units have increasingly become an attractive option to provide clean and efficient electricity in certain niche applications. This paper discusses the characteristics of a proton exchange membrane (PEM) fuel cell for a battery extender auxiliary power unit and explains the steps of the design process. A two-leg converter topology is proposed to control the fuel cell output, battery charge and discharge process, and the voltage of the DC link. Different operating modes of the system are analyzed and the functions of energy management system are studied. Sizing for the fuel cell, battery, power electronic converter, and passive components are presented, and the controllers of the power electronic converter are designed. Simulation case studies in both steady state and transient conditions are presented to validate the effectiveness of the presented fuel cell-based battery extender power unit and the proposed design process.

Real Time Modeling and Control of Smart Grid Systems

The real time modeling and simulation of smart grid behavior under the disturbance helps in the analysis and planning of system in order to minimize the possible damage. Real time modeling and simulations with hardware in the loop capabilities allows testing the smart grid control algorithms and new equipments.