Cristina Guzman

Development of a FPGA Based Real-Time Power Analysis and Control for Distributed Generation Interface

Energy coming from renewable sources has become very important nowadays, mainly because of their negligible contribution to greenhouse gas generation. A problem that then arises is how to integrate these new sources into a traditional power grid, in such a manner as to maximize the efficiency and reliability of this new distributed generation (DG) system. The hardware to do that is generally a voltage source inverter (VSI) that supplies a common load, as in single-phase residential and commercial applications. The optimizing process requires, of course, the usual power analysis. This paper presents the development and the experimental evaluation of a power control system for a single-phase grid-connected VSI including the power analysis using as processor for the control implementation a field-programmable gate array (FPGA) circuit. New hardware structures of adaptive linear neural networks (ADALINE) allow the implementation of power control algorithms and have also permitted the real-time analysis of the high-order harmonics without increasing the implementation area of the FPGA circuit. These features are ideal for novel DG power electronics interfaces that could be used not only for active power dispatch but also for harmonics and reactive power compensation. Simulation and experimental results of the proposed fixed and variable frequency schemes are included to confirm their validity.

Real-time evaluation of power quality using FPGA based measurement system

Real-time evaluation of power quality is a desired feature in research and industrial projects, especially when embedded systems are employed and/or studied. Fast Fourier Transforms FFT is commonly used to evaluate the harmonic content of electric signals. Artificial Neural Networks (ANN) are also employed for harmonics estimation with short processing time and low implementation complexity. Commercial power quality measurement systems are available and offer good performance, communication and storage capabilities, and other special features, however in most of them the real-time information is not available or it is offered with important communication delays. This paper presents the implementation of a measurement system using Xilinx FPGA target and the Adaptive Linear Neuron (ADALINE) algorithm for real-time evaluation of power quality. Experimental results show that the implemented system can be employed for power quality monitoring and embedded control applications.

Load Sharing Strategy for Autonomous AC Microgrids Based on FPGA Implementation of ADALINE&FLL

Paralleled operation of voltage-source inverters (VSIs) is currently achieved by using voltage/frequency droop control techniques which requires the knowledge of the system parameters. Otherwise, centralized control techniques with robust communication among VSIs controllers are also used. This paper presents a new control strategy which allows the load sharing between the power sources of an ac microgrid without centralized controller or any communication among the VSIs; only local measurements of voltage and output current are used. The dispatchable sources (e.g., fuel cells) of the microgrid are operated using voltage control with a direct droop scheme, and the nondispatchables or intermittent ones (e.g., wind turbine generators) are operated using power control with a complementary inverse droop scheme (D-Droop + I-Droop). The number of operating sources can be changed online without any modification needed on the VSI controllers. The proposed VSI controllers are based on the variable frequency adaptive linear neuron with frequency-locked loop for the VSIs system synchronization, voltage/power and signal estimation. Experimental results using field-programmable gate array devices for the implementation of each VSI control in the microgrid test bench demonstrated the validity of the proposition.

FPGA implementation of fixed and variable frequency ADALINE schemes for grid-connected VSI synchronization

Grid-connected Voltage Source Inverter (VSI) are essentials to integrate the Distributed Energy Resources (DER) with the utility power systems. This integration allows the increasing of the reliability and the efficiency of power systems. However, the massive utilization of VSI can generates problems into the power quality indices of power systems, especially if the power control algorithm has a poor synchronization. Therefore, a good synchronization of power control algorithm helps to keep acceptable power quality indices. This paper presents the FPGA implementation of synchronization and power control of VSI using a variable frequency ADALINE structure. The proposed ADALINE implementation is used for amplitude, frequency and phase detection of the fundamental utility voltage and its harmonics. Fundamental signal information is then employed for the synchronization and power control scheme. The fundamental and harmonics information is employed to evaluate the power flow and the power quality of VSI output current. This evaluation is very useful for power quality problems mitigation. Experimental results, using low power VSI and Xilinx FPGA system, demonstrate the validity of proposition.

Frequency Locked Loop for grid-connected VSI synchronization and power analysis

Future power systems will include the massive utilization of distributed generation mainly based on renewable energy resources. These renewable energy resources can be interconnected to the utility grid by means of power electronics converters working as Voltage Source Inverters (VSIs) which must be synchronized with the utility voltage. Synchronization methods are mandatory to make possible a correct power control and to keep an acceptable power quality. The Field Programmable Gate Array (FPGA) has been introduced in recent years as a promising target device for embedded applications especially when the parallel implementation of multiple algorithms is needed. This paper presents a new structure of the Adaptive Linear Neuron (ADALINE) with Frequency Locked Loop (ADALINE-FLL), its FPGA implementation and its experimental evaluation. The proposition has been implemented in a Xilinx FPGA device and experimentally validated using low power VSI connected to a low voltage utility.

Hardware implementation of droop control for isolated AC microgrids

Lately the integration of Distributed generation systems privileging renewable sources for offshore regions is growing to view a reduction of air pollutant emissions. Due to the intermittency of Renewable Energy Sources (RES) it must be necessary to develop a quality advanced control of the involved power interfaces to warrant the frequency and voltage required by ac off-shore loads taking into account the absence of grid connection. The droops control is a well known control strategy used for load sharing using local information of the inverters active and reactive powers. This paper presents the experimental validation of droop control strategy, using ADAptive LInear NEuron (ADALINE) signal decomposition technique for the VSI synchronization, and within a realistic scenario representing an autonomous microgrid. The advantages of the real-time operation and parallel multi task operation have been exploited using the FPGA devices, which have been employed for the hardware implementation of each VSI (Voltage Source Inverter) control. Simulation, co-simulation and experimental results are provided to verify the validity of the proposed implementation.

Modeling of residential centralized and baseboard space heating systems

The Smart grid scenario in the local side imposes a responsible utilization of energy consumption with the participative behavior of the end-users. Utilities offer nowadays many alternatives to their clients in order to prevent peak power demand that greatly affects the electricity supplier when the grid capacity is exceeded. The residential energy profiles in Nordic countries have a particular behavior concerning their energy consumption; in fact, most of the energy is employed in water heater systems and space heating systems during winter time. This paper focuses on the modeling and simulation of space heating systems commonly employed in Canadian residences. In this study, the centralized and baseboard systems models are compared in order to provide a better comprehension of technical and operational aspects. The impact of thermostat types and their setup applied to the two heating systems is evaluated in terms of the peak power and energy consumption. Simulation results demonstrate the potential of the proposed modeling approach for multi-residential energy and power analysis.

Control of voltage source inverter using FPGA implementation of ADALINE-FLL

Power electronics converters like Voltage source inverters (VSI) are normally employed as the power interface in many applications including the uninterruptible power systems (UPS) and the renewable energy systems. Both, stand alone operation and grid connected operation of VSI need an accurate voltage and frequency control (V-F control) to keep a stable operation and a good output power control. A correct V-F control is mandatory for the parallel operation of inverters like in UPS and micro-grid systems. This paper presents a control structure for voltage and frequency control of VSI based on the Adaptive Linear Neuron with Frequency Locked Loop (ADALINE-FLL). The proposed structure offers a good transient and steady state response. The proposed structure has been implemented in a Field Programmable Gate Array (FPGA) device. Simulation and experimental results demonstrate the validity of the proposition.

Evaluation of meta-heuristic optimization methods for home energy management applications

Home energy management (HEM) requires optimization techniques to solve multi-variable and multi-objective problems. The optimal use of energy, the occupants comfort, the reduction of peak power and energy cost are objectives with dissimilar variables behaviors. Their solutions increase in complexity with the number of variables which would be a challenge if the real-time response is needed. Meta-heuristics optimization techniques offer great potential for the solution of such complex optimization problems, however, their main inconvenient is that a non negligible number of iterations must be executed which is reflected in a heavy computation loops and high resources utilization. In this paper, three meta-heuristic optimization algorithms are studied and evaluated focusing on HEM applications. As the better feasible option among them, Particle Swarm Optimization (PSO) method have been selected and applied to the comfort control in the residential environment. To achieve the real-time execution of the computational burden of the MPC-PSO implementation, the advantage of VLSI parallelism is used. The FPGA in the loop co-simulation results, using real data of an occupied house, demonstrate the potential of the implemented algorithm and future multi-objective target.

Development of real-time admittance analysis system for residential load monitoring

Residential load management plays an important role in Demand Side Management (DSM) when a more optimized Smart Grid (SG) is envisaged. Actions must be done to address the local and remote control to obtain a load profile matching the available power. The identification of the working cycles of controllable and non-controllable loads, out of an aggregated load profile, is a desirable feature for the implementation of DSM technologies. A detailed knowledge of the loads can be obtained by means of intrusive or non-intrusive methods. Non-intrusive ones are preferred by customers and utilities due to the lower cost, lower hardware complexity, and easy installation. Non-Intrusive Appliances Load Monitoring (NIALM) is not a new concept in order to extract loads signature; it is lately taking more importance with the evolution of the SG technologies. Most of the literature works are devoted to the off-line NILM algorithms. Nevertheless, real-time load monitoring becomes necessary to feed the future Home Energy Management Systems (HEMS); the consumers and the utilities with accurate consumption information. This paper proposes the implementation in Field Programmable Gate Arrays (FPGAs) of real-time admittance analysis for residential load monitoring. Explorative experimental results of Non-intrusive Load Monitoring are provided and discussed.