Chi-Cheng Peter Chu

Distributed Optimal Energy Management in Microgrids

Energy management in microgrids is typically formulated as a nonlinear optimization problem. Solving it in a centralized manner does not only require high computational capabilities at the microgrid central controller (MGCC), but may also infringe customer privacy. Existing distributed approaches, on the other hand, assume that all generations and loads are connected to one bus, and ignore the underlying power distribution network and the associated power flow and system operational constraints. Consequently, the schedules produced by those algorithms may violate those constraints and thus are not feasible in practice. Therefore, the focus of this paper is on the design of a distributed energy management strategy (EMS) for the optimal operation of microgrids with consideration of the distribution network and the associated constraints. Specifically, we formulate microgrid energy management as an optimal power flow problem, and propose a distributed EMS where the MGCC and the local controllers jointly compute an optimal schedule. We also provide an implementation of the proposed distributed EMS based on IEC 61850. As one demonstration, we apply the proposed distributed EMS to a real microgrid in Guangdong Province, China, consisting of photovoltaics, wind turbines, diesel generators, and a battery energy storage system. The simulation results demonstrate the effectiveness and fast convergence of the proposed distributed EMS.

Optimal Residential Demand Response in Distribution Networks

Demand response (DR) enables customers to adjust their electricity usage to balance supply and demand. Most previous works on DR consider the supply-demand matching in an abstract way without taking into account the underlying power distribution network and the associated power flow and system operational constraints. As a result, the schemes proposed by those works may end up with electricity consumption/shedding decisions that violate those constraints and thus are not feasible. In this paper, we study residential DR with consideration of the power distribution network and the associated constraints. We formulate residential DR as an optimal power flow problem and propose a distributed scheme where the load service entity and the households interactively communicate to compute an optimal demand schedule. To complement our theoretical results, we also simulate an IEEE test distribution system. The simulation results demonstrate two interesting effects of DR. One is the location effect, meaning that the households far away from the feeder tend to reduce more demands in DR. The other is the rebound effect, meaning that DR may create a new peak after the DR event ends if the DR parameters are not chosen carefully. The two effects suggest certain rules we should follow when designing a DR program.

Real-Time Energy Management in Microgrids

Energy management in microgrids is typically formulated as an offline optimization problem for day-ahead scheduling by previous studies. Most of these offline approaches assume perfect forecasting of the renewables, the demands, and the market, which is difficult to achieve in practice. Existing online algorithms, on the other hand, oversimplify the microgrid model by only considering the aggregate supply-demand balance while omitting the underlying power distribution network and the associated power flow and system operational constraints. Consequently, such approaches may result in control decisions that violate the real-world constraints. This paper focuses on developing an online energy management strategy (EMS) for real-time operation of microgrids that takes into account the power flow and system operational constraints on a distribution network. We model the online energy management as a stochastic optimal power flow problem and propose an online EMS based on Lyapunov optimization. The proposed online EMS is subsequently applied to a real-microgrid system. The simulation results demonstrate that the performance of the proposed EMS exceeds a greedy algorithm and is close to an optimal offline algorithm. Lastly, the effect of the underlying network structure on energy management is observed and analyzed.

On the Identification Device Management and Data Capture via WinRFID1 Edge-Server

In this paper, we present a layered architecture and approach for creating a high performance edge server called reader coordinator (RC) for managing variety of automatic identification hardware such as radio frequency identification (RFID) reader, RFID printer, sensor, barcode scanner, or a controllable device (e.g., programmable logic controller). A unique hardware abstraction approach is used to provide device extensibility and manageability. Rule-based device configuration and control which allows the real-time changing of system behavior is presented. Various data encoding schemes used to accommodate data captured by a device and used as the input of rule based data filtration and aggregation are discussed. We discuss a mechanism of building self-governed automation processing in the data capture process. Performance is measured by using virtual reader that generates high volume of data at high speed. The measurement shows the RC is capable of handling such data.

Integration of V2H/V2G hybrid system for demand response in distribution network

Integration of Electrical Vehicles (EVs) with power grid not only brings new challenges for load management, but also opportunities for distributed storage and generation in distribution network. With the introduction of Vehicle-to-Home (V2H) and Vehicle-to-Grid (V2G), EVs can help stabilize the operation of power grid. This paper proposed and implemented a hybrid V2H/V2G system with commercialized EVs, which is able to support both islanded AC/DC load and the power grid with one single platform. Standard industrial communication protocols are implemented for a seamless respond to remote Demand Respond (DR) signals. Simulation and implementation are carried out to validate the proposed design. Simulation and implementation results showed that the hybrid system is capable of support critical islanded DC/AC load and quickly respond to the remote DR signal for V2G within 1.5kW of power range.

Evaluating microgrid management and control with an implementable energy management system

A microgrid can be characterized by its integration of distributed energy resources and controllable loads. Such integration brings unique challenges to the microgrid management and control which can be significantly different from conventional power systems. Therefore, a conventional energy management system (EMS) needs to be re-designed with consideration of the unique characteristics of microgrids. To this end, we propose a microgrid EMS named a microgrid platform (MP). We take into account all the functional requirements of a microgrid EMS (i.e., forecast, optimization, data analysis, and human-machine interface) and address the engineering challenges (i.e., flexibility, extensibility, and interoperability) in the design and development of the MP. Moreover, we deploy the prototype system and conduct experiments to evaluate the microgrid management and control in real-world settings at the UCLA Smart Grid Energy Research Center. Our experimental results demonstrate that the MP is able to manage various devices in the testbed, interact with the external systems, and perform optimal energy scheduling and demand response.

Design of RFID mesh network for Electric Vehicle smart charging infrastructure

With an increased number of Electric Vehicles (EVs) on the roads, charging infrastructure is gaining an ever-more important role in simultaneously meeting the needs of the local distribution grid and of EV users. This paper proposes a mesh network RFID system for user identification and charging authorization as part of a smart charging infrastructure providing charge monitoring and control. The Zigbee-based mesh network RFID provides a cost-efficient solution to identify and authorize vehicles for charging and would allow EV charging to be conducted effectively while observing grid constraints and meeting the needs of EV drivers.

Safety design for smart Electric Vehicle charging with current and multiplexing control

As Electric Vehicles (EVs) increase, charging infrastructure becomes more important. When during the day there is a power shortage, the charging infrastructure should have the options to either shut off the power to the charging stations or to lower the power to the EVs in order to satisfy the needs of the grid. This paper proposes a design for a smart charging infrastructure capable of providing power to several EVs from one circuit by multiplexing power and providing charge control and safety systems to prevent electric shock. The safety design is implemented in different levels that include both the server and the smart charging stations. With this smart charging infrastructure, the shortage of energy in a local grid could be solved by our EV charging management system.

A Quantitative Analysis on Virtual Reality-Based Computer Aided Design System Interfaces

Chi-Cheng Chu, Jianzhong Mo, and Rajit Gadh ABSTRACT In this paper, a series of interface tests on interaction approach for the generation of geometric shape designs via multi-sensory user interface of a Virtual Reality (VR) based System is presented. The goal of these interface tests is to identify an effective user interface for VR based Computer-Aided Design (CAD) system. The intuitiveness of the VR based interaction approach arises from the use of natural hand movements/gestures, and voice commands that emulate the way in which human beings discuss geometric shapes in reality. In order to evaluate the proposed interaction approach, a prototypical VR-CAD system is implemented. A series of interface tests were performed on the prototypical systems to determine the relative efficiency of a set of potential interaction approach with respect to specific fundamental design tasks. The interface test and its results are presented in this paper.

A distributed optimal energy management strategy for microgrids

Energy management in microgrids is typically formulated as a non-linear optimization problem. Solving it in a centralized manner not only requires high computational capabilities at the microgrid central controller (MGCC) but may also infringe customer privacy. Existing distributed approaches, on the other hand, assume that all the generations and loads are connected to one bus and ignore the underlying power distribution network and the associated power flows and system operational constraints. Consequently, the schedules produced by those algorithms may violate those constraints and thus are not feasible in practice. Therefore, the focus of this paper is on the design of a distributed energy management strategy (EMS) for the optimal operation of microgrids with consideration of the distribution network and the associated constraints. Specifically, we formulate microgrid energy management as an optimal power flow problem and propose a distributed EMS where the MGCC and the local controllers jointly compute an optimal schedule. As one demonstration, we apply the proposed distributed EMS to a real microgrid in Guangdong Province, China consisting of photovoltaics, wind turbines, diesel generators, and a battery energy storage system. The simulation results demonstrate that the proposed distributed EMS is effective in both islanded and grid-connected mode. It is also shown that the proposed algorithm converges fast.