Control and Communication Protocols that Enable Smart Building Microgrids

Recent communication, computation, and technology advances coupled with climate change concerns have transformed the near future prospects of electricity transmission, and, more notably, distribution systems and microgrids. Distributed resources (wind and solar generation, combined heat and power) and flexible loads (storage, computing, EV, HVAC) make it imperative to increase investment and improve operational efficiency. Commercial and residential buildings, being the largest energy consumption group among flexible loads in microgrids, have the largest potential and flexibility to provide demand side management. Recent advances in networked systems and the anticipated breakthroughs of the Internet of Things will enable significant advances in demand response capabilities of intelligent load network of power-consuming devices such as HVAC components, water heaters, and buildings. In this paper, a new operating framework, called packetized direct load control (PDLC), is proposed based on the notion of quantization of energy demand. This control protocol is built on top of two communication protocols that carry either complete or binary information regarding the operation status of the appliances. We discuss the optimal demand side operation for both protocols and analytically derive the performance differences between the protocols. We propose an optimal reservation strategy for traditional and renewable energy for the PDLC in both day-ahead and real time markets. In the end we discuss the fundamental trade-off between achieving controllability and endowing flexibility

Role of control, communication, and markets in smart building operation

This thesis explores the role of control, communication, and markets in the operation of smart buildings and microgrids. It develops models to study demand response (DR) alternatives in smart buildings using different communication and control protocols in building management systems. Moreover, it aims at understanding the extent to which smart buildings can provide regulation service reserves (RSR) by real time direct load control (DLC) or price-based indirect control approaches. In conducting a formal study of these problems, we first investigate the optimal operational performance of smart buildings using a control protocol called packetized direct load control (PDLC). This is based on the notion of the energy packet which is a temporal quantization of energy supplied to an appliance or appliance pool by a smart building operator (SBO). This control protocol is built on top of two communication protocols that carry either complete or binary information regarding the operation status of the appliances in the pool. We discuss the optimal demand side operation for both protocols and analytically derive the performance differences between them. We analyze the costs of renewable penetration to the system's real time operation. In order to strike a balance between excessive day-ahead energy reservation costs and stochastic real time operation costs, we propose an optimal reservation strategy for traditional and renewable energy for the PDLC in both the day-ahead and the real time markets to hedge the uncertainty of real time energy prices and renewable energy realization. The second part of the thesis proposes systematic approaches for smart buildings to reliably participate in power reserve markets. The problem is decomposed into two parts in the first of which the SBO starts by estimating its prior capacity of reserve provision based on characteristics of the building, the loads, and consumer preferences. We show that the building's reserve capacity is governed by a few parameters and that there is a trade off for smart buildings to provide either sustained reserve or ramping reserve. Based on the estimated capacity, we propose two real time control mechanisms to provide reliable RSR. The first is a DLC framework wherein consumers allow the SBO to directly modulate their appliances' set points within allowable ranges. We develop a feedback controller to guarantee asymptotic tracking performance of the smart building's aggregated response to the RSR signal. The second is a price controlled framework that allows consumers to voluntarily connect and consume electricity based on their instantaneous utility needs. Consumers' time varying dynamic preferences in providing RSR are studied by Monte Carlo simulation, in which such preferences are characterized by sufficient statistics that can be used in a stochastic dynamic programming (DP) formulation to solve for the optimal pricing policy

Flexible Demand Resource Pricing Scheme: A Stochastic Benefit-Sharing Approach

With the rapidly increased penetration of renewable generations, incentive-based demand side management (DSM) shows great value on alleviating the uncertainty and providing flexibility for microgrid. However, how to price those demand resources becomes one of the most significant challenges for promoting incentive-based DSM under microgrid environments. In this paper, a flexible demand resource pricing scheme is proposed. Instead of using the utility function of end users like most existing literatures, the economic benefit of flexible demand resources is evaluated by the operation performance enhancement of microgrid and correspondingly the resource is priced based on a benefit sharing approach. An iteration-based chance-constrained method is established to calculate the economic benefit and shared compensation for demand resource providers. Meanwhile, the financial risks for the microgrid operator due to uncertain factors are mitigated by the chance-constrained criterion. The proposed scheme is examined by an experimental microgrid to illustrate its effectiveness.Comment: 10 pages, 16 figure

SECURE REAL-TIME SMART GRID COMMUNICATIONS: A MICROGRID PERSPECTIVE

Microgrids are a key component in the evolution of the power grid. Microgrids are required to operate in both grid connected and standalone island mode using local sources of power. A major challenge in implementing microgrids is the communications and control to support transition from grid connected mode and operation in island mode. In this dissertation we propose a distributed control architecture to govern the operation of a microgrid. The func- tional communication requirements of primary, secondary and tertiary microgrid controls are considered. Communication technology media and protocols are laid out and a worst-case availability and latency analysis is provided. Cyber Security challenges to microgrids are ex- amined and we propose a secure communication architecture to support microgrid operation and control. A security model, including network, data, and attack models, is defined and a security protocol to address the real-time communication needs of microgrids is proposed. We propose a novel security protocol that is custom tailored to meet those challenges. The chosen solution is discussed in the context of other security options available in the liter- ature. We build and develop a microgrid co-simulation model of both the power system and communication networks, that is used to simulate the two fundamental microgrid power transition functions - transition from island to grid connected mode, and grid connected to island mode. The proposed distributed control and security architectures are analyzed in terms of performance. We further characterize the response of the power and communication subsystems in emergency situations: forced islanding and forced grid modes. Based on our findings, we generalize the results to the smart grid

Transmission and Distribution Co-Simulation and Applications

As the penetration of flexible loads and distributed energy resources (DERs) increases in distribution networks, demand dispatch schemes need to consider the effects of large-scale load control on distribution grid reliability. Thus, we need demand dispatch schemes that actively ensure that distribution grid operational constraints are network-admissible and still deliver valuable market services. In this context, this work develops and evaluates the performance of a new network-admissible version of the device-driven demand dispatch scheme called Packetized Energy Management (PEM). Specifically, this work develops and investigates the live grid constraint-based coordinator and metrics for performance evaluation. The effects of grid measurements for a practical-sized, 2,522-bus, unbalanced distribution test feeder with a 3000 flexible kW-scale loads operating under the network-admissible PEM scheme is discussed. The results demonstrate the value of live grid measurements in managing distribution grid operational constraints while PEM can effectively deliver frequency regulation services. Increased penetration of flexible loads and DERs on distribution system (DS) will lead to increased interaction of transmission and distribution (T&D) system operators to ensure reliable operation of the interconnected power grids, as well as the control actions at LV/MV grid in aggregation will have significant impact on the transmission systems (TS). Thus, a need arises to study the coupling of the transmission and distribution (T&D) systems. Therefore, this work develops a co-simulation platform based on decoupled approach to study integrated T&D systems collectively. Additionally, the results of a decoupled method applied for solving T&D power flow co-simulation is benchmarked against the collaborator developed unified solution which proves the accuracy of the decoupled approach. The existing approaches in the literature to study steady-state interaction of TS-DS have several shortcomings including that the existing methods exhibit scalability, solve-time and computational memory usage concerns. In this regard, this work develops comprehensive mathematical models of T&D systems for integrated power flow analysis and brings advancements from the algorithmic perspective to efficiently solve large-scale T&D circuits. Further, the models are implemented in low-cost CPU-GPU hybrid computing platform to further speed up the computational performance. The efficacy of the proposed models, solution algorithms, and their hardware implementation are demonstrated with more than 13,000 nodes using an integrated system that consists of 2383-bus Polish TS and multiple instances of medium voltage part of the IEEE 8,500-node DS. Case studies demonstrate that the proposed approach is scalable and can provide more than tenfold speed up on the solve time of very large-scale integrated T&D systems. Overall, this work develops practically applicable and efficient demand dispatch coordinator able to integrate DERs into DS while ensuring the grid operational constraints are not violated. Additionally, the dynamics introduced in the DS with such integration that travels to TS is also studied collectively using integrated T&D co-simulation and in the final step, a mathematically comprehensive model tackles the scalability, solve-time and computational memory usage concerns for large scale integrated T&D co-simulation and applications

The role of communication systems in smart grids: Architectures, technical solutions and research challenges

The purpose of this survey is to present a critical overview of smart grid concepts, with a special focus on the role that communication, networking and middleware technologies will have in the transformation of existing electric power systems into smart grids. First of all we elaborate on the key technological, economical and societal drivers for the development of smart grids. By adopting a data-centric perspective we present a conceptual model of communication systems for smart grids, and we identify functional components, technologies, network topologies and communication services that are needed to support smart grid communications. Then, we introduce the fundamental research challenges in this field including communication reliability and timeliness, QoS support, data management services, and autonomic behaviors. Finally, we discuss the main solutions proposed in the literature for each of them, and we identify possible future research directions

Energy Harvesting for Residential Microgrid Distributed Sensor Systems

Microgrids are localized, independent power grids that can operate while connected to the larger electrical grid. These systems make intelligent decisions regarding power management and use an array of components to monitor power generation, consumption, and environmental conditions. While this technology can save end users money, the complexity of installation and maintenance has limited the adoption of microgrids in residential spaces. To simplify this technology for end users, the next evolution of microgrid components includes sensors that are wireless and ambiently powered. Even with a microgrid installed, significant energy is wasted in residential spaces. To address this loss, energy harvesting circuits can be incorporated into microgrid sensors, enabling them to recapture otherwise wasted environmental energy. Light, heat, radio frequency (RF) energy, mechanical energy, and 60 Hz noise from power lines are all abundant in most residential spaces and can be harvested to power microgrid components. Equipping microgrid sensors with energy harvesters simplifies the end user experience by eliminating the need for cable routing. Implementing energy harvesting techniques results in a microgrid that is easier to deploy, cleaner, and requires less maintenance. Developing this type of sensor is not only feasible, but sensible and can be constructed using off-the-shelf components. My research led me to conclude that the most effective strategy for designing an energy harvesting sensor is to combine energy harvesting technologies with battery power. By delegating smaller loads away from the harvesting integrated circuit (IC), its full harvesting potential is utilized, maximizing energy collection for the power-hungry transmitter. Simultaneously, a small coin-cell battery can sustain the remaining components, ensuring over a decade of functionality. This thesis explores the feasibility and design of a hybrid battery and energy harvesting sensor. The developed system block diagram allows for the swapping of components within each block, catering to the varying needs of the end user. The system is data and energy-aware, allowing it to make intelligent decisions regarding data transmission and enable communication as reliable as that of a traditional wire-line powered sensor. The hybrid sensor module underwent testing with a small monocrystalline solar cell as its energy source, delivering consistent power throughout the testing period. It accumulated surplus energy in a super capacitor storage unit, ensuring the system’s reliable operation even at night when the energy source was not available. While the tests utilized a photovoltaic (PV) cell, the design accommodates any energy harvesting source that can generate a minimum of 40 µW of power