Computing in the RAIN: a reliable array of independent nodes

The RAIN project is a research collaboration between Caltech and NASA-JPL on distributed computing and data-storage systems for future spaceborne missions. The goal of the project is to identify and develop key building blocks for reliable distributed systems built with inexpensive off-the-shelf components. The RAIN platform consists of a heterogeneous cluster of computing and/or storage nodes connected via multiple interfaces to networks configured in fault-tolerant topologies. The RAIN software components run in conjunction with operating system services and standard network protocols. Through software-implemented fault tolerance, the system tolerates multiple node, link, and switch failures, with no single point of failure. The RAIN-technology has been transferred to Rainfinity, a start-up company focusing on creating clustered solutions for improving the performance and availability of Internet data centers. In this paper, we describe the following contributions: 1) fault-tolerant interconnect topologies and communication protocols providing consistent error reporting of link failures, 2) fault management techniques based on group membership, and 3) data storage schemes based on computationally efficient error-control codes. We present several proof-of-concept applications: a highly-available video server, a highly-available Web server, and a distributed checkpointing system. Also, we describe a commercial product, Rainwall, built with the RAIN technology

Techno-Economic Analysis and Optimization of Distributed Energy Systems

As a promising approach for sustainable development, distributed energy systems have receive increasing attention worldwide and have become a key topic explored by researchers in the areas of building energy systems and smart grid. In line with this research trend, this dissertation presents a techno-economic analysis and optimization of distributed energy systems including combined heat and power (CHP), photovoltaics (PV), battery energy storage (BES), and thermal energy storage (TES) for commercial buildings. First, the techno-economic performance of the CHP system is analyzed and evaluated for four building types including hospital, large office, large hotel, and secondary school, located in different U.S. regions. The energy consumption of each building is obtained by EnergyPlus simulation software. The simulation models of CHP system are established for each building type. From the simulation results, the payback period (PBP) of the CHP system in different locations is calculated. The parameters that have an influence on the PBP of the CHP system are analyzed. Second, PV system and integrated PV and BES (PV-BES) system are investigated for several commercial building types, respectively. The effects of the variation in key parameters, such as PV system capacity, capital cost of PV, sell back ratio, battery capacity, and capital cost of battery, on the performance of PV and/or PV-BES system are explored. Finally, subsystems in previous chapters (CHP, PV, and BES) along with TES system are integrated together based on a proposed control strategy to meet the electric and thermal energy demand of commercial buildings (i.e., hospital and large hotel). A multi-objective particle swarm optimization (PSO) is conducted to determine the optimal size of each subsystem with the objective to minimize the payback period and maximize the reduction of carbon dioxide emissions. The results reveal how the key factors affect the performance of distributed energy system and demonstrate the proposed optimization can be effectively utilized to obtain an optimized design of distributed energy systems that can get a tradeoff between the environmental and economic impacts for different buildings

Microgrids/Nanogrids Implementation, Planning, and Operation

Today’s power system is facing the challenges of increasing global demand for electricity, high-reliability requirements, the need for clean energy and environmental protection, and planning restrictions. To move towards a green and smart electric power system, centralized generation facilities are being transformed into smaller and more distributed ones. As a result, the microgrid concept is emerging, where a microgrid can operate as a single controllable system and can be viewed as a group of distributed energy loads and resources, which can include many renewable energy sources and energy storage systems. The energy management of a large number of distributed energy resources is required for the reliable operation of the microgrid. Microgrids and nanogrids can allow for better integration of distributed energy storage capacity and renewable energy sources into the power grid, therefore increasing its efficiency and resilience to natural and technical disruptive events. Microgrid networking with optimal energy management will lead to a sort of smart grid with numerous benefits such as reduced cost and enhanced reliability and resiliency. They include small-scale renewable energy harvesters and fixed energy storage units typically installed in commercial and residential buildings. In this challenging context, the objective of this book is to address and disseminate state-of-the-art research and development results on the implementation, planning, and operation of microgrids/nanogrids, where energy management is one of the core issues

Current state of the mass storage system reference model

IEEE SSSWG was chartered in May 1990 to abstract the hardware and software components of existing and emerging storage systems and to define the software interfaces between these components. The immediate goal is the decomposition of a storage system into interoperable functional modules which vendors can offer as separate commercial products. The ultimate goal is to develop interoperable standards which define the software interfaces, and in the distributed case, the associated protocols to each of the architectural modules in the model. The topics are presented in viewgraph form and include the following: IEEE SSSWG organization; IEEE SSSWG subcommittees & chairs; IEEE standards activity board; layered view of the reference model; layered access to storage services; IEEE SSSWG emphasis; and features for MSSRM version 5

A Distributed Coordination Strategy for Heterogeneous Building Flexible Thermal Loads in Responding to Smart Grids

Air conditioning systems are promising energy flexibility resources for smart grids. However, buildings with various thermodynamics must be coordinated to utilize limited energy flexibility effectively. This study proposes a distributed coordination strategy to coordinate building flexible thermal loads of different characteristics for optimized utilization of energy flexibility in a scalable and distributed manner. It consists of two components:1) an average consensus-based distributed sensing scheme to estimate the average thermal state of charge (SoC) of multiple zones, and 2) a weighted consensus-based distributed allocation module to allocate the demand response (DR) tasks or limited energy resources to multiple zones, proportional to their thermal storage capacities and deviations to the average thermal SoCs. Both algorithms achieve their goals respectively by fully distributed means through a sparse network with neighbor-to-neighbor communication. The sufficient condition for converging the weighted consensus algorithm is also derived for the first time. The proposed strategy is adopted for 1) weighted DR participation of residential inverter air conditioners and 2) weighted water flow redistribution of the commercial building water heating systems under urgent DR events. Simulation results show that adopting the distributed coordination strategy avoids the early depletion of demand flexibility resources and nonuniform thermal comfort sacrifices under uncoordinated control

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