Multiagent-Based Control for Plug-and-Play Batteries in DC Microgrids with Infrastructure Compensation

The influence of the DC infrastructure on the control of power-storage flow in micro- and smart grids has gained attention recently, particularly in dynamic vehicle-to-grid charging applications. Principal effects include the potential loss of the charge–discharge synchronization and the subsequent impact on the control stabilization, the increased degradation in batteries’ health/life, and resultant power- and energy-efficiency losses. This paper proposes and tests a candidate solution to compensate for the infrastructure effects in a DC microgrid with a varying number of heterogeneous battery storage systems in the context of a multiagent neighbor-to-neighbor control scheme. Specifically, the scheme regulates the balance of the batteries’ load-demand participation, with adaptive compensation for unknown and/or time-varying DC infrastructure influences. Simulation and hardware-in-the-loop studies in realistic conditions demonstrate the improved precision of the charge–discharge synchronization and the enhanced balance of the output voltage under 24 h excessively continuous variations in the load demand. In addition, immediate real-time compensation for the DC infrastructure influence can be attained with no need for initial estimates of key unknown parameters. The results provide both the validation and verification of the proposals under real operational conditions and expectations, including the dynamic switching of the heterogeneous batteries’ connection (plug-and-play) and the variable infrastructure influences of different dynamically switched branches. Key observed metrics include an average reduced convergence time (0.66–13.366%), enhanced output-voltage balance (2.637–3.24%), power-consumption reduction (3.569–4.93%), and power-flow-balance enhancement (2.755–6.468%), which can be achieved for the proposed scheme over a baseline for the experiments in question.</p

Integrated Dynamic Facade Control with an Agent-based Architecture for Commercial Buildings

Dynamic façades have significant technical potential to minimize heating, cooling, and lighting energy use and peak electric demand in the perimeter zone of commercial buildings, but the performance of these systems is reliant on being able to balance complex trade-offs between solar control, daylight admission, comfort, and view over the life of the installation. As the context for controllable energy-efficiency technologies grows more complex with the increased use of intermittent renewable energy resources on the grid, it has become increasingly important to look ahead towards more advanced approaches to integrated systems control in order to achieve optimum life-cycle performance at a lower cost. This study examines the feasibility of a model predictive control system for low-cost autonomous dynamic façades. A system architecture designed around lightweight, simple agents is proposed. The architecture accommodates whole building and grid level demands through its modular, hierarchical approach. Automatically-generated models for computing window heat gains, daylight illuminance, and discomfort glare are described. The open source Modelica and JModelica software tools were used to determine the optimum state of control given inputs of window heat gains and lighting loads for a 24-hour optimization horizon. Penalty functions for glare and view/ daylight quality were implemented as constraints. The control system was tested on a low-power controller (1.4 GHz single core with 2 GB of RAM) to evaluate feasibility. The target platform is a low-cost ($35/unit) embedded controller with 1.2 GHz dual-core cpu and 1 GB of RAM. Configuration and commissioning of the curtainwall unit was designed to be largely plug and play with minimal inputs required by the manufacturer through a web-based user interface. An example application was used to demonstrate optimal control of a three-zone electrochromic window for a south-facing zone. The overall approach was deemed to be promising. Further engineering is required to enable scalable, turnkey solutions

An Autonomous Surface Vehicle for Long Term Operations

Environmental monitoring of marine environments presents several challenges: the harshness of the environment, the often remote location, and most importantly, the vast area it covers. Manual operations are time consuming, often dangerous, and labor intensive. Operations from oceanographic vessels are costly and limited to open seas and generally deeper bodies of water. In addition, with lake, river, and ocean shoreline being a finite resource, waterfront property presents an ever increasing valued commodity, requiring exploration and continued monitoring of remote waterways. In order to efficiently explore and monitor currently known marine environments as well as reach and explore remote areas of interest, we present a design of an autonomous surface vehicle (ASV) with the power to cover large areas, the payload capacity to carry sufficient power and sensor equipment, and enough fuel to remain on task for extended periods. An analysis of the design and a discussion on lessons learned during deployments is presented in this paper.Comment: In proceedings of MTS/IEEE OCEANS, 2018, Charlesto

Multi-Agent Systems Based Advanced Energy Management of Smart Micro-grid

Microgrids play a major role in enabling the widespread adoption of renewable distributed energy resources. However, as the power generated from renewable resources is intermittent in nature, it impacts the dynamics and stability of the microgrid, and hence their integration needs new approaches to coordination and control. The existing systems lack run-time adaptive behavior. To face these constraints, the electric energy system must adapt by integrating Information and Communication Technologies (ICT). Multiagent system (MAS) is emerging as an integrated solution approach to distributed computing, communication, and data integration needs for smart grid application. Distributed and heterogeneous information can be efficiently processed locally, but utilized globally to coordinate distributed knowledge networks, resulting in reduction of information processing time and network bandwidth. Parallel operations, asynchronous communication, and autonomous actions of agents enable MAS to adapt to dynamic changes of the environment, thereby improving the reliability, responsiveness, fault tolerance, and stability of the microgrid. In this chapter, MAS is implemented with Java Agent DEvelopment (JADE) framework for advanced energy management of a microgrid. Also, MAS is linked with Arduino microcontroller for practical verification of agent operations. Three microgrids are interconnected to form a microgrid testbed, and smart grid features such as demand side management and plug and play are implemented, making it into a smart microgrid

Microgrid, Its Control and Stability: The State of The Art

Some of the challenges facing the power industries globally include power quality and stability, diminishing fossil fuel, climate change amongst others. The use of distributed generators however is growing at a steady pace to address these challenges. When interconnected and integrated with storage devices and controllable load, these generators operate together in a grid, which has incidental stability and control issues. The focus of this paper, therefore, is on the review and discussion of the different control approaches and the hierarchical control on a microgrid, the current practice in the literature concerning stability and the control techniques deployed for microgrid control; the weakness and strength of the different control strategies were discussed in this work and some of the areas that require further research are highlighted

Review on Control of DC Microgrids and Multiple Microgrid Clusters

This paper performs an extensive review on control schemes and architectures applied to dc microgrids (MGs). It covers multilayer hierarchical control schemes, coordinated control strategies, plug-and-play operations, stability and active damping aspects, as well as nonlinear control algorithms. Islanding detection, protection, and MG clusters control are also briefly summarized. All the mentioned issues are discussed with the goal of providing control design guidelines for dc MGs. The future research challenges, from the authors' point of view, are also provided in the final concluding part

Optimal operation of hybrid AC/DC microgrids under uncertainty of renewable energy resources : A comprehensive review

The hybrid AC/DC microgrids have become considerably popular as they are reliable, accessible and robust. They are utilized for solving environmental, economic, operational and power-related political issues. Having this increased necessity taken into consideration, this paper performs a comprehensive review of the fundamentals of hybrid AC/DC microgrids and describes their components. Mathematical models and valid comparisons among different renewable energy sources’ generations are discussed. Subsequently, various operational zones, control and optimization methods, power flow calculations in the presence of uncertainties related to renewable energy resources are reviewed.fi=vertaisarvioitu|en=peerReviewed

Carbon Free Boston: Transportation Technical Report

Part of a series of reports that includes: Carbon Free Boston: Summary Report; Carbon Free Boston: Social Equity Report; Carbon Free Boston: Technical Summary; Carbon Free Boston: Buildings Technical Report; Carbon Free Boston: Waste Technical Report; Carbon Free Boston: Energy Technical Report; Carbon Free Boston: Offsets Technical ReportOVERVIEW: Transportation connects Boston’s workers, residents and tourists to their livelihoods, health care, education, recreation, culture, and other aspects of life quality. In cities, transit access is a critical factor determining upward mobility. Yet many urban transportation systems, including Boston’s, underserve some populations along one or more of those dimensions. Boston has the opportunity and means to expand mobility access to all residents, and at the same time reduce GHG emissions from transportation. This requires the transformation of the automobile-centric system that is fueled predominantly by gasoline and diesel fuel. The near elimination of fossil fuels—combined with more transit, walking, and biking—will curtail air pollution and crashes, and dramatically reduce the public health impact of transportation. The City embarks on this transition from a position of strength. Boston is consistently ranked as one of the most walkable and bikeable cities in the nation, and one in three commuters already take public transportation. There are three general strategies to reaching a carbon-neutral transportation system: • Shift trips out of automobiles to transit, biking, and walking;1 • Reduce automobile trips via land use planning that encourages denser development and affordable housing in transit-rich neighborhoods; • Shift most automobiles, trucks, buses, and trains to zero-GHG electricity. Even with Boston’s strong transit foundation, a carbon-neutral transportation system requires a wholesale change in Boston’s transportation culture. Success depends on the intelligent adoption of new technologies, influencing behavior with strong, equitable, and clearly articulated planning and investment, and effective collaboration with state and regional partners.Published versio