Contrasting the capabilities of building energy performance simulation programs

For the past 50 years, a wide variety of building energy simulation programs have been developed, enhanced and are in use throughout the building energy community. This paper is an overview of a report, which provides up-to-date comparison of the features and capabilities of twenty major building energy simulation programs. The comparison is based on information provided by the program developers in the following categories: general modeling features; zone loads; building envelope and daylighting and solar; infiltration, ventilation and multizone airflow; renewable energy systems; electrical systems and equipment; HVAC systems; HVAC equipment; environmental emissions; economic evaluation; climate data availability, results reporting; validation; and user interface, links to other programs, and availability

Assessment of highly distributed power systems using an integrated simulation approach

In a highly distributed power system (HDPS), micro renewable and low carbon technologies would make a significant contribution to the electricity supply. Further, controllable devices such as micro combined heat and power (CHP) could be used to assist in maintaining stability in addition to simply providing heat and power to dwellings. To analyse the behaviour of such a system requires the modelling of both the electrical distribution system and the coupled microgeneration devices in a realistic context. In this paper a pragmatic approach to HDPS modelling is presented: microgeneration devices are simulated using a building simulation tool to generate time-varying power output profiles, which are then replicated and processed statistically so that they can be used as boundary conditions for a load flow simulation; this is used to explore security issues such as under and over voltage, branch thermal overloading, and reverse power flow. Simulations of a section of real network are presented, featuring different penetrations of micro-renewables and micro-CHP within the ranges that are believed to be realistically possible by 2050. This analysis indicates that well-designed suburban networks are likely to be able to accommodate such levels of domestic-scale generation without problems emerging such as overloads or degradation to the quality of supply

Agent based modeling of energy networks

Attempts to model any present or future power grid face a huge challenge because a power grid is a complex system, with feedback and multi-agent behaviors, integrated by generation, distribution, storage and consumption systems, using various control and automation computing systems to manage electricity flows. Our approach to modeling is to build upon an established model of the low voltage electricity network which is tested and proven, by extending it to a generalized energy model. But, in order to address the crucial issues of energy efficiency, additional processes like energy conversion and storage, and further energy carriers, such as gas, heat, etc., besides the traditional electrical one, must be considered. Therefore a more powerful model, provided with enhanced nodes or conversion points, able to deal with multidimensional flows, is being required. This article addresses the issue of modeling a local multi-carrier energy network. This problem can be considered as an extension of modeling a low voltage distribution network located at some urban or rural geographic area. But instead of using an external power flow analysis package to do the power flow calculations, as used in electric networks, in this work we integrate a multiagent algorithm to perform the task, in a concurrent way to the other simulation tasks, and not only for the electric fluid but also for a number of additional energy carriers. As the model is mainly focused in system operation, generation and load models are not developed

NMOS-based integrated modular bypass for use in solar systems (NIMBUS): intelligent bypass for reducing partial shading power loss in solar panel applications

NMOS-based Integrated Modular Bypass for Use in Solar systems (NIMBUS) is designed as a replacement for the traditional bypass diode, used in common solar panels. Because of the series connection between the individual solar cells, the power output of a photovoltaic (PV) panel will drop disproportionally under partial shading. Currently, this is solved by dividing the PV panel into substrings, each with a diode bypass placed in parallel. This allows an alternative current path. However, the diodes still have a significant voltage drop (about 350 mV), and due to the fairly large currents in a panel, the diodes are dissipating power that we would rather see at the output of the panel. The NIMBUS chip, being a low-voltage-drop switch, aims to replace these diodes and, thus, reduce that power loss. NIMBUS is a smart bypass: a completely stand-alone system that detects the failing of one or more cells and activates when necessary. It is designed for a 100-mV voltage drop under a 5-A load current. When two or more NIMBUS chips are placed in parallel, an internal synchronization circuit ensures proper operation to provide for larger load currents. This paper will elaborate on the operation, design and implementation of the NIMBUS chip, as well as on the first measurements

Five-Axis Machine Tool Condition Monitoring Using dSPACE Real-Time System

This paper presents the design, development and SIMULINK implementation of the lumped parameter model of C-axis drive from GEISS five-axis CNC machine tool. The simulated results compare well with the experimental data measured from the actual machine. Also the paper describes the steps for data acquisition using ControlDesk and hardware-in-the-loop implementation of the drive models in dSPACE real-time system. The main components of the HIL system are: the drive model simulation and input – output (I/O) modules for receiving the real controller outputs. The paper explains how the experimental data obtained from the data acquisition process using dSPACE real-time system can be used for the development of machine tool diagnosis and prognosis systems that facilitate the improvement of maintenance activities