A review of microgrid development in the United States – A decade of progress on policies, demonstrations, controls, and software tools

Microgrids have become increasingly popular in the United States. Supported by favorable federal and local policies, microgrid projects can provide greater energy stability and resilience within a project site or community. This paper reviews major federal, state, and utility-level policies driving microgrid development in the United States. Representative U.S. demonstration projects are selected and their technical characteristics and non-technical features are introduced. The paper discusses trends in the technology development of microgrid systems as well as microgrid control methods and interactions within the electricity market. Software tools for microgrid design, planning, and performance analysis are illustrated with each tool's core capability. Finally, the paper summarizes the successes and lessons learned during the recent expansion of the U.S. microgrid industry that may serve as a reference for other countries developing their own microgrid industries

Investigation of the energy performance of a novel modular solar building envelope

The major challenges for the integration of solar collecting devices into a building envelope are related to the poor aesthetic view of the appearance of buildings in addition to the low efficiency in collection, transportation, and utilization of the solar thermal and electrical energy. To tackle these challenges, a novel design for the integration of solar collecting elements into the building envelope was proposed and discussed. This involves the dedicated modular and multiple-layer combination of the building shielding, insulation, and solar collecting elements. On the basis of the proposed modular structure, the energy performance of the solar envelope was investigated by using the Energy-Plus software. It was found that the solar thermal efficiency of the modular envelope is in the range of 41.78–59.47%, while its electrical efficiency is around 3.51% higher than the envelopes having photovoltaic (PV) alone. The modular solar envelope can increase thermal efficiency by around 8.49% and the electrical efficiency by around 0.31%, compared to the traditional solar photovoltaic/thermal (PV/T) envelopes. Thus, we have created a new envelope solution with enhanced solar efficiency and an improved aesthetic view of the entire building

Screening of energy efficient technologies for industrial buildings' retrofit

This chapter discusses screening of energy efficient technologies for industrial buildings' retrofit

Analysis of Geo-Energy System with Focus on Borehole Thermal Energy Storage

Ground source heat pump (GSHP) systems have become more popular lately both for residential space heating and for commercial applications. GSHP systems can use water, ground or the bedrock as a thermal source. The energy extracted is regarded as a renewable energy-source and it consists of both stored solar energy and a share of geothermal energy. A borehole thermal storage (BTES) consists of boreholes drilled in a specific pattern with a few meters in-between. A BTES can be used for both heating during winter and cooling during summer. The stable temperature of the bedrock provides good performance as long as the balance between extracted and injected heat is kept. With increasing size of GSHP-systems it is desirable to simulate the systems and to perform optimization and life cycle analysis to justify investments. There are several existing software that can simulate a BTES but they are either working with too large time steps or they are too complicated for industrial usage. Within this thesis a short time-step model of a BTES is constructed based on existing research. The model is validated using existing simulation software and then demonstrated within a simplified GSHP-system

Modelling and Co-simulation of Multi-Energy Systems: Distributed Software Methods and Platforms

L'abstract è presente nell'allegato / the abstract is in the attachmen

The architecture for testing central heating control algorithms with feedback from wireless temperature sensors

The energy consumption of buildings is a significant contributor to overall energy con- sumption in developed countries. Therefore, there is great demand for intelligent buildings in which energy consumption is optimized. Online control is a crucial aspect of such optimization. The imple- mentation of modern algorithms that take advantage of developments in information technology, artificial intelligence, machine learning, sensors, and the Internet of Things (IoT) is used in this context. In this paper, an architecture for testing central heating control algorithms as well as the control algorithms of the heating system of the building is presented. In particular, evaluation metrics, the method for seamless integration, and the mechanism for real-time performance monitoring and control are put forward. The proposed tools have been successfully tested in a residential building, and the conducted tests confirmed the efficiency of the proposed solution

IEA ECES Annex 31 Final Report - Energy Storage with Energy Efficient Buildings and Districts: Optimization and Automation

At present, the energy requirements in buildings are majorly met from non-renewable sources where the contribution of renewable sources is still in its initial stage. Meeting the peak energy demand by non-renewable energy sources is highly expensive for the utility companies and it critically influences the environment through GHG emissions. In addition, renewable energy sources are inherently intermittent in nature. Therefore, to make both renewable and nonrenewable energy sources more efficient in building/district applications, they should be integrated with energy storage systems. Nevertheless, determination of the optimal operation and integration of energy storage with buildings/districts are not straightforward. The real strength of integrating energy storage technologies with buildings/districts is stalled by the high computational demand (or even lack of) tools and optimization techniques. Annex 31 aims to resolve this gap by critically addressing the challenges in integrating energy storage systems in buildings/districts from the perspective of design, development of simplified modeling tools and optimization techniques

Building Energy Modeling with OpenStudio : A Practical Guide for Students and Professionals

The energy, environmental, and societal challenges of the twenty-first century are here; they are crystal clear; and they are daunting. Our responses to those challenges are less clear, but one component at least is obvious—we need a better building stock, one that uses less energy, provides greater comfort and security, and houses and supports the economic activity of a rapidly growing and urbanizing population. One of the most powerful tools in our collective belts is building energy modeling (BEM), physics-based software simulation of building energy use given a description of the physical building, its use patterns, and prevailing weather conditions. BEM is a sine qua non tool for designing and operating buildings to the levels of energy efficiency that our future and present require. According to the AIA 2030 Commitment report, buildings designed using BEM use 20% less energy than those designed without it. BEM is also instrumental in developing and updating the codes, standards, certificates, and financial incentive infrastructure that supports energy efficiency in all building projects, including those that don’t directly use BEM. The OpenStudio project has been a driving force in the evolution of BTO’s BEM program. OpenStudio was BTO’s first truly open-source software project, a strategic direction that has influenced BTO’s entire BEM portfolio. Open-source is not an altruistic emergent enterprise. Successful open-source projects are funded, centrally managed, and resemble proprietary software projects in many structural and operational ways. Source control. Code reviews. Regression testing. Bug reporting and fixing. Pre-feature documentation. Post-feature documentation. The full Monty