Energy management means to optimize one of the most complex and important technical creations that we know: the energy system. While there is plenty of experience in optimizing energy generation and distribution, it is the demand side that receives increasing attention by research and industry. Demand Side Management (DSM) is a portfolio of measures to improve the energy system at the side of consumption. It ranges from improving energy efficiency by using better materials, over smart energy tariffs with incentives for certain consumption patterns, up to sophisticated real-time control of distributed energy resources. This paper gives an overview and a taxonomy for DSM, analyzes the various types of DSM, and gives an outlook on the latest demonstration projects in this domain.

/pdf/demand-side-management-demand-response-intelligent-energy-27yx5jmy0a.pdf

Demand Side Management: Demand Response, Intelligent Energy Systems, and Smart Loads

Green building is one of measures been put forward to mitigate significant impacts of the building stock on the environment, society and economy. However, there is lack of a systematic review of this large number of studies that is critical for the future endeavor. The last decades have witnessed rapid growing number of studies on green building. This paper reports a critical review of the existing body of knowledge of researches related to green building. The common research themes and methodology were identified. These common themes are the definition and scope of green building; quantification of benefits of green buildings compared to conventional buildings; and various approaches to achieve green buildings. It is found that the existing studies played predominately focus on the environmental aspect of green building. Other dimensions of sustainability of green building, especially the social sustainability is largely overlooked. Future research opportunities were identified such as effects of climatic conditions on the effectiveness of green building assessment tools, validation of real performance of green buildings, unique demands of specific population, and future proofing.

Green building research–current status and future agenda: A review

Buildings consume about 41.1% of primary energy and 74% of the electricity in the U.S. Better or even optimal building energy control and operation strategies provide great opportunities to reduce building energy consumption. Moreover, it is estimated by the National Energy Technology Laboratory that more than one-fourth of the 713 GW of U.S. electricity demand in 2010 could be dispatchable if only buildings could respond to that dispatch through advanced building energy control and operation strategies and smart grid infrastructure. Energy forecasting models for building energy systems are essential to building energy control and operation. Three general categories of building energy forecasting models have been reported in the literature which include white-box (physics-based), black-box (data-driven), and gray-box (combination of physics based and data-driven) modeling approaches. This paper summarizes the existing efforts in this area as well as other critical areas related to building energy modeling, such as short-term weather forecasting. An up-to-date overview of research on application of building energy modeling methods in optimal control for single building and multiple buildings is also summarized in this paper. Different model-based and model-free optimization methods for building energy system operation are reviewed and compared in this paper. Agent based modeling, as a new modeling strategy, has made a remarkable progress in distributed energy systems control and optimization in the past years. The research literature on application of agent based model in building energy system control and operation is also identified and discussed in this paper.

Review of building energy modeling for control and operation

https://escholarship.org/content/qt0dq0x4tg/qt0dq0x4tg.pdf?t=p8gzv3

Ten questions concerning occupant behavior in buildings: The big picture

A hybrid decision support system for sustainable office building renovation and energy performance improvement

https://escholarship.org/content/qt9qz4j2w9/qt9qz4j2w9.pdf?t=p0ju82

Quantifying Flexibility of Commercial and Residential Loads for Demand Response using Setpoint Changes

https://escholarship.org/content/qt8pm198tv/qt8pm198tv.pdf

Study on Auto-DR and pre-cooling of commercial buildings with thermal mass in California

Study on Auto-DR and Pre-cooling of Commercial Buildings with Thermal Mass in California Rongxin Yin, Peng Xu, Mary Ann Piette, Sila Kiliccote Lawrence Berkeley National Laboratory January 2010

Study on Auto-DR and Pre-Cooling of Commercial Buildings with Thermal Mass in California

Energy modeling of two office buildings with data center for green building design

https://simulationresearch.lbl.gov/sites/all/files/lipingpaperonb90.pdf

Rongxin Yin

Papers

Quantifying Flexibility of Commercial and Residential Loads for Demand Response using Setpoint Changes

Study on Auto-DR and pre-cooling of commercial buildings with thermal mass in California

Study on Auto-DR and Pre-Cooling of Commercial Buildings with Thermal Mass in California

Energy modeling of two office buildings with data center for green building design

Monitoring-based HVAC commissioning of an existing office building for energy efficiency