scholarly journals Towards net-zero carbon performance: using demand side management and a low carbon grid to reduce operational carbon emissions in a UK public office

2021 ◽  
Vol 2069 (1) ◽  
pp. 012150
Author(s):  
E Burman ◽  
N Jain ◽  
M de-Borja-Torrejón
Keyword(s):  
Carbon Emissions ◽  
Demand Side Management ◽  
Carbon Intensity ◽  
Grid Integration ◽  
Demand Side ◽  
Low Carbon ◽  
Electricity Grid ◽  
Integration Strategy ◽  
Carbon Performance ◽  
And Control

Abstract This paper investigates the performance of an office building that has achieved a low carbon performance in practice thanks to a performance contract and Soft Landings approach. The findings show the potential of this building for further de-carbonisation as a result of electrification of heating and load shifting to take advantage of a low carbon electricity grid. Whilst retrospective modelling based on the past carbon intensity data shows the effectiveness of demand-side management, assessment of the existing smart readiness of the building revealed that the building services and control strategy are not fully equipped with the data analytics and carbon or price signal responsiveness required to facilitate grid integration. The environmental strategy and procurement method used for this building combined with an effective grid integration strategy can serve as a prototype for low carbon design to achieve the ever stringent carbon emissions objectives set out for the non-domestic buildings.

A Scalable Energy–Economy Model for State-Level Policy Analysis Applied to a Demand-Side Management Program

2020 ◽  
Vol 34 (4) ◽  
pp. 372-386
Author(s):  
Zachary A. Wendling ◽  
David C. Warren ◽  
Barry M. Rubin ◽  
Sanya Carley ◽  
Kenneth R. Richards
Keyword(s):  
Green Building ◽  
State Level ◽  
Demand Side Management ◽  
Management Program ◽  
Demand Side ◽  
Low Carbon ◽  
Economic Sectors ◽  
Endogenous Variables ◽  
Performance Results ◽  
Low Carbon Energy

Over the past two decades, states and cities implemented low-carbon energy development, renewable portfolio standards, demand-side management (DSM), renewable energy production incentives, green building requirements, regional carbon trading agreements, and other energy-based economic development initiatives. Yet the dearth of state-level and substate-level models makes it difficult to predict the effects of such actions. This article addresses this shortcoming by presenting the performance results of the new Indiana Scalable Economy and Energy Model (IN-SEEM)—a model utilizing a dynamic, simultaneous equations framework—and demonstrates the model’s capabilities with an analysis of electricity price increases from a DSM program in the state of Indiana. Overall performance of the model is strong, with high adjusted R2 values and low mean absolute percent errors for most of 30 endogenous variables. A DSM price increase analysis finds variation in impact across the state’s 10 major economic sectors and small changes in energy consumption.

scholarly journals Life-Cycle Carbon Emissions and Energy Implications of High Penetration of Photovoltaics and Electric Vehicles in California

Energies ◽  
2021 ◽  
Vol 14 (16) ◽  
pp. 5165
Author(s):  
Marco Raugei ◽  
Alessio Peluso ◽  
Enrica Leccisi ◽  
Vasilis Fthenakis
Keyword(s):  
Life Cycle ◽  
Electric Vehicles ◽  
Carbon Emissions ◽  
Lithium Ion ◽  
Net Energy ◽  
Low Carbon ◽  
High Penetration ◽  
Original Grid ◽  
Carbon Performance ◽  
High Level

California has set two ambitious targets aimed at achieving a high level of decarbonization in the coming decades, namely (i) to generate 60% and 100% of its electricity using renewable energy (RE) technologies, respectively, by 2030 and by 2045, and (ii) introducing at least 5 million zero emission vehicles (ZEVs) by 2030, as a first step towards all new vehicles being ZEVs by 2035. In addition, in California, photovoltaics (PVs) coupled with lithium-ion battery (LIB) storage and battery electric vehicles (BEVs) are, respectively, the most promising candidates for new RE installations and new ZEVs, respectively. However, concerns have been voiced about how meeting both targets at the same time could potentially negatively affect the electricity grid’s stability, and hence also its overall energy and carbon performance. This paper addresses those concerns by presenting a thorough life-cycle carbon emission and energy analysis based on an original grid balancing model that uses a combination of historical hourly dispatch and demand data and future projections of hourly demand for BEV charging. Five different scenarios are assessed, and the results unequivocally indicate that a future 80% RE grid mix in California is not only able to cope with the increased demand caused by BEVs, but it can do so with low carbon emissions (<110 g CO2-eq/kWh) and satisfactory net energy returns (EROIPE-eq = 12–16).

Calculation and Evaluation Methodology of Transport Energy Consumption and Carbon Emissions: A Case Study of Jiangsu Province

2014 ◽  
Vol 962-965 ◽  
pp. 1293-1302 ◽  
Author(s):  
Bin Ouyang ◽  
Zhen Hua Feng ◽  
Qing Hua Bi
Keyword(s):  
Energy Consumption ◽  
Carbon Emissions ◽  
Energy Intensity ◽  
Jiangsu Province ◽  
Policy Implications ◽  
System Structure ◽  
Evaluation Methodology ◽  
Carbon Intensity ◽  
Low Carbon ◽  
Carbon Transport

The calculation methodology of transport carbon emissions, based on the methodology recommended by Intergovernmental Panel on Climate Change (IPCC) and the energy consumption statistics of provincial transport industry in China, is proposed. By using the methodology, the energy consumption and carbon emissions of highway, waterway and urban passenger transport from 2005 to 2012 of Jiangsu Province are calculated and evaluated. And the developing trends and main features from the perspectives of the total amount of transport energy consumption and carbon emissions, the proportional of both various energy types and various transport modes in the energy consumption, the energy intensity and carbon dioxide intensity, are systematically analyzed. Finally, some policy implications of low-carbon transport development were conclusively put forward, including reducing energy intensity and carbon intensity as the core focus, the highway transport as the breakthrough point, optimizing the integrated transport system structure and developing of public transport in priority as the strategic orientation, developing clean and low-carbon energy as an important way, etc. The research methodology and results can provide references for decision-making and management of the relevant provinces and cities on low-carbon transport development.

Demand-side management and control in buildings

2014 ◽  
pp. 129-160
Author(s):  
Jun Hong ◽  
Cameron M. Johnstone ◽  
Jae Min Kim ◽  
Paul Tuohy
Keyword(s):  
Demand Side Management ◽  
Demand Side ◽  
And Control

Smart Grid and Demand Side Management

2020 ◽  
pp. 139-159
Author(s):  
Alper Ozpinar ◽  
Eralp Ozil
Keyword(s):  
Smart Grid ◽  
Supply And Demand ◽  
Carbon Capture And Storage ◽  
Demand Side Management ◽  
Demand Side ◽  
Low Carbon ◽  
Energy Technologies ◽  
The Common ◽  
Management Optimization ◽  
New Policies

Energy becoming more and more crucial and critical in the civilized populations and locates itself as one of the major requirements of living standards. Obtaining the energy from fossil fuels still is one of the common sources of energy production; however, there is a common understanding of increasing the potential use of renewables, carbon capture and storage, energy efficiency and intelligence and smart applications for collecting, distributing and transmission of the energy between the supply and demand locations. Those applications and generating the new policies, roadmaps in order to make an energy revolution and increase the usage of low-carbon energy technologies targeting the decrease of energy related emissions. In this chapter, the authors explains the common issues about smart grid and demand side management and possible use artificial intelligence and metaheuristic algorithms for smart grid and demand side management optimization and scheduling.

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