Advances in Theoretical and Computational Energy Optimization Processes

The paradigm in the design of all human activity that requires energy for its development must change from the past. We must change the processes of product manufacturing and functional services. This is necessary in order to mitigate the ecological footprint of man on the Earth, which cannot be considered as a resource with infinite capacities. To do this, every single process must be analyzed and modified, with the aim of decarbonising each production sector. This collection of articles has been assembled to provide ideas and new broad-spectrum contributions for these purposes

Smart and flexible electric heat: an energy futures lab briefing paper

Heating in residential, commercial and industrial settings makes up almost half of final energy consumption in the UK, more than the energy consumed for electricity or transport. The electrification of heat is anticipated to play a major role for the UK’s efforts to reduce emissions to net-zero by 2050. Heating demand is highly variable between seasons and time of day. To take maximum advantage of low-carbon generation, and to respect the limitations of the distribution grid, electricity loads for heating will need to be flexible. This Briefing Paper explores the potential for smart flexible low-carbon electric heating in UK homes and the challenges for consumer engagement. This paper considers four key elements for enabling smart, flexible and cost- effective electric heating in UK homes: low-carbon heating systems; cost-reflective electricity pricing; thermally efficient buildings; and smart storage devices

Advanced Warehouse Energy Storage System Control Using Deep Supervised and Reinforcement Learning

The world is undergoing a shift from fossil fuels to renewable energy sources due to the threat of global warming, which has led to a substantial increase in complex buildingintegrated energy systems. These systems increasingly feature local renewable energy production and energy storage systems that require intelligent control algorithms. Traditional approaches, such as rule-based algorithms, are dependent upon timeconsuming human expert design and maintenance to control the energy systems efficiently. Although machine learning has gained increasing amounts of research attention in recent years, its application to energy cost optimization in warehouses still remains in a relatively early stage. Suggested newer approaches are often too complex to implement efficiently, very computationally expensive, or lacking in performance. This Ph.D. thesis explores, designs, and verifies the use of deep learning and reinforcement learning approaches to solve the bottleneck of human expert resource dependency with respect to efficient control of complex building-integrated energy systems. A technologically advanced smart warehouse for food storage and distribution is utilized as acase study. The warehouse has a commercially available Intelligent Energy ManagementSystem (IEMS).publishedVersio

Integration of Renewables in Power Systems by Multi-Energy System Interaction

This book focuses on the interaction between different energy vectors, that is, between electrical, thermal, gas, and transportation systems, with the purpose of optimizing the planning and operation of future energy systems. More and more renewable energy is integrated into the electrical system, and to optimize its usage and ensure that its full production can be hosted and utilized, the power system has to be controlled in a more flexible manner. In order not to overload the electrical distribution grids, the new large loads have to be controlled using demand response, perchance through a hierarchical control set-up where some controls are dependent on price signals from the spot and balancing markets. In addition, by performing local real-time control and coordination based on local voltage or system frequency measurements, the grid hosting limits are not violated

Smart Energy, Plasma and Nuclear Systems

The extended papers in this Special Issue cover the topics of smart energy, nuclear systems, and micro energy grids. In “Electrical Loads and Power Systems for the DEMO Nuclear Fusion Project” and “Energy Analysis for the Connection of the Nuclear Reactor DEMO to the European Electrical Grid”, the authors introduce a European DEMO project. In “Comparison and Design of Resonant Network Considering the Characteristics of a Plasma Generator” the authors present a theoretical analysis and experimental study on the resonant network of the power conditioning system (PCS). In “Techno-Economic Evaluation of Interconnected Nuclear-Renewable Micro Hybrid Energy Systems with Combined Heat and Power”, the authors conducted a sensitivity analysis to identify the impact of the different variables on the investigated systems. In “Fault Current Tracing and Identification via Machine Learning Considering Distributed Energy Resources in Distribution Networks”, the authors propose a current tracing method to model the single distribution feeder as several independent parallel connected virtual lines, with the result of tracing the detailed contribution of different current sources to the power line current. From the five extended papers, we observe that the SEGE is actively engaged in smart grid and green energy techniques. We hope that the readers enjoy this Special Issue

Techno-economic projections until 2050 for smaller heating and cooling technologies in the residential and tertiary sector in the EU

This study provides data and projections for smaller heating and cooling technologies including an outlook till 2050. It complements a similar study on large-scale heating and cooling technologies in the EU. The data sets can be downloaded at http://data.jrc.cec.eu.int/dataset/jrc-etri-techno-economics-smaller-heating-cooling-technologies-2017JRC.C.7-Knowledge for the Energy Unio

Carbon Free Boston: Buildings 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: Transportation Technical Report; Carbon Free Boston: Waste Technical Report; Carbon Free Boston: Energy Technical Report; Carbon Free Boston: Offsets Technical Report; Available at http://sites.bu.edu/cfb/OVERVIEW: Boston is known for its historic iconic buildings, from the Paul Revere House in the North End, to City Hall in Government Center, to the Old South Meeting House in Downtown Crossing, to the African Meeting House on Beacon Hill, to 200 Clarendon (the Hancock Tower) in Back Bay, to Abbotsford in Roxbury. In total, there are over 86,000 buildings that comprise more than 647 million square feet of area. Most of these buildings will still be in use in 2050. Floorspace (square footage) is almost evenly split between residential and non-residential uses, but residential buildings account for nearly 80,000 (93 percent) of the 86,000 buildings. Boston’s buildings are used for a diverse range of activities that include homes, offices, hospitals, factories, laboratories, schools, public service, retail, hotels, restaurants, and convention space. Building type strongly influences energy use; for example, restaurants, hospitals, and laboratories have high energy demands compared to other commercial uses. Boston’s building stock is characterized by thousands of turn-of-the-20th century homes and a postWorld War II building boom that expanded both residential buildings and commercial space. Boston is in the midst of another boom in building construction that is transforming neighborhoods across the city. [TRUNCATED]Published versio