Integrating Energy Efficiency Research Articles

Enhancing Building Energy Management: Adaptive Edge Computing for Optimized Efficiency and Inhabitant Comfort

Nowadays, in contemporary building and energy management systems (BEMSs), the predominant approach involves rule-based methodologies, typically employing supervised or unsupervised learning, to deliver energy-saving recommendations to building occupants. However, these BEMSs often suffer from a critical limitation—they are primarily trained on building energy data alone, disregarding crucial elements such as occupant comfort and preferences. This inherent lack of adaptability to occupants significantly hampers the effectiveness of energy-saving solutions. Moreover, the prevalent cloud-based nature of these systems introduces elevated cybersecurity risks and substantial data transmission overheads. In response to these challenges, this article introduces a cutting-edge edge computing architecture grounded in virtual organizations, federated learning, and deep reinforcement learning algorithms, tailored to optimize energy consumption within buildings/homes and facilitate demand response. By integrating energy efficiency measures within virtual organizations, which dynamically learn from real-time inhabitant data while prioritizing comfort, our approach effectively optimizes inhabitant consumption patterns, ushering in a new era of energy efficiency in the built environment.

The Impact of Roof Coating and Solar PV System in the Tropical Region of Ghana

Adding PV module to roof has impacts on building`s electricity energy consumption. The aim of this paper is to assess the energy consumption performance of buildings by integrating solar Photovoltaic (PV) system into buildings with roof coating. An experiment was conducted to verify the efficient outcome of PV module using a building from the Anaji area of Takoradi in the Western region of Ghana. A framework energy model was proposed to analyse the integrated contribution of coating and PV performance using PVSOL. The temperature of the coated roof surfaces underneath the PV panels were significantly lower than that of the exposed roof in the daytime. The system integrated energy efficiency for flat and tilted overhead PV roofs are 63.35 % and 62.73 %, respectively. Using the mean absolute percentage error (MAPE) performance criterion, the monthly energy savings for coated roofs with solar PV is 28.86 kW or GH¢ 340.21; while the monthly energy savings for coated roofs without PV is 25.91 kW or GH¢ 303.00. Overall, the proposed integrated coated roof with PV outperforms the coated roof without PV. Validating the model, the mean relative errors (MRE) were all below 10%, while the accuracy of Power-Added Efficiency (PAE) were all beyond 95%. Thus, the proposed integrated roof coating and solar PV model for optimizing energy consumption is reliable.

A 22-pJ/spike 73-Mspikes/s 130k-compartment neural array transceiver with conductance-based synaptic and membrane dynamics.

Neuromorphic cognitive computing offers a bio-inspired means to approach the natural intelligence of biological neural systems in silicon integrated circuits. Typically, such circuits either reproduce biophysical neuronal dynamics in great detail as tools for computational neuroscience, or abstract away the biology by simplifying the functional forms of neural computation in large-scale systems for machine intelligence with high integration density and energy efficiency. Here we report a hybrid which offers biophysical realism in the emulation of multi-compartmental neuronal network dynamics at very large scale with high implementation efficiency, and yet with high flexibility in configuring the functional form and the network topology. The integrate-and-fire array transceiver (IFAT) chip emulates the continuous-time analog membrane dynamics of 65 k two-compartment neurons with conductance-based synapses. Fired action potentials are registered as address-event encoded output spikes, while the four types of synapses coupling to each neuron are activated by address-event decoded input spikes for fully reconfigurable synaptic connectivity, facilitating virtual wiring as implemented by routing address-event spikes externally through synaptic routing table. Peak conductance strength of synapse activation specified by the address-event input spans three decades of dynamic range, digitally controlled by pulse width and amplitude modulation (PWAM) of the drive voltage activating the log-domain linear synapse circuit. Two nested levels of micro-pipelining in the IFAT architecture improve both throughput and efficiency of synaptic input. This two-tier micro-pipelining results in a measured sustained peak throughput of 73 Mspikes/s and overall chip-level energy efficiency of 22 pJ/spike. Non-uniformity in digitally encoded synapse strength due to analog mismatch is mitigated through single-point digital offset calibration. Combined with the flexibly layered and recurrent synaptic connectivity provided by hierarchical address-event routing of registered spike events through external memory, the IFAT lends itself to efficient large-scale emulation of general biophysical spiking neural networks, as well as rate-based mapping of rectified linear unit (ReLU) neural activations.

Smart heat tariffs in transition to free market

Innovative pricing mechanisms should motivate heat suppliers and consumers to move toward more sustainable energy systems and introduce low-temperature district heating systems and sector coupling in smart energy systems. Therefore, district heating regulation regimes should also be changed to stimulate transformations in the energy sector. The district heating tariffs depend on many factors, including fuel prices, operational parameters, taxes, investments, and other criteria. Therefore, an analysis of the DH tariffs has been implemented to find solutions to motivate DH enterprises towards energy efficiency and climate neutrality. The analysis results are based on the decision-making assessment approach by selecting various criteria and evaluating them from five significant aspects: engineering, environmental, climate, economic and socioeconomic. The central elements within the developed fuzzy cognitive mapping model are investment costs, heat production costs, and primary energy consumption. Considering the set boundary conditions, the most beneficial method for smart heat tariff definition could be heat tariff benchmarking with integrated energy efficiency standards for DH operators.

Scenario data and full code associated with the article: Comparison of battery models integrating energy efficiency and aging for the design of microgrids

Scenario data and full code associated with the article: Comparison of battery models integrating energy efficiency and aging for the design of microgrids

Scenario data and full code associated with the article: Comparison of battery models integrating energy efficiency and aging for the design of microgrids

Scenario data and full code associated with the article: Comparison of battery models integrating energy efficiency and aging for the design of microgrids

Clean production of power and heat for waste water treatment plant by integrating sewage sludge anaerobic digester and solid oxide fuel cell

A Sewage Sludge Anaerobic Digester (SSAD) system integrated with a Solid Oxide Fuel Cell (SOFC) was modeled and optimized to reach an efficient/cost effective system for producing clean power and heat in Parand wastewater treatment plant (WWTP). The system modeling was performed by the use of 4E analyses (energy, exergy, economic, environmental). Based on 4E modeling and by the use of two objective functions (payback period and exergy efficiency) and seven design variables, SSAD-SOFC system was optimized for shorter payback period and higher exergy efficiency. This multi-objective optimization provided the optimum system operating specifications. From this type of investigation which was not observed in literature for SSAD-SOFC system, the results showed 58747 m3/day of biogas production as well as 7.5 MWel and 5.3 MWth electricity and heating generation, respectively at the optimum point. Furthermore, at the optimum point the integrated system overall energy and exergy efficiency were also 28% and 21%, with payback period of 1.7 years. Moreover, in comparison with a traditional system in which WWTP had to buy electricity and natural gas from the grid and burns fuel for heating requirements, the relative annual benefit of the SSAD-SOFC system increased by 17.9%. Finally, results from multi-objective optimization showed 6.9% improvement in overall energy efficiency and 7.5% enhancement in exergy efficiency in comparison with those for single-objective optimization with only payback period as the single objective function. The development of a sustainable and cost-effective procedure for optimum design of WWTP for electricity and heat generation as well as implementing of the above analysis in other integrated systems with similar equipment are implications of this research.

Synergistic planning of an integrated energy system containing hydrogen storage with the coupled use of electric-thermal energy

Regional integrated energy systems (RIES) can economically and efficiently use regional renewable energy resources, of which energy storage is an important means to solve the uncertainty of renewable energy output, but traditional electrochemical energy storage is only single electrical energy storage, and the energy efficiency level is low. Hydrogen energy storage has the advantages of large energy storage capacity, long storage time, clean and pollution-free, and can realize the synergistic and efficient utilization of electricity and thermal power. Based on this, this paper proposes a synergistic planning method for an integrated energy system with hydrogen storage taking into account the coupled use of electric-thermal energy, which effectively reduces the system carbon emission and improves the comprehensive energy efficiency level. Firstly, this paper constructs an electric-thermal coupling model of the hydrogen energy storage unit and proposes an optimization strategy for the integrated energy system containing hydrogen storage taking into account the utilization of electricity and thermal power. Secondly, a planning optimization model with the lowest economy and carbon emission and the highest comprehensive energy efficiency was constructed. Third, the CSPO-GE optimization algorithm is proposed for solving the problem, which significantly improves the solution efficiency. Finally, a planning optimization simulation of RIES for a residential community W in northern China verifies the effectiveness of the model and method proposed in this paper. The comparative analysis of the three schemes shows that compared with the integrated energy system with conventional electrochemical energy storage and heat storage tank as the main form of energy storage and the integrated energy system with only hydrogen storage, the integrated energy system with hydrogen storage and heat storage tank can reduce carbon emissions by 43.8% and 7.61%, respectively, and improve the integrated energy efficiency level by 337.14% and 14.44%.

Convergence of Energy Policies between the EU and Ukraine under the Green Deal Policy

EU countries declared the strategic goal to achieve energy independence and increase energy efficiency. In this case, EU countries have provided a vast range of incentives, mechanisms, and directives to promote energy efficiency. Ukraine as a potential candidate should provide a convergent policy with EU countries to increase energy efficiency. The paper aims to estimate energy efficiency based on the revealed convergent and divergent determinants of energy policies among the EU and Ukraine. The data are compiled from the World Energy Statistics Yearbook, the European Statistical Office, the International Energy Agency, SolAbility agencies, and State Statistics Service of Ukraine. The study applies σ- i β-convergence theory to determine the convergent and divergent determinants of the country’s energy efficiency. The empirical results allow concluding that Ukraine has an average level in the integrated energy efficiency index of the national economy, and the highest value of this index was in 2008. The highest values of energy efficiency were in Sweden and Denmark among EU countries. Besides, the findings confirm that the Ukrainian government should pay attention to divergent determinants (expenditure for environmental protection, pricing for energy resources, etc.) to improve the country’s energy efficiency.

Regional integration and city-level energy efficiency: Evidence from China

The improvement of energy efficiency is extremely vital for the sustainable development of cities since higher energy efficiency means lower energy inputs. Numerous studies investigate the direct impact of regional integration on energy efficiency, however, the potential impact of the relative size of the core-periphery cities has been ignored. This study constructs a theoretical model to explore the impact mechanism of regional integration on city-level energy efficiency. Using the panel data of 16 major urban agglomerations in China from 2003 to 2016, our findings show that regional integration significantly improves energy efficiency when the core-peripheral relative size is higher than 1.21. More specifically, the thresholds for core and peripheral cities are 0.98 and 1.35, respectively. Finally, this study provides policy suggestion on the promotion of energy efficiency and sustainable development of cities and discuss their applicability to different economies.

Beyond Energy Efficiency: A clustering approach to embed demand flexibility into building energy benchmarking

The intermittency of carbon-free renewables and the demand changes associated with the widespread push for electrifying the transportation and building sectors provides an opportunity for buildings to go beyond energy efficiency and push towards providing demand flexibility to the electricity grid. The duality of energy efficiency and demand flexibility is necessary for success in a sustainable and reliable energy transition. Current building energy benchmarking models are limited in their ability to integrate concepts of demand flexibility and/or utilize granular smart meter data. Thus, current benchmarking methods are focused annual energy usage and fail to incorporate how the time of use of energy consumption impacts emissions in a quickly changing energy grid. Without a more comprehensive view of energy usage and associated real-time emissions, current benchmarking methods are unlikely to realize the full decarbonization potential of buildings. New emerging data streams provide an opportunity to develop a new generation of benchmarking energy models that embed dimensions of energy efficiency, grid interactivity, and demand flexibility into their analysis. In this paper, we propose a four-step method for embedding grid interactivity and demand flexibility into building benchmarking models that utilizes emerging building and time-series electricity data streams. We first engineer features to produce a mix-type dataset that encompasses many attributes of grid-interactive and efficient buildings, and then we apply K-medoids using Gower's Distance to produce peer-group clusters. We apply the method to a case study of 306 primary and secondary schools in southern California, USA. The results show that the method effectively clusters buildings by attributes of demand flexibility and energy efficiency. The clustering results reveal patterns in inefficient building operations and demand inflexibility at the building peer group level. The interpretation of clusters can serve as an integrated energy efficiency and demand flexibility benchmarking model and inform performance-specific policy targeting for buildings that go beyond traditional efficiency measures.

An integrated energy efficiency evaluation method for forging workshop based on IoT and data-driven

Forging is an industry with high emissions and high energy consumption. Due to the constant increase in the international energy price and the negative impact on the world's environment, researchers have begun to focus on transforming forging into information and sustainable development. However, there remains a substantial gap in the development of the energy management process and energy-efficiency evaluation for complicated forging processes. Therefore, this paper defines a multi-level energy flow model and energy indicators with forging energy characteristics. Then, an energy management system for energy efficiency evaluation is developed based on IoT and data-driven. The energy consumption data are conceived for collection, transmission, storage, processing, mining, and application. Moreover, an integrated energy efficiency evaluation method is detailed with the system energy consumption data. Finally, a case study is carried out to verify the proposal's feasibility and credibility. Through the proposed evaluation method, a forging enterprise can make energy efficiency-optimization decisions.

Evaluation of the performance of water-cooled VRF system for heat exchanger geometry under part-load operation

In this study, static numerical simulation was used to evaluate the performance of a water-cooled variable refrigerant flow (VRF) system for geometry of plate-type outdoor heat exchanger. In general, heat exchanger is designed based on full-load operating condition. Since most of operation for VRF system is part-load operation, part-load operating characteristics should be considered to optimize entire system. The geometry characteristics are divided into chevron angle and vertical length. Numerical models of cooling and heating modes were developed for the VRF system, system performance was represented by integrated energy efficiency ratio (IEER) for the cooling system and coefficient of performance (COP) for the heating system by AHRI standard 1230. Regardless of operating mode, 20° of chevron angle among 20°, 35° and 45° is the optimal angle of outdoor heat exchanger. The energy efficiency was proportional to the vertical length of the plate heat exchanger and inversely proportional to the chevron angle. In the cooling mode, the energy efficiency ratio (EER) calculation converged at a shorter vertical length of the heat exchanger with a decrease in operating loads. The optimal vertical length is 1.7 m with only considering full-load, and 1.2 m with considering part-load operation. In the heating mode, the tendency of energy efficiency was similar to that of the cooling mode. The optimal vertical length is 1 m which is 0.2 m shorter than the optimal length in cooling mode.

A probabilistic-based framework for the integrated assessment of seismic and energy economic losses of buildings

Structural safety and environmental sustainability are major factors in investment decisions for building systems, but are rarely considered simultaneously. Recent research efforts have redressed this by developing assessment methodologies and technical solutions for integrated energy efficiency and seismic performance. These studies are typically limited to existing buildings and retrofit interventions at global building scale, whereas an effective framework could and should be part of the design process of either new or existing buildings at both building and component scales. This paper proposes a probabilistic-based assessment framework to assess the building performance in terms of integrated economic losses and support the selection of resilience-enhanced solutions. The proposed methodology is validated through its application to reinforced concrete case-study buildings consisting of traditional vs low-damage earthquake-resistant technologies coupled with energy efficiency strategies. Seismic and energy risk assessment analyses are performed accounting for both modelling uncertainties and earthquake/weather variability. Probabilistic distributions of the integrated economic losses are finally derived to compare the design solutions in terms of risk and reliability. The research outcomes demonstrate the effectiveness of the probabilistic approach for decision-making in building projects. Specifically, it is found that the economic losses can be highly underestimated (greater than40 %) in the single domains (energy or seismic); greater savings and return on investment can be achieved when the seismic safety is involved in the design process; probabilistic distributions and reliability/risk values can represent an effective tool to assess and compare design solutions.

A Tool to Assess the Interaction between Energy Efficiency, Demand Response, and Power System Reliability

Utilities are increasingly interested in integrating energy efficiency and demand response measures as a strategic approach that aims to achieve an increasingly reliable, dynamic, and integrated electric system. The concepts of energy efficiency (EE), demand response (DR), and system reliability (ESR) have been mainly studied from a different perspective, dealing only with the interaction between EE and DR and between EE and ESR. This paper aims to improve knowledge and demonstrate the validity of EE interventions (EEIs) through the use of a tool for evaluating the benefits of energy efficiency measures (EEMs) in the environmental sphere and in terms of DR and ESR. In order to evaluate this interaction, a quantitative method is proposed and validated on real results in an Italian case scenario, taking into account the analysis of smart meters data for residential users located in southern Italy in Calabria. Based on the collected data, an aggregation of users was evaluated with real hourly profiles covering the period from January 2020 to August 2020. These results show how efficient energy use may affect DR resource availability and power systems reliability. In conclusion, the authors justify that a more reliable electric system is ready for new types of EE financing systems based on pay-for-performance contracts.

Energy-efficient integration of assembly line balancing and part feeding with a modified genetic algorithm

Energy-efficient integration of assembly line balancing and part feeding with a modified genetic algorithm

High-Power Digital Transmitters for Wireless Infrastructure Applications (A Feasibility Study)

Fully digital transmitters (DTXs) have the potential of replacing analog-intensive transmitter (TX) line-ups in future massive multiple-input and multiple-output (mMIMO) systems since they hold the promise of higher system integration level and energy efficiency. DTX operation so far has been limited to low RF output powers. This article introduces a concept that enables high-power DTX operation. A DTX demonstrator targeting both high output power and high efficiency is realized as a proof of concept. It is based on a custom <inline-formula> <tex-math notation="LaTeX">${V_{T}}$ </tex-math></inline-formula>-shifted laterally-diffused MOS (LDMOS) technology, which is utilized to implement a segmented high-power output stage operated in class-BE. A low-voltage high-speed 40-nm CMOS controller drives the individual output stage segments at gigahertz rates. Measurements show the promising results for the proposed high-power DTX concept and provide valuable lessons for future DTX implementations.

Operation optimization of electric power - hot water - steam integrated energy system

The distributed integrated energy system can optimize the energy structure of the user side by using natural gas and realize the cascade utilization and low energy consumption of energy. This paper takes the integrated energy system as the research object, establishes the electric power ”source-network-load” model, the combined hydrothermal model and the steam network model, and proposes alternate iterative power flow solution method. On the basis of power flow solution, the integrated energy system optimization model is established with economy and system energy efficiency as the objective function, and the genetic algorithm toolbox is used to optimize the solution. The results show that the proposed operation optimization method is effective and feasible, which can effectively improve the integrated energy efficiency and realize the optimized operation of the integrated energy system.

Energy neutrality potential of wastewater treatment plants: A novel evaluation framework integrating energy efficiency and recovery

Energy neutrality potential of wastewater treatment plants: A novel evaluation framework integrating energy efficiency and recovery

Integrating energy efficiency into private home repair, maintenance and improvement practice in England and Wales

ABSTRACT The energy performance of housing is a crucial element in plans for climate change mitigation, future energy supply and addressing energy poverty. The age of the UK housing stock, and its slow rate of replacement, indicate that attention needs to be focussed in particular on improving existing homes, a high proportion of which are private owner occupied. Thus, the improvements necessary to achieve carbon reductions will require both large scale investment and likely lead to significant disruption. The thriving home repair, maintenance and improvement market, delivered largely by small building trades companies and sole traders, offers practical opportunities and a potential route to market for such improvements. Set against the context of high-level strategic targets, this paper draws on qualitative research at the micro level and presents a framework for the changes that will be needed to enable this to happen in practice, as well as insights into current practice and the existing regime in which the industry operates. Through application of a multi-level perspective to this socio-technical challenge, the work identifies the levels at which such changes should occur, and uses the results to develop and identify key weaknesses and solutions to enable change.