Energy Cost Savings Research Articles

Minimum-Energy Scheduling of Flexible Job-Shop Through Optimization and Comprehensive Heuristic

This study considers a flexible job-shop scheduling problem where energy cost savings are the primary objective and where the classical objective of the minimization of the make-span is replaced by the satisfaction of due times for each job. An original two-level mixed-integer formulation of this optimization problem is proposed, where the processed flows of material and their timing are explicitly considered. Its exact solution is discussed, and, considering its computational complexity, a comprehensive heuristic, balancing energy performance and due time constraint satisfaction, is developed to provide acceptable solutions in polynomial time to the minimum-energy flexible job-shop scheduling problem, even when considering its dynamic environment. The proposed approach is illustrated through a small-scale example.

Study on steam energy efficiency enhancement, cost management and CO2 emissions in the food industry

Malaysia’s energy intensity per unit GDP has been increasing since the 1990s, leading to the government’s efforts to promote energy efficiency via policies and initiatives such as Energy Performance Contracting (EPC). Additionally, the industrial sector in Malaysia consumed 28% of total final energy in 2018, placing it as the country’s second-largest final energy consumer [1]. This case study focuses on improving energy efficiency in the steam system of an existing plant in the food industry in Malaysia. This work was performed in collaboration with a local Energy Service Company (ESCO) to study the existing steam system, recognize its process requirements and constraints and consequently propose and evaluate retrofit opportunities. These opportunities were evaluated across 3 performance parameters (power output or energy savings, cost savings and CO2 emissions savings). Simulations were performed using the Steam System Modeler Tool (SSMT). The study found that Combined Heat and Power (CHP) was not feasible due to a combination of low steam pressure and flowrate available in the system. However, the study also found that improving condensate recovery coupled with condensate flashing from the high pressure to low pressure header offered the highest increments in overall performance.

Applied Economic Engineering To Solar Energy Projects

Background: The search for the use of electrical energy through renewable sources is experiencing significant expansion, particularly at a time when social policies are being implemented with a focus on climate conditions. Solar energy stands out as a renewable energy source with costs that are more accessible than conventional energy sources. Photovoltaic panels for commercial use represent a smart strategy for many companies seeking energy efficiency, cost savings, and sustainability. These systems offer benefits that range from reductions in operational expenses to contributions toward corporate social responsibility goals. Materials and Methods: To conduct this study, two research methods were used: bibliographic research and documentary research. The qualitative approach employed in this article enabled a detailed investment analysis of the elements related to economic engineering applied to solar energy projects. Techniques for economic and financial viability were presented, including Net Present Value (NPV), Internal Rate of Return (IRR), and Payback Period. Results: The findings of the research demonstrated that solar energy is a viable and strategic option for economic growth in Ceará. Considering that Ceará ranks fifth in Brazil for its capacity to generate solar energy, solar power represents a promising investment alternative for the state. The study highlighted the economic and environmental advantages of utilizing solar energy. Conclusion: The research clearly shows that solar energy not only contributes to economic growth but also plays a crucial role in environmental conservation in Ceará. Achieving the objectives reinforces the importance of government policies focused on expanding clean energy sources. These policies will ensure that the benefits of solar energy extend beyond the current scenario, fostering a more sustainable and inclusive future.

PENERAPAN ENERGI TERBARUKAN DI KAWASAN WISATA LUMBUNG MATARAMAN DESA BENDUNG GUNUNGKIDUL

The community service activities carried out focus on the application of renewable energy in the Lumbung Mataraman tourism area, Bendung Village, Semin, Gunungkidul. The community service activities carried out are strategic steps in supporting a sustainable green economy. By utilising appropriate technology (TTG) in the form of solar panels and wind turbines, this area is expected to reduce dependence on fossil energy and increase operational energy efficiency. In addition, the tourism area has the potential to become an educational model on the use of renewable energy, both for local communities and tourists. The methods used in this research include qualitative and quantitative approaches. The qualitative approach was conducted through interviews with local stakeholders, such as tourism area managers, communities, and renewable energy experts. In addition, field observations were conducted to understand energy needs and the potential for implementing renewable energy technologies. The quantitative approach involved analysing current energy consumption data and calculating the potential of renewable energy that can be applied, such as solar panels and wind turbines. The results of the activities show that the implementation of renewable energy in Lumbung Mataraman can reduce dependence on fossil energy sources, lower carbon emissions, and provide additional economic benefits through energy cost savings and educational media in the use of renewable energy.

Research on Intelligent Energy System and Power Metering Optimization Based on Multi-objective Optimization Decision Algorithm

In this paper, the intricate problem of optimizing power metering within an intelligent energy system, utilizing a multi-objective optimization decision-making algorithm, is thoroughly explored. Given the current energy landscape, achieving efficient energy utilization and environmental sustainability has become a focal point of research. As a pivotal aspect of future energy management, the precision and optimization of power metering in intelligent energy systems directly influence the effectiveness and cost of energy consumption. To begin, this paper delves into the fundamental principles and application backdrop of intelligent energy systems, highlighting the significance of power metering in such systems. Subsequently, addressing the multi-objective optimization challenges in power metering, a novel optimization method based on a multi-objective optimization decision algorithm is introduced. This algorithm achieves comprehensive optimization of power metering, encompassing multiple objectives such as power cost reduction, enhanced energy efficiency, and environmental protection. The experimental results underscore the remarkable performance of this algorithm, which not only elevates the precision of power metering but also achieves substantial savings in energy costs and significantly boosts energy efficiency. Furthermore, the algorithm exhibits robust adaptability, making it capable of addressing power metering optimization challenges across diverse scenarios. Finally, this paper discusses the practical application prospects of the optimization algorithm in intelligent energy systems, and points out the direction of future research. The research in this paper provides new ideas and methods for the optimization of power metering in intelligent energy systems, and has important theoretical and practical significance for promoting the intelligence and refinement of energy management.

EASL: Enhanced append-only skip list index for agile block data retrieval on blockchain

The weakness of blockchain is widely recognised as the linear, temporal cost required for retrieving data due to the sequential structure of data blocks. To address this, conventional approaches have relied on database indexing techniques applied to each individual replica copy of a blockchain. However, this only partially addresses the problem, because if the index is not distributed it is not available for devices in the blockchain network. If an index is to be incorporated and distributed within blockchain, the unique attribute of immutability necessitates a more innovative approach. To that end, we propose an Enhanced Append-only Skip List (EASL). This specialised indexing technique utilises binary search with skip lists in blockchain, resulting in a sublinear cost for data retrieval. The EASL indexing technique is maintained by each newly appended blockchain block and offers enhanced readability and robustness using an explicitly recorded index structure. Our proposed technique is 42% more efficient in computing and 60% more efficient in storage consumption than its predecessor, the Deterministic Append-only Skip List (DASL) indexing technique. This is achieved through agile data retrieval, resulting in energy cost savings from less computational effort to maintain the index, and less network bandwidth to retrieve blockchain data. The code for the proposed technique is publicly available on GitHub {https://github.com/jarednewell/EASL/}, to expedite future research and encourage the practical application of this effectual data index.

Sustainable Cost Management and Green Business: The Role of Managerial Accounting Innovations

This research explores the impact of innovations in managerial accounting on sustainable cost management, focusing on the integration of green business practices. The objectives are to analyze how technological, process, strategic, and organizational innovations contribute to cost savings and sustainability performance, and to provide recommendations for practitioners and policymakers. A quantitative research design was employed, utilizing case studies from various industries. Data collection involved detailed analysis of company reports and sustainability metrics, while statistical techniques were used for data analysis. Key findings reveal that big data analytics and real-time reporting significantly enhance energy efficiency and cost savings, aligning with existing literature on the benefits of data-driven decision-making. Activity-Based Costing (ABC) and Environmental Management Accounting (EMA) improve cost allocation accuracy and environmental cost tracking, resulting in substantial cost reductions. Strategic frameworks like the Balanced Scorecard (BSC) and Life-Cycle Costing (LCC) effectively integrate sustainability goals with business objectives, promoting long-term financial and environmental benefits. Organizational practices, including cross-functional teams and strong top management commitment, are crucial for successful sustainability initiatives. The study concludes that these innovations in managerial accounting are vital for achieving sustainable cost management. Recommendations for practitioners include investing in advanced technologies, adopting strategic costing methodologies, and fostering a collaborative organizational culture. Policymakers are advised to create incentives and regulations that encourage sustainable practices. Future research should focus on the long-term impacts of these practices, industry-specific adaptations, and the socio-economic benefits of sustainable cost management. This research contributes to the growing body of knowledge on sustainable business practices and provides practical guidance for enhancing sustainability through managerial accounting innovations.

Humidity-aware model predictive control for residential air conditioning: A field study

Model predictive control of residential air conditioning could reduce energy costs and greenhouse gas emissions while maintaining or improving occupants’ thermal comfort. However, most approaches to predictive air conditioning control either do not model indoor humidity or treat it as constant. This simplification stems from challenges with modeling indoor humidity dynamics, particularly the high-order, nonlinear equations that govern heat and mass transfer between the air conditioner’s evaporator coil and the indoor air. This paper develops a machine-learning approach to modeling indoor humidity dynamics that is suitable for real-world deployment at scale. This study then investigates the value of humidity modeling in four field tests of predictive control in an occupied house. The four field tests evaluate two different building models: One with constant humidity and one with time-varying humidity. Each modeling approach is tested in two different predictive controllers: One that focuses on reducing energy costs and one that focuses on constraining electric power below a utility-specified threshold. The two models lead to similar performance for reducing energy costs. Combining the results of this study and a prior heating study of the same house, the estimated year-round energy cost savings were $340–497 or 22%–31% (95% confidence intervals); these savings were consistent across both humidity models. However, in the demand response tests, the simplifying assumption of constant humidity led to far more frequent and severe violations of the power constraint.

Striding towards a greener future: Unlocking the potential of natural resources and employment dynamics in green energy transition in sub‐Saharan Africa

AbstractThe adoption and utilization of renewable energy offer potential benefits such as enhanced energy efficiency, cost savings, and ecological advantages. However, a key research question addressed in this analysis is whether natural resource rent and employment dynamics influence renewable energy consumption in Africa. Previous research has predominantly focused on the aggregate employment rate, overlooking the nuances of labor diversity across sectors and employment types. Hence, this study evaluates the importance of natural resource rent and employment in driving the transition to green energy in sub‐Saharan Africa from 1991 to 2022. It employs the innovative method of moments quantile regression (MMQR) model for this purpose. The findings reveal a positive connection between natural resource rent and the adoption of green energy. When considering employment types, the study observes that self‐employment and wages/salaried workers undermine clean energy utilization. Moreover, the study highlights that employment across key economic sectors also plays a role. While employment in the agriculture and service sectors fosters green energy utilization, employment in the industrial sector impedes renewable energy consumption. To advance the development of green energy in Africa, this study underscores a range of policy options.

Mathematical model of the process of mixing semi-liquid feeds in a device with a propeller

The article considers the issues of using a propeller apparatus for mixing semi-liquid feed mixtures in a mixer with an eccentrically positioned working body in the form of a propeller (screw). Until now, when studying the mixing process, little attention has been paid to the transporting ability of the working body in the form of a propeller agitator. When preparing wet mixtures, agitators with a vertically positioned shaft, which is located in the center of a vertical cylindrical tank, are widely used. When installing the working body horizontally, the propeller having a pumping effect (axial movement), can be used not only for mixing, but also for unloading the finished feed mixture, as well as moving it through pipes over short distances. The existing models of the mixing process do not take into account its stochastic nature. Methods of mathematical description of mixing processes considering the prevailing axial movement of the flow are scarcely developed. The proposed mathematical models make it possible to determine the mixer's performance and the required mixing power. The research was aimed at increasing the effectiveness of preparing a feed mixture in a horizontal mixer of propeller type with an eccentrically positioned working body (screw) and saving energy costs along with raising the productivity. The object of the study was a mixing chamber with eccentrically located working bodies of various diameters (0.2, 0.25 and 0.35 m). During the experiments, the productivity required to drive the motor shaft was determined. It has been experimentally established that increasing the agitator rotation speed from 200 to 400 min-1 with a propeller diameter from 0.2 to 0.35 m and a feed mixture humidity of 84 % leads to an increase in power consumption to 3.5 kW and mixer productivity to 12 m3/h, and the degree of uniformity of feed mixtures is up to 98 %.

Indoor Environment Design and Energy Saving Analysis of Sustainable Development Integrated with Green Building

Modern architectural design has gradually distanced itself from the actual living needs of urban residents in the process of pursuing the integration of architecture and nature. To achieve the perfect combination of sustainable ecological concepts and effective energy utilization, green buildings have become an actively pursued design concept. Unlike relying solely on high-tech means, the core goal of green buildings is to build an environmentally friendly building environment by achieving sustainable and efficient utilization of energy and resources. In the design phase, green buildings should focus on functionality and economy, and be tailored to the local economic conditions, regional characteristics, natural resources, and climate conditions of the building's location to create green buildings with unique architectural and regional characteristics. This article endeavors to furnish both theoretical underpinnings and practical directives for the indoor environment design and energy conservation efforts of green buildings. By delving into the pivotal role of indoor environments as an essential architectural component, it integrates sustainable development principles with green building practices and delves into the intricate relationship between indoor environment design and energy efficiency, thus offering valuable insights and guidance for achieving sustainable and energy-efficient indoor spaces. In this process, this article examines the energy and resource utilization benefits that green building design can achieve, as well as the specific impact of indoor environment improvement on the quality of life of residents. Through an in-depth analysis of these aspects, this article aims to provide substantial contributions to achieving the sustainable development goals of green buildings. The experimental comparison results show that in terms of natural ventilation design, compared to mechanical ventilation, the proposed scheme can achieve an annual energy cost savings of 20%.

Looking beyond energy efficiency targets: Life cycle sustainability of mechanical and water heating equipment in Canadian homes

The building sector's impacts on climate are widely acknowledged, leading to policies and standards promoting energy-efficient buildings. In order to achieve sustainability in a holistic sense, the environmental, social, and economic impacts of equipment used in buildings need to be evaluated. In this regard, a novel decision support framework is introduced to evaluate the heating and cooling equipment in single-family detached homes. Energy simulation, life cycle environmental, social, and economic analyses, and a multi-criteria decision-making method are used to identify the most sustainable set of equipment. This framework is demonstrated through its application on mechanical and water heating equipment in three existing residential buildings of varying energy efficiencies (low, medium, and high, the latter being net-zero home) over a 50-year study period.The results indicate that the carbon footprint of a natural gas furnace is six times higher than that of other equipment. In contrast, the drain water heat recovery unit showed the lowest impacts attributed to lower material and energy usage. For most equipment, the product stage accounted for more than 50% of the total impacts. When grouped, the equipment in the low-efficiency home showed the highest environmental impacts, while the equipment in the medium-efficiency home had higher social and economic impacts. Overall, the equipment set in a net-zero home is the best choice under equal, pro-social, and pro-economic scenarios and only lags behind the equipment set in a medium-efficiency home for pro-environmental scenario. The work will help improve sustainable building policies beyond immediate energy and operational cost savings.

An energy efficiency and cost analysis of utilizing high-intensity profile UVC systems on air handling unit under cool-humid climate

The feasibility of the ultraviolet germicidal irradiation (UVGI) application has been proven over the past few decades, especially in disinfection performances; however, a small number of studies were found that explored the energy efficiency improvement and cost savings of real buildings by implementing the UVC systems on cooling coils. The goal of this study is to verify the energy efficiency improvements and cost savings of AHU in a real building environment by removing biofilms on the cooling coil surfaces with the UVC irradiation techniques that can provide higher lamp output (300 μW/cm2) as well as higher intensity levels (1000–4000 μW/cm2) on the cooling coil surfaces. A series of experiments were conducted in an AHU in a medical center located in Michigan, US, to estimate energy efficiency improvement of cooling coils, chiller, and fan with UVC application. The results show that after 7 weeks of UVC operation increased coil overall enthalpy-based thermal conductance by 15.62 %, achieved chiller-side energy savings by up to 28.2 %, reduced pump energy by 32.1 %, and fan energy by 17.7 %. A return on investment (ROI) based only on energy savings is estimated to be 43 % and has a payback period of 2.32 years. When the labor, chemical, and water-saving costs for coil cleaning were included, the ROI was increased to 49 % and reduced the payback period to 2.04 years. When it comes to UVC's disinfection performances, six pathogens showed a more than 99 % removal rate while Klebsiella pneumoniae and Clostridium difficile showed a relatively lower 94 % removal rate.

Neural network energy management strategy for plug-in hybrid electric combine harvesters based on quasi-periodic samples

Energy management strategies are crucial for Plug-in Hybrid Electric Combine Harvester (PHECH). However, many existing approaches rely on rigid, pre-setting rules that struggle to adjust to the PHECH operational conditions. This paper first introduces a power estimation model tailored to the quasi-periodic process of harvester activity. Then, Dynamic Programming (DP) is applied to derive optimal samples of engine power ratio across various scenarios. Building on the samples, a Neural Network (NN) is developed to enhance the strategy's economic and real-time performance. Simulation tests evaluate the proposed algorithm's efficacy and its energy conservation potential. The findings suggest that, compared to fuel-driven harvesters, the NN strategy achieves similar energy cost savings to the DP approach, exceeding 11%, which is better than the Charge Depleting and Charge Sustaining (CDCS) strategy's 7.22% and the MPC-ECMS strategy's 7.87%. Moreover, the NN strategy reduces the time expense to roughly one-fifth of that required by the DP approach.

Infrared signal-based implementation of model-based predictive control (MPC) for cost saving in a campus building

Model-based predictive control (MPC) is an advanced control method that is used to achieve energy and cost savings in building energy management. However, there are various challenges to implementing MPC in actual buildings, such as additional engineering costs, physical damage to systems, and security concerns. This study proposes a non-intrusive implementation method for MPC based on a low-cost communication system. Firstly, a grey-box building model was developed along with the heating, ventilation, and air conditioning (HVAC) models based on the actual measurements of the test building. A simulation case study of MPC was performed, along with baseline feedback control, using these constructed models. The MPC outperformed the feedback control in terms of comfort, electricity consumption, and cost. It was implemented in an actual test zone to demonstrate the feasibility of a low-cost and non-intrusive implementation method that was realized using Arduino-based infrared signal communication and to evaluate the cost-saving potential of the MPC when compared with the baseline control. This experiment was conducted under a confined schedule for occupancy and set-point temperature for three days for the MPC and two days for the baseline feedback control in the cooling season. The cost savings of the MPC are as high as 5.8 %. Additional feedback cases were considered with a non-confined occupancy schedule and set-point temperature. The resulting energy consumption and cost savings are 25.2 % and 33.7 %, respectively. In this study, the applicability of the Arduino-based low-cost and non-intrusive implementation method for MPC was demonstrated, and the actual saving percentage of the MPC was compared with the conventional control method in a real building.

Contemporary roof pattern for energy efficient buildings: Air conditioning cost alleviation, CO2 emission mitigation potential and acceptable payback period

Buildings account for a significant portion of global energy use and consumption. Buildings have substantial energy consumption due to the use of heating, ventilation, and cooling systems. It is evident that the use of insulation materials and phase change materials (PCMs) in the design of buildings can effectively reduce the cost of air conditioning by reducing external heat gains and losses. Additionally, the use of environmentally friendly, cost-effective, and natural materials can be beneficial from an environmental standpoint. This paper aims to evaluate the potential for cost savings in the air conditioning of various PCMs and insulation-stuffed building roof configurations. In that respect, four types of phase change materials (HS29, HS36, FS42, and FS30) and four insulation materials (Therma cork, sawdust, aerogel, and sheep wool) were selected. The thermophysical properties of PCMs (solid and liquid state), insulation materials, and building elements were determined experimentally as per ASTM D 5334 standards. Ten various building roof models (contemporary roof pattern) are studied with four various PCMs and four various insulations. In addition, novel building roof design integrated with PCM/insulation were analysed numerically, related to environmental conditions that refer to two different scenarios in India (hot dry and composite climates). It further analyses the reduction in greenhouse gas emissions associated with different roof configurations. The aforementioned PCM/insulation materials were stuffed in the void spaces of the contemporary roof pattern. Thermo-economic analysis of novel roof design with PCM/insulation materials on air-conditioning costs, carbon dioxide emissions and payback time are compared with conventional roofs (CR) and contemporary roof patterns (CRP). The thermo-economic analysis was carried out based on the number of degree-hours of heating and cooling to determine the building's annual energy usage. HS29 PCM stuffed roof pattern (HS29RP) saved the highest total energy cost savings of 11.89/14.71 $/m2/year when compared with conventional roof and 11.35/13.89 $/m2/year compared with contemporary roof pattern for Jabalpur/Kota climatic conditions. HS29 PCM stuffed roof pattern (HS29RP) exhibits the maximum carbon emission mitigation of 215.32/275.37 kg/kWh when compared with conventional roof and 204.95/259.57 kg/kWh for climatic conditions of Jabalpur/Kota. While considering shortest payback span, sawdust stuffed roof pattern shows the minimum payback period of 0.69 and 2.15 years when compared with conventional roof and contemporary roof pattern. The findings of this research offer significant contributions to the development of energy-efficient building envelopes applicable to a wider range of buildings, including those with and without air conditioning systems.

The Impact of Smart Home Technologies on Energy Efficiency, Cost Savings, and Environmental Benefits

The results of this study addressed the effectiveness of smart home technologies in terms of energy consumption, cost reduction, and environmental advantages in Nigerian homes. Given the growing energy requirements and concern for the environment, assessing the efficiency of such technologies is critical for socioeconomic development. We collected data using a combination of surveys and statistical analysis in five major Nigerian cities: Lagos, Abuja, Kano, Port Harcourt, and Enugu. We evaluated smart home technologies such as smart thermostats, lighting systems, appliances, plugs, and energy monitoring systems based on their energy savings (%), monthly cost savings (NGN), kilogram of CO2 emissions cut, and percent adoption. We used descriptive analysis and regression modeling to analyze the data collected from the respondents. The introduction of smart technologies reduced general energy use by fifteen to twenty-five percent, with smart appliances recording the highest reduction of up to 25%. This feature demonstrated how monthly cost savings varied depending on the technology and geographical location, resulting in significant increases of up to 4000 NGN per household, each household saw a reduction in CO2 emissions by 500 kg to 700 kg annually, resulting in significant environmental benefits. According to the studies, smart home technologies can help promote energy conservation and therefore reduce CO2 emissions in Nigerian households. However, there are still widely recognized obstacles, like high initial costs and a low level of awareness. offering financial incentives, improving Information Promotion of existing policies and overhauling the distribution systems to increase the pace of uptake and impact returns.

Strategic Evaluation of Sustainable Practices for HVAC Systems in Small and Medium-Sized U.S. Manufacturers

Abstract This paper investigates the often overlooked yet crucial role of Heating, Ventilation, and Air Conditioning (HVAC) systems in advancing sustainable manufacturing practices in the United States. Through all outcomes of the energy assessments conducted by the Industrial Assessment Centers (IACs) in various industrial settings, the current study focuses on the energy consumption of HVAC systems and assesses the impact of their energy-efficient measures on the overall industrial energy usage. In-depth analysis covers both technological and economic facets of resource management practices, utilizing case studies and data from energy assessments on 20,818 small- and medium-sized manufacturing facilities. The results reveal substantial potential for reducing energy consumption, estimated at 71.9 million MMBtu per year, along with annual energy cost savings of approximately $744 million per year and a noteworthy mitigation of 8.7 million metric tons of CO2 emissions per year, all achievable through HVAC system improvements. These findings show the practical significance of sustainable HVAC practices and their potential to improve energy efficiency and mitigate the environmental impact within the manufacturing sector.

Electrochemical deposition combined with high-temperature molecular sieve adsorption strategy: Efficient removal of key fission element yttrium for purification of radioactive molten salts

In order to realize energy cost savings in waste salt recycling and electrolysis processes during the nuclear fuel cycle, this paper presents a novel approach for the purification of waste molten salt by employing molecular sieves to absorb excess fission products selectively. The method is founded on the principles of electrolytic refining to achieve sustainable development of reprocessing. In this study, a systematic investigation of the electrochemical reduction/oxidation processes of Y(III)/In(III) was performed on electrode, as well as the electrode reaction of Y(III) on an In electrode at 773 K. Constant-current electrolysis produced an extraction rate of 93.11 % for Y(III) on the In electrode. In order to improve the current efficiency, greatly save the processing cost, and realize the sustainable development of dry post-processing. Subsequently, the waste molten salt environment following electrolysis was simulated, and the fission product was effectively adsorbed utilizing 5A molecular sieves, resulting in a yttrium removal rate of up to 99.94 %. This process not only significantly reduces the cost of electrolysis but also enhances the removal efficiency of target nuclides. The study examined the molten salt adsorption mechanism of molecular sieve, determining the primary adsorption mechanism to be chemical one (ion exchange), through the application of pseudo-first-order, pseudo-second-order, and Weber-Morris kinetic models for re-evaluation.

Utility-based context-aware multi-agent recommendation system for energy efficiency in residential buildings

A significant part of CO2 emissions is due to high electricity consumption in residential buildings. Using load shifting can help to improve the households’ energy efficiency. To nudge changes in energy consumption behavior, simple but powerful architectures are vital. This paper presents a novel algorithm of a recommendation system generating device usage recommendations and suggests a framework for evaluating its performance by analyzing potential energy cost savings. As a utility-based recommender system, it models user preferences depending on habitual device usage patterns, user availability, and device usage costs. As a context-aware system, it requires an external hourly electricity price signal and appliance-level energy consumption data. Due to a multi-agent architecture, it allows for easy integration of new agents, enabling seamless functionality expansion, or the disabling of existing agents to tailor the system to specific needs. Empirical results show that the system can provide energy cost savings of 18% and more for most studied households.