Scheduling of Multiple Energy Consumption in The Smart Buildings with Peak Demand Management

The global energy crisis and the depletion of fossil fuels have become pressing concerns, leading experts to search for alternative solutions. This paper presents an analysis of the day-ahead operation of the multi-carrier energy system (MCES) with the aim of minimizing operational costs, reducing pollution emissions, and maximizing consumers' comfort. The authors propose an optimal scheduling strategy called energy demand curtailment (EDCS), which aims at efficiently managing electrical energy consumption. Additionally, they consider an on-site generation strategy (OGS) for consumers to operate their own energy storages. Both EDCS and OGS are modeled based on demand-side management (DSM). To optimize these strategies and achieve their objectives, fuzzy logic is employed as an optimization approach along with objective functions. Finally, two scenarios are examined through numerical simulations to illustrate the effectiveness of this approach in optimizing energy utilization in MCE

Scheduling of Multiple Energy Consumption in The Smart Buildings with Peak Demand Management

The global energy crisis and the depletion of fossil fuels have become pressing concerns, leading experts to search for alternative solutions. This paper presents an analysis of the day-ahead operation of the multi-carrier energy system (MCES) with the aim of minimizing operational costs, reducing pollution emissions, and maximizing consumers' comfort. The authors propose an optimal scheduling strategy called energy demand curtailment (EDCS), which aims at efficiently managing electrical energy consumption. Additionally, they consider an on-site generation strategy (OGS) for consumers to operate their own energy storages. Both EDCS and OGS are modeled based on demand-side management (DSM). To optimize these strategies and achieve their objectives, fuzzy logic is employed as an optimization approach along with objective functions. Finally, two scenarios are examined through numerical simulations to illustrate the effectiveness of this approach in optimizing energy utilization in MCE

DEVELOPMENT OF INFORMATION COMPETENCE OF FUTURE TEACHER OF INITIAL CLASSES IN VOCATIONAL AND EDUCATIONAL ACTIVITIES

Information competence of a person is directly related to the process of informatization of society. The exponential growth of information affects society and leads to its informatization. This article considers the information competence of future elementary school teachers as a necessary component of their professional competence

DEVELOPMENT OF INFORMATION COMPETENCE OF FUTURE TEACHER OF INITIAL CLASSES IN VOCATIONAL AND EDUCATIONAL ACTIVITIES

Information competence of a person is directly related to the process of informatization of society. The exponential growth of information affects society and leads to its informatization. This article considers the information competence of future elementary school teachers as a necessary component of their professional competence

DEVELOPMENT OF INFORMATION COMPETENCE OF FUTURE TEACHER OF INITIAL CLASSES IN VOCATIONAL AND EDUCATIONAL ACTIVITIES

Information competence of a person is directly related to the process of informatization of society. The exponential growth of information affects society and leads to its informatization. This article considers the information competence of future elementary school teachers as a necessary component of their professional competence

Mathematical model of the solar combined cycle power plant using phase change materials in thermal energy storage system (Thermodynamic analysis)

This research presents a novel mathematical framework for optimizing solar combined cycle power plants, with a particular emphasis on the exergy analysis of various superheating heat exchanger configurations used in thermal energy storage. The importance of phase change materials (PCMs) in improving the thermodynamic efficiency of solar combined cycle power plants is emphasized in this study. The investigation includes three configurations, two with a single PCM and one with two PCMs. The use of PCMs is intended to increase storage density, reduce volume, and maintain consistent temperatures, thereby favoring latent energy storage. The model developed evaluates exergy efficiency and output temperature profiles during the charging and discharging processes. The results show that the single PCM configuration has an impressive charging efficiency of 93.12 %, reaching an output temperature of 371 °C in 8 h. The two PCM configurations, on the other hand, achieve even higher efficiency at 94.89 % during charging, with an output temperature of 367 °C over a slightly longer 10-hour period. This comparison emphasizes the benefits of using two PCMs, demonstrating increased exergy efficiency and a marginal increase in output temperature over a single PCM setup. Furthermore, a comparison of the outcomes resulting from the use of a single type of PCM in exchangers reveals that the disparity in PCM melting temperatures causes only minor variations in the system's efficiency. The findings emphasize the significance of optimal PCM utilization for efficient solar energy retention, particularly during periods of low radiation

Heat recovery from oxy-supercritical carbon dioxide cycle incorporating Goswami cycle for zero emission power/heat/cooling production scheme; techno-economic study and artificial intelligence-based optimization

This research aims to explore the economic and energy efficiency ramifications of combining the supercritical carbon dioxide oxy-fuel cycle with the Goswami cycle in the context of integrated heating and cooling systems, as well as power generation. Oxy-fuel systems, known for their high operating temperatures. In oxy-fuel systems, gas turbine exhaust gases typically preheat incoming flows to the combustion chamber. Nevertheless, even after preheating the combustion chamber inlets, the exhaust gases from the gas turbine retain a relatively high temperature, demonstrating considerable potential for energy production. Through a comprehensive parametric study, the impact of independent parameters on system performance is systematically explored. Subsequently, a three-stage economic analysis, total capital investment cost estimation, total operating cost estimation, and income evaluation, is conducted. The investment return time is assessed based on the selling price of system products. In the final step, a genetic algorithm, combined with artificial intelligence, optimizes the system for rational and optimal economic and energy conditions. The research findings reveal that in the absence of the Goswami cycle, the system yields 13.5 MW of power and 8.5 MW of heating, with an investment return time of approximately 16.32 years. However, with the inclusion of the Goswami cycle, power production increases to 15 MW, accompanied by 5 MW of cooling and 6.7 MW of heating. Despite augmented initial and operational costs, the investment return time is significantly reduced to 9.9 years. The results of a three-objective optimization strategy, focusing on maximizing power, heating, and cooling, highlight the system's versatility. Opting for maximum power production enhances power by 12.53 % and cooling by 27.48 %, compared to the reference mode. However, heating production decreases by 37.01 %. Notably, total capital investment costs show improvement by about 4.54 %, and the pay-back time experiences a substantial reduction of approximately 27.68 %. Moreover, the levelized cost of energy decreases from 111.4 $/MWh in the reference state to 106.9$/MWh, underscoring the economic efficiency of the integrated system

Comparative analysis of analytical and numerical approximations for the flow and heat transfer in mixed convection stagnation point flow of Casson fluid

A mathematical description of non-Newtonian mixed convective Casson fluid stagnation point flow and transfer of heat exists in terms of partial differential equations. We considered the same to study it further under the effects of unsteadiness and varied film thickness parameters. For inclusion of these parameters in the flow model study we modified the available similarity transformations. The governing equations with three independent variables are converted into ordinary differential equations by employing the modified invertible transformations. For the mass and heat transfer in the mixed convection stagnation point unsteady flow of Casson fluid over a stretching sheet, a detailed comparative analysis is carried out in this paper, of the analytical and numerical approximation techniques. The Homotopy Analysis Method is applied for the analytical solutions while the Runge-Kutta with a Shooting Method (RKF45) and Finite Difference Method are used for obtaining the numerical solutions. With these solution schemes we present an analysis of velocity and temperature profiles under the effects of embedded parameters such as the Casson fluid parameter, unsteadiness parameter, mixed convection parameter, Prandtl number, Eckert number, and stretching ratio. The results are presented in both graphical and tabulated forms and they illustrate the dependence of mass and heat transfer characteristics of Casson fluid upon the embedded parameters. Further, we have shown an agreement between the analytical and the approximate solutions for the considered flow and heat transfer which reflects a validation of the results presented here

Modeling of thermal energy saving in commercial buildings of Australia by balanced tree growth optimizer

Low-energy cases can be designed more efficiently by using analytical optimization. The non-linear thermal performance of buildings has led to the development of optimization techniques based on simulation. In building optimization, it is important to achieve superior solutions while minimizing calculation expenses. This study aims to optimize an Australian office building using the Balanced Tree Growth Optimizer (BTGO). It has resulted that more than 11.7 % of energy can be saved by the optimization process and also some energy-saving measures. A comparison of the utilized algorithm with benchmark algorithms including the Nelder-Mead method, hybrid Particle Swarm Optimization, Hooke-Jeeves, and Ant Colony Optimization for continuous domain showed that the BTGO can achieve better solutions and needs less computational time

Coupled heat and mass transfer mathematical study for lubricated non-Newtonian nanomaterial conveying oblique stagnation point flow: A comparison of viscous and viscoelastic nanofluid model

The lubrication phenomenon plays a novel role in the chemical industries, manufacturing processes, extrusion systems, thermal engineering, petroleum industries, soil sciences, etc. Owing to such motivated applications, the aim of the current work is to predict the assessment of heat and mass transfer analysis for non-Newtonian nanomaterial impinging over a lubricated surface. The flow is subject to the oblique stagnation point framework. The lubricated phenomenon is observed due to viscoelastic nanofluid. The impacts of chemical reaction are also endorsed. The fundamental conservation laws are utilized to model the flow problem and similarity transformation are used to transform the governing system of partial differential equations into ordinary differential equations. A thin layer of power law lubricant is used to enhance the lubrication features. The numerical object assessment regarding the simulation process is captured by implementing the Keller Box scheme. The physical characterization endorsing the thermal fluctuation with flow parameters is inspected