Auxiliary Boiler Research Articles

Management and real-time monitoring of interconnected energy hubs using digital twin: Machine learning based approach

Getting equipped by highly new smart technologies, Energy Hubs (EHs) and Smart Grids (SGs) are gaining interest these days. Energy management will advance over time as a result of the interaction impact among power and natural gas grids, and the use of smart technology for communications. The present study proposes a novel approach entitled Smart EH (SEH) for modeling multi-carrier energy systems in SG environments. Furthermore, this paper determines the optimum management and sizing of combined heat and power, auxiliary boiler, absorption chiller, as well as transformer unit as the essential components of an SEH. It is difficult to address the requirements of SGs with most conventional load scheduling algorithms because they lack robustness and performance in complex environments. An evaluation of the benefits and costs of optimizing such parameters was carried out in this paper and the Reinforcement Learning (RL) algorithm is applied to solve the optimization problem. An individual user in a dynamic electrical market was examined as an SEH in support of the suggested approach. According to simulation outcomes, the suggested method is effective regarding time efficiencies and load variations.

DISPERSION OF SO2 AND NO2 EMITTED BY AUXILIARY BOILER OF PT KMI METHANOL INDUSTRIAL USING THE GAUSSIAN PLUM MODEL AERMOD IN BONTANG CITY EAST KALIMANTAN INDONESIA

The petrochemical industry PT Kaltim Methanol Industri Bontang City, uses auxiliary boilers with natural gas fuel and is connected to the stack to emit pollutants into the atmosphere. The objectives of this study are SO2 modeling with a radius of 5 kilometers and modeling of NO2 with a radius of 10 kilometers from the emission source. Modeling using AERMOD software, AERMET Software, and Aermap ArcGIS Software. The wind rose in the dominant research area from the southwest and northeast directions. Dispersion of SO2 and NO2 decreases according to the distance. The increase in concentration occurred in areas that experienced elevation increases, in Teluk Pandan District with a distance of about 10 kilometers northwest with an elevation of about 100 meters above sea level, and part of the West Bontang District with a distance of about 5 kilometers to the southwest with an elevation of about 90 meters above sea level. The maximum concentration of SO2 at the receptor was 6.2631 μg/m3 on hourly modeling, 0.58132 μg/m3 on modeling per 24 hours, and 0.0317 μg/m3 on annual modeling. The maximum NO2 concentration at the receptor was 1.96781 μg/m3 on hourly modeling, 0.18089 μg/m3 on hourly modeling, and 0.01002 μg/m3 on annual modeling. The distribution of pollutants based on hourly modeling per 24 hours is spreading in all directions and irregularly while for annual modeling it tends to spread towards the southwest and northeast according to the wind rose.Keywords: AERMOD, Emissions, Modeling, Air Dispersion, Auxiliary boiler

Performance analysis of solar-assisted-geothermal combined cooling, heating, and power (CCHP) systems incorporated with a hydrogen generation subsystem

In this study, the response surface method (RSM) and transient assessment was used to evaluate the energy and economic performance of a solar-assisted-geothermal combined cooling, heating, and power system (SG-CCHP). The proposed SG-CCHP process consisted of two steam turbines (STs), photovoltaic/thermal (PV/T) collectors, a fuel cell circuit, an absorption chiller, and a heat pump (HP), with battery cells and a hydrogen storage container as the power storage modules. The system's performance was investigated using the TRNSYS modeling tool. The design of experiments (DOE) approach was used to determine the optimal arrangement of the SG-CCHP scheme by controlling the key design factors. A number of simulation scenarios were generated using DOE, and their outcomes were analyzed using RSM. The transient interactions of the controlling design factors on the techno-economic metrics were given after RSM identified the optimal SG-CCHP scheme. The number of PV/T panels, steam turbine capacity, fuel cell power, HP heating capacity and absorption chiller cooling capacity were considered as decision variables. Total electricity consumption (TEU) and auxiliary boiler fuel consumption (ABFU) as indicators of primary energy consumption of the system and predicted average vote (PMV) as an index of thermal comfort of the system and life cycle cost (LCC) as an economic measure to 4 objective functions were selected for optimization. The results indicated that the optimal system significantly reduced its annual life cycle costs, thermal comfort score, total power usage, and auxiliary boiler natural gas usage. The findings also demonstrated that the SG-CCHP system's integration of battery and hydrogen storage components achieved the maximum efficiencies of 90%, 60%, 23%, and 18% for the electrolyzer, fuel cell, PV/T solar collector, and electrical generator, respectively over a year. The optimization results showed that the system cycle cost (LCC) is $514,188.21 per year, the system comfort coefficient (PMV) is 0.257 per year, the boiler fuel consumption is 46,271.40 cubic meters per year, and the total electricity consumption is −50,082.37 kWh per year.

Hybrid IGDT-stochastic self-scheduling of a distributed energy resources aggregator in a multi-energy system

The optimal management of distributed energy resources (DERs) and renewable-based generation in multi-energy systems (MESs) is crucial as it is expected that these entities will be the backbone of future energy systems. To optimally manage these numerous and diverse entities, an aggregator is required. This paper proposes the self-scheduling of a DER aggregator through a hybrid Info-gap Decision Theory (IGDT)-stochastic approach in an MES. In this approach, there are several renewable energy resources such as wind and photovoltaic (PV) units as well as multiple DERs, including combined heat and power (CHP) units, and auxiliary boilers (ABs). The approach also considers an EV parking lot and thermal energy storage systems (TESs). Moreover, two demand response (DR) programs from both price-based and incentive-based categories are employed in the microgrid to provide flexibility for the participants. The uncertainty in the generation is addressed through stochastic programming. At the same time, the uncertainty posed by the energy market prices is managed through the application of the IGDT method. A major goal of this model is to choose the risk measure based on the nature and characteristics of the uncertain parameters in the MES. Additionally, the behavior of the risk-averse and risk-seeking decision-makers is also studied. In the first stage, the sole-stochastic results are presented and then, the hybrid stochastic-IGDT results for both risk-averse and risk-seeker decision-makers are discussed. The proposed problem is simulated on the modified IEEE 15-bus system to demonstrate the effectiveness and usefulness of the technique.

Acute port congestion and emissions exceedances as an impact of COVID-19 outcome: the case of San Pedro Bay ports

In the second half of 2020, the shift in consumer demand and reduction in containership capacity, as a consequence of the COVID-19 pandemic, contributed to the disruption of the global supply chains, especially on the US West Coast. This article provides an environmental view of acute maritime congestion in Los Angeles and Long Beach anchorage areas aiming to calculate air emissions of anchored ships consistently in a specific month of the year and compare the dynamics of the emission levels with previous years. The findings determine the causes of the increased environmental pollution and conclude on the preservation measures improvement. CO2, SOx, NOx, PM10, and PM2.5 emissions are examined in this study, considering the statistical data on port performance, productivity and competitiveness elements, ship specifications and propulsion, and emission factors of principal pollutants. Results of our mathematical calculation showed an exponential increase of air emissions generated from ships' auxiliary engines and boilers in 2021, compared with the previous periods, reaching more than 45,000 tons of pollutants emitted in November (mainly carbon dioxide). The increased port congestion and pressure upon the environment and human health also exposed the vulnerability of the intermodal chain on the landside, manifested in higher utilization of trucking services inland, contributing to the additional growth of total emissions. The environmental degradation caused by the surge in demand for products carried by container ships coincides with increased social impacts and the requirement for investments in mitigation measures for emissions to reduce the harmful effects of shipping activities.

Ship carbon dioxide emission estimation in coastal domestic emission control areas using high spatial-temporal resolution data: A China case

It is necessary to accurately calculate ship carbon emissions for shipping suitability. The state-of-the-art approaches could arguably not be able to estimate ship carbon emissions accurately due to the uncertainties of Ship Technical Specification Database (STSD) and the geographical and temporal breakpoints in Automatic Identification System (AIS) data, hence requiring a new methodology to be developed to address such defects and further improve the accuracy of emission estimation. Firstly, a novel STSD iterative repair model is proposed based on the random forest algorithm by the incorporation of13 ship technical parameters. The repair model is scalable and can substantially improve the quality of STSD. Secondly, a new ship AIS trajectory segmentation algorithm based on ST-DBSCAN is developed, which effectively eliminates the impact of geographical and temporal AIS breakpoints on emission estimation. It can accurately identify the ships' berthing and anchoring trajectories and reasonably segment the trajectories. Finally, based on this proposed framework, the ship carbon dioxide emissions within the scope of domestic emission control areas (DECA) along the coast of China are estimated. The experiment results indicate that the proposed STSD repair model is highly credible due to the significant connections between ship technical parameters. In addition, the emission analysis shows that, within the scope of China's DECA, the berthing period of ships is longer owing to the joint effects of coastal operation features and the strict quarantine measures under the COVID-19 pandemic, which highlights the emissions produced by ship auxiliary engines and boilers. The carbon intensity of most coastal provinces in China is relatively high, reflecting the urgent demand for the transformation and updates of the economic development models. Based on the theoretical models and results, this study recommends a five-stage decarbonization scheme for China's DECA to advance its decarbonization process.

Life Cycle Assessment for a solar cooling plant

This work aims to evaluate the environmental loads of a hypothetical solar cooling plant making a Life Cycle Assessment (LCA) analysis. In this study, an LCA of a solar cooling plant for a cold room installed in a fruit and vegetable company is performed. The plant is equipped with an absorption chiller of 150 kW and an auxiliary boiler of 50 kW. The hot water storage tank is 5000 l as the cold water one. The solar thermal field is 250 m2 using evacuated tube collectors. The functional unit of the study is the entire plant. The entire life cycle is evaluated assuming that the lifetime is equal to 20 years. The Ecoinvent v3.8 database is used to collect data and SimaPro v.9 software is used to perform the analysis. IPCC 2013 and ReCiPe 2016 are chosen as impact assessment methods and their results are evaluated. The results show that the total CO2 equivalent emissions that are given by the Global Warming Potential evaluation using IPCC 2013 method increase when solar fraction decrease. Therefore, reducing gas consumption and, also, improving plant solar fraction is the most important way to reduce the total emission. However, the solar plant emissions are related to the installation, maintenance and use phases.

Optimalisasi Perawatan Sistem Auxiliary Boiler Dalam Menghasilkan Uap Panas

Auxiliary boilers that have the function of producing hot steam are auxiliary steam boilers. The function of this steam is to heat the fresh water jacket cooling and fuel, drive the turbine pump, heat the liquid in the tank and room. This study aims to optimize the maintenance of auxiliary boiler systems, especially in the auxiliary steam boilers. This research was conducted in the engine room on the MT ship. This research is a qualitative descriptive study with data collection obtained from observation, interviews and documentation. The result of this study is the implementation of maintenance of auxiliary boiler components including: Boiler water; main burner; pilot burner; blower; and pumps. Overall, the average before optimizing maintenance, the effectiveness of the implementation of the planning maintenance system in auxiliary boilers was around 58.86%, and the average increased by 27.57% so that the average after optimization of maintenance with the guidelines for planning system maintenance became 86.43%. Auxiliary boiler system maintenance steam boiler In MT Tender Harmony can run optimally so that it can produce quality steam so that it can heat the fuel optimally.

Using Rooftop Solar Heating to Supply Part of a High-Rise Residential Building Heat in the Cold Climate of Iran: One-Year Dynamic Analysis

Higher energy consumption, especially for heating, in high-rise buildings than conventional buildings, necessitates partially supplying thermal energy by solar water heaters (SWHs). Considering the very high solar radiation potential in Iran, this study used roof solar collectors to partially supply the heat required for domestic hot water (DHW) and heat the indoor space and a swimming pool in a 48-unit building in a cold climate (Shahrekord, Iran). Climatic data were extracted from Meteonorm 7.3, and technical, energy, environmental, and economic analyses were performed with the help of TSOL 2018 R(1). The one-year dynamic analysis was performed, considering all possible losses, and an auxiliary gas boiler (AGB) was also used. According to the results, considering the available roof area, 8.7% of the total required heat equivalent to 82814 kWh is supplied by SWHs with a unit cost of $0.022/kWh. The AGB supplied 867259 kWh/year, preventing CO2 emissions by 25.5 tons. This is the first study in this regard in Iran, and the authors hope that the results can be employed as a guideline for decision makers to extend the use of SWHs in Iran.

Design, modeling, and thermo-economic optimization of an innovative continuous solar-powered hybrid desalination plant integrated with latent heat thermal energy storage

Ever-increasing needs for freshwater over the globe have made scientists investigate and find out viable solutions to overcome this concern. In line with this fact, multi-objective optimization of a solar-assisted hybrid desalination plant, which encompasses multi-effect distillation with thermal vapor compression and humidification-dehumidification units, was carried out during this study. Parabolic trough solar collectors play the role of a supplier of required input energy to run this system. In addition, there is a heating and storage unit, which includes a latent heat thermal storage tank to store the excess heat gained by solar collectors and an auxiliary boiler to assist in supplying the required heat for desalination units. Design parameters such as Parabolic trough solar collectors rows, phase change materials, number of multi-effect distillation system effects, motive steam flow rate, and last effect brine temperature of multi-effect distillation system which have the greatest impact on the performance of the system are selected. The non-dominated sorting genetic algorithm was employed to conduct multi-objective optimization. According to the optimization results, the total cost rate of the system and the sustainability index is 0.548 $/s and 1.54 respectively. In addition, adding the humidification-dehumidification unit to the system contribute to producing 0.5% more fresh water and brings 0.1% extra cost.

A robust optimization framework for scheduling of active distribution networks considering DER units and demand response program

The widespread penetration of new resources of electricity and thermal generation and storage in active distribution networks (ADNs) has affected many issues of the distribution network, such as generation scheduling. In consideration of that, in this paper, a problem of simultaneous scheduling of CHP units, electrical and thermal storage, auxiliary boilers, distributed generation system, and responsive loads is studied considering the uncertainties of the network. In this situation, the operator of the ADN performs day-ahead optimal scheduling of the electrical and heat generation units, taking into account the possibility of participation of responsive loads and exchanging electricity with the upstream market to minimize operating costs. Moreover, the uncertainty of energy market prices is also modeled using information-gap decision theory (IGDT) and robustness and opportuneness functions. To solve the problem, a mixed-integer linear programming is proposed. Furthermore, the proposed model is implemented on the IEEE standard 18-bus system, and its efficiency is evaluated by using various scenarios and sensitivity analyses of the optimization problem. • Scheduling of CHP units, storages, boilers, DGs, and responsive loads is studied. • The uncertainty of electricity market energy prices is modeled. • The proposed problem is modeled using a robust planning scheme. • To solve the problem, a mixed-integer linear programming is proposed.

Analysis of EU-DEMO WCLL Power Conversion System in Two Relevant Balance of Plant Configurations: Direct Coupling with Auxiliary Boiler and Indirect Coupling

Among the Key Design Integration Issues (KDIIs) recently selected for the DEMOnstration Fusion Power Plant (DEMO), the operation of the Balance of Plant (BoP) Power Conversion System (PCS) has been recognized as a crucial aspect, due to the typical pulsed regime characterizing the fusion power plant. In the framework of the DEMO Water-Cooled Lead-Lithium Breeding Blanket (WCLL BB) concept, three BoP solutions have been recognized to be able to overcome this issue. They rely on different coupling options between the Primary Heat Transfer Systems (PHTSs) and the PCS: an Indirect Coupling Design (ICD) with Intermediate Heat Transport System (IHTS) and Energy Storage System (ESS), a Direct Coupling Design (DCD) with AUXiliary Boiler (AUXB), and a DCD with small ESS. The present paper deals with a preliminary feasibility assessment of the first two solutions. The analysis, carried out with the GateCycleTM code, referred to a preliminary design phase, devoted to the sizing of the main components, and to a second phase focused on the cycle optimization. The study demonstrated the feasibility of the two BoP concepts. They are able to produce a satisfactory average electric power (>700 MW) with an acceptable average net electric efficiency (33.6% for both concepts). For each solution, the main strengths and weaknesses are compared and discussed.

Semi‐empirical development of a novel and versatile multiobjective optimization tool for co/trigeneration energy system design

This article describes a novel and implemented optimization routine for the analysis of combined cooling, heat, and power generation. The optimization model is briefly described both in terms of logic and operation and in terms of mathematical formalization. The model is able to optimize energy systems with different technologies used for the cogeneration unit, namely, SOFC and PEM fuel cells, internal combustion engines (ICEs), and micro-gas turbines (MGTs). The validation is performed both in terms of energy efficiency curves and in terms of unit costs, for all components within the energy system, including energy storage systems, heat pumps, and auxiliary boilers. The main key performance indicators included in the technical analysis of the CCHP units are the nominal electric and overall efficiency as a function of installed size and during a partial load operation, as well as the power-to-heat factor in dependence upon the nominal capacity/power. Two main storage technologies have been included, namely lithium-ion batteries (Li-ion BES) and lead-acid batteries (LA BES). The heat pump portfolio allows the choice between compression gas heat pumps (CGHPs) and absorption heat pumps (ABHPs), with their COP and EER described as a function of the external temperature and of a partial load operation. The validation of the modeled curves is performed in comparison with data of existing commercial units, presenting a correlation factor over 95% for most of the technologies. Highlights Presentation of a multiphysical design tool for CCHP systems; Economic, technical, and environmental analysis and optimization; PEMFC and SOFC are included in the tool technology portfolio; The model is based on validated and semi-empirical correlations; Evaluation of different energy storage systems and heat pump technologies. The present article describes the validation of an innovative multiobjective model aiming to optimize both the operating strategy of the plant and the sizing of the main equipment in a correlated way. The article focuses on the validation of the proposed model and, as a further novelty, includes a broad technological portfolio in terms of cogeneration units and describes the semi-empirical validation of the model by comparing the cost and performance curves modeled with existing market elements or literature data.

Exergy Criteria of Performance of Waste Heat Recovery Applied for Marine Auxiliary Boiler

Auxiliary boilers onboard motor ships are the subject of ongoing research. Steam is produced by an auxiliary boiler for fuel heating and cargo oil pumping turbines. This marine boiler is a pressure jet burner water tube auxiliary boiler with a 70-80% efficiency rating. The goal of determining the process and components of irreversibility loss in a system is to identify the process and components of exergy losses. The second law of thermodynamics and the concept of irreversible entropy production are the foundations of this study's exergy technique of analysis. This concept of considering entropy at a given steady-state condition rather than as a change in a process is also one of the features of this exergy analysis of the marine oil-fired boiler. The exergy loss in the combustion chamber was calculated and determined to be 35024 kJ, which is the maximum irreversibility in this maritime auxiliary boiler. A numerical analysis of the current nozzle jet burner is undertaken to evaluate the enhancement of the combustion process. The temperature and velocity contour of the fuel stream passing through the nozzle of this auxiliary boiler's burner depicts atomization.

Fresnel solar cooling plant for buildings: Optimal operation of an absorption chiller through inverse modelling

Increasing comfort conditions in buildings imply higher energy demands. However, these needs can be mitigated by solar cooling solutions. These systems, such as absorption chillers, are complex and require stable operation, with strict control to maximise the solar fraction and minimise gas consumption. This is incompatible with the variability of renewable resources, so they are often coupled with auxiliary gas systems. Although gas-free operation is possible if these systems are optimally controlled, they would require special supervision. This paper aims to develop an experimental validation of an inverse model to manage an absorption chiller coupled with a solar cooling plant. To know its real behaviour, long-term experiments have been performed using this plant, which consists of a linear Fresnel solar collector and an auxiliary natural gas boiler. The inverse model is used as a predictive control tool to decide the auxiliary boiler commands of the absorption chiller to optimise its operation: maximum cooling production by minimising gas consumption and maximising solar contribution. It has been identified with data from two weeks and validated with data from one summer month. Results show that the model estimates, on a time base of fewer than 30 min, are acceptable with errors of less than 5%. In addition, the maximum error of the estimated seasonal COP and the renewable fraction are less than 6% per day. Therefore, the results prove the usefulness of the proposal as a predictive control for optimal operation. Furthermore, it could be used as a baseline for preventive maintenance. If the proposed model is used for optimal management of the absorption chiller, the thermal efficiency of the plant increases significantly, doubling the solar contribution. As a result, the gas consumption of the solar cooling plant is halved and the total cost of air conditioning the building decreases by 16%.

Operation optimization of auxiliary electric boiler system in HTR-PM nuclear power plant

Electric boilers (EBs) are the backup steam source for the auxiliary steam system of high-temperature gas-cooled reactor nuclear power plants. When the plant is in normal operations, the EB is always in hot standby status. However, the current hot standby operation strategy has problems of slow response, high power consumption, and long operation time. To solve these problems, this study focuses on the optimization of hot standby operations for the EB system. First, mathematical models of an electrode immersion EB and its accompanying deaerator were established. Then, a control simulation platform of the EB system was developed in MATLAB/Simulink implementing the established mathematical models and corresponding control systems. Finally, two optimization strategies for the EB hot standby operation were proposed, followed by dynamic simulations of the EB system transient from hot standby to normal operations. The results indicate that the proposed optimization strategies can significantly speed up the transient response of the EB system from hot standby to normal operations and reduce the power consumption in hot standby operations, improving the dynamic performance and economy of the system.

Development and experimental testing of an integrated prototype based on Stirling, ORC and a latent thermal energy storage system for waste heat recovery in naval application

This paper focuses on an advanced energy system, able to increase the overall efficiency of ships by recovering the heat wasted by the propulsion system. A small-scale prototype has been realized, developed, and tested under realistic operating conditions of boat during a winter and summer cruise. The main novelty of the research that has been presented in this paper lies in a significant contribution by developing an integrated dynamic device for electrical production and thermal energy storage. It is based on a 1000 cm3 light duty compression ignition engine coupled with a properly adapted Stirling Engine (SE), an Organic Rankine Cycle group (ORC) and a latent Thermal Energy Storage system (TES). All the components have been managed by means of a specifically developed electronic control, simulating two standard cruise profiles. Scaled engine power data have been imposed to simulate port, manoeuvring and open sea navigation phases. The consumption of hot water has been obtained by considering the typical hourly use profile of a cruise ship.It has been demonstrated that the proposed integrated system allows recovering all the thermal energy needed to satisfy the hot water request during the cruise, avoiding the use of auxiliary boilers. The results indicate a favourable effect because the recovered thermal energy represents the 7.7 % of the total energy consumed by fuel. The net electrical energy generated by ORC and Stirling engine resulted to be about 1 % of the total fuel energy consumption, respectively 0.8 % and 0.2 %. The developed prototype can be a useful tool in viability analysis and can easily be reproduced for several uses. In conclusion, the integration of different systems with an optimal integration and sizing of the thermal energy storage considerably improve the thermodynamic, economic and environmental results for future clean ships.

Technical and economic evaluation of the combined production cooling, heating, power, freshwater, and hydrogen (CCHPWH) system in the cold climate

BackgroundMulti-generation plant is a decentralized, energy-efficient method of different type of energy production. Such a system can deliver multiple benefits and advantages compared to conventional energy production such as improvement in the efficiency, emission, cost and reliability. MethodsTechnical-economic analysis of the combined cooling, heating, power, freshwater and hydrogen generation system (CCHPWH) are presented in this paper. Selecting the nominal power of prime movers, their numbers, the cooling capacity of absorption and electrical chillers, the heating capacity of auxiliary boiler, electric cooling ratio (the ratio of electrical chiller capacity to the cooling load demand), motive steam pressure, number of effects, motive steam flow rate, feed flow rate and 24 partial loads for the prime mover during in the year are considered as 35 design parameters. The optimization of the studied system was used by the genetic algorithm to obtain the minimum total annual cost (TAC) as an objective function. The total annual cost includes economic, energy and environmental parameters. It should be noted that selling/buying electricity to/from the grid is allowable in this study. Significant findingsThe optimum results showed 24.8% reduction in the total annual cost of the CCHPWH system using a gas engine as prime mover as compared with a gas turbine. In addition, the exergy efficiency of the cogeneration system in the optimal state for the prime mover of the gas turbine and the gas engine was obtained 31.21% and 45.58%, respectively. Finally, the optimal results in different cases were compared and results were discussed.

Optimal configuration planning of rule and optimization-based driven storage coupled micro cogeneration systems by the implementation of constraint programming

In this paper, an optimization model for optimal size and dispatch planning of micro combined heat and power systems regarding distinct structures for the inclusion of the cogeneration unit, auxiliary boiler, heat storage and battery storage in the configuration of the system is introduced. The presented model is developed in a unified form by the implementation of constraint programming to consider different strategies for the system's operation. Furthermore, important details such as minimum/maximum permissible state of charge, maximum charge/discharge rate and battery inverter for modeling practical storages as technical specifications and simultaneous consideration of calendar life and life cycle as service life as well as assessment of heat dumping avoidance has been taken into account in this study. The model has been applied to three operation strategies and four kinds of buildings while considering two single-objective and one multi-objective optimization for minimization of the greenhouse gas emissions and annual costs of the system. The study has been validated by multiple study cases and the analyzes indicate that the implementation of different structures for the configuration of the micro CHP systems can impressively affect the optimum size and dispatch of these systems in each operation strategy. Comparison of the obtained results for the candidate multi-criteria solutions considering the exploitation of different storage options indicates that the inclusion of the heat storage by up to 21.5% further reduction in annual expenditures with an equal amount of emissions is a more influential energy storage option for utilization in the proposed residential cogeneration system. Regarding heat dumping assumption, dumping avoidance can be a powerful key factor in the system's management to prevent extra greenhouse generations by restricting the heedless minimization of the annual costs when it adversely affects the generation of the emissions.

Modeling and Optimization of Smart Building Energy Management System Considering Both Electrical and Thermal Load

Energy consumption in buildings is expected to increase by 40% over the next 20 years. Electricity remains the largest source of energy used by buildings, and the demand for it is growing. Building energy improvement strategies is needed to mitigate the impact of growing energy demand. Introducing a smart energy management system in buildings is an ambitious yet increasingly achievable goal that is gaining momentum across geographic regions and corporate markets in the world due to its potential in saving energy costs consumed by the buildings. This paper presents a Smart Building Energy Management system (SBEMS), which is connected to a bidirectional power network. The smart building has both thermal and electrical power loops. Renewable energy from wind and photo-voltaic, battery storage system, auxiliary boiler, a fuel cell-based combined heat and power system, heat sharing from neighboring buildings, and heat storage tank are among the main components of the smart building. A constraint optimization model has been developed for the proposed SBEMS and the state-of-the-art real coded genetic algorithm is used to solve the optimization problem. The main characteristics of the proposed SBEMS are emphasized through eight simulation cases, taking into account the various configurations of the smart building components. In addition, EV charging is also scheduled and the outcomes are compared to the unscheduled mode of charging which shows that scheduling of Electric Vehicle charging further enhances the cost-effectiveness of smart building operation.