Search Results (99)

To address the shortcomings of poor convergence and the ease of falling into local optima when using the traditional gold rush optimization (GRO) algorithm to solve the complex scheduling problem of a combined cooling, heating, and power (CCHP) microgrid system, an optimal scheduling model for a microgrid based on the improved gold rush optimization (IGRO) algorithm is proposed. First, the Halton sequence is introduced to initialize the population, ensuring a uniform and diverse distribution of prospectors, which enhances the algorithm’s global exploration capability. Then, a dynamically adaptive weighting factor is applied during the gold mining phase, enabling the algorithm to adjust its strategy across different search stages by balancing global exploration and local exploitation, thereby improving the convergence efficiency of the algorithm. In addition, a weighted global optimal solution update strategy is employed during the cooperation phase, enhancing the algorithm’s global search capability while reducing the risk of falling into local optima by adjusting the balance of influence between the global best solution and local agents. Finally, a t-distribution mutation strategy is introduced to improve the algorithm’s local search capability and convergence speed. The IGRO algorithm is then applied to solve the microgrid scheduling problem, with the objective function incorporating power purchase and sale cost, fuel cost, maintenance cost, and environmental cost. The example results show that, compared with the GRO algorithm, the IGRO algorithm reduces the average total operating cost of the microgrid by 3.29%, and it achieves varying degrees of cost reduction compared to four other algorithms, thereby enhancing the system’s economic benefits. Full article

In this paper, a new type of cogeneration system using LNG cold energy as a cooling source and geothermal energy as a heat source is designed and studied from the perspective of LNG cold energy gradient utilization. The system integrates power generation, cold storage, and district cooling. In order to provide more detailed information, the proposed system was analyzed in terms of energy, exergy, and economy. The effects of separator pressure, LNG pump outlet pressure, the mass flow rate of n-Pentane in ORC-I, liquefaction temperature of R23 in the cold storage module, and pump 5 outlet pressure in the refrigeration module on the performance of the system were also investigated. Additionally, the particle swarm algorithm (PSO) was used to optimize the CCHP system with multiple objectives to determine the system’s optimal operation. The optimization results show that the system’s thermal efficiency, exergy efficiency, and depreciation payback period are 66.06%, 42.52%, and 4.509 years, respectively. Full article

In the context of rapid urbanization in China, many farmers still live in areas far away from urban energy supply networks. To meet the multi-level energy demands of rural communities, this study proposes a combined heat, power, and electricity (CCHP) supply system that uses solar and biomass energy as inputs, tailored to the natural resources and climatic conditions of the northwestern region. A theoretical model of this system was established in Nanan Community, Wuwei City, and its dynamic performance throughout the year was simulated and analyzed using TRNSYS software. The system was also evaluated for its economic viability, energy efficiency, and environmental impact. The results show that compared with the original and traditional energy supply systems, the CCHP system achieves average primary energy saving rates of −9.87% and 41.52% during the heating season, annual cost savings of 50.35% and 64.19%, carbon dioxide emission reduction rates of 32.89% and 66.86%, and a dynamic investment payback period of 3.14 years. This study provides development ideas for constructing modern integrated energy systems in rural areas that are remote from urban energy supply networks and offers references for investors. Full article

As the world’s population grows and energy demand increases, there is a need to switch from fossil fuels to renewable energy. In order to preserve the environment and meet these growing demands, especially for cooling applications, trigeneration systems could be the answer. The aim of this work is to provide a structured overview of the current state of the art in the field of trigeneration (CCHP) systems. Firstly, these systems and their applications are presented. An overview of the different indicators used to describe the performance of these systems is given. A comparison between CCHP (combined cooling, heat, and power) systems is made. Finally, improvements and other concepts found in the literature are presented. This review will later serve as a basis for the exergo-economic optimization of a low-temperature CCHP system based on renewable energy sources. Therefore, more attention is given to the technologies used for such systems. Full article

Within the 21st century, in the Maritime Silk Road, wave energy, a clean renewable source, is drawing more interest, especially in areas with power shortages. This paper investigates wave energy in ships, particularly in a hybrid electric bulk carrier, by designing a system that supplements the existing power setup with oscillating buoy wave energy converters. The system includes diesel generators (DGs), a wave energy generation system, heterogeneous energy storage (consisting of battery storage (BS) and thermal storage (TS)), a combined cooling heat and power (CCHP) unit, and a power-to-thermal conversion (PtC) unit. To ensure safe and reliable navigation despite uncertainties in wave energy output, onboard power loads, and outdoor temperature, a robust coordination method is adopted. This method employs a two-stage robust optimization (RO) strategy to coordinate the various onboard units across different time scales, minimizing operational costs while satisfying all operational constraints, even in the worst-case scenarios. By applying constraint linearization, the robust coordination model is formulated as a mixed-integer linear programming (MILP) problem and solved using an efficient solver. Finally, the effectiveness of the proposed method is validated through case studies and comparisons with existing ship operation benchmarks, demonstrating significant reductions in operational costs and robust performance under various uncertain conditions. Notably, the simulation results for the Singapore–Trincomalee route show an 18.4% reduction in carbon emissions compared to conventional systems. Full article

The combined cooling, heating, and power system is based on the principle of energy cascade utilization, which is conducive to reducing fossil energy consumption and improving the comprehensive utilization efficiency of energy. With the characteristics of a lower expansion ratio and larger recuperation of a supercritical carbon dioxide (SCO₂) power cycle, a combined cooling, heating, and power (CCHP) system is proposed. The system is based on a SCO₂ cycle and is driven by solar energy. The system is located in Qingdao and simulated by MATLAB/Simulink software (R2022b). Firstly, the thermodynamic performance of the CCHP system at the design condition is analyzed. The energy utilization efficiency of the CCHP system is 79.75%, and the exergy efficiency is 58.63%. Then, the thermodynamic, environmental, and economic performance analyses of the system under variable conditions are carried out. Finally, the solar multiple is optimized. The results show that the minimum levelized cost of electricity is 10.4 ¢/(kW·h), while the solar multiple is 4.8. The annual primary energy saving rate of the CCHP system is 85.04%, and the pollutant emission reduction rate is 86.05%, compared with the reference system. Therefore, an effective way to reduce environmental pollution and improve the utilization efficiency of solar energy is provided. Full article

Recently, electric distribution grids supply not only electric loads but also heating and cooling loads simultaneously to increase the efficiency of the system and reduce the emission of greenhouse gases. An energy management system (EMS) to reduce the combined total expense including environmental damage cost of the combined cooling, heating, and power (CCHP) smart distribution grids in a cooperative framework is proposed in this paper. The entire problem is modelled as a unit commitment interval mixed integer quadratic program (UCIMIQP). The UC is developed to respond to the operation of the electric, heating, and cooling systems and takes into consideration the exchange of energy between these systems. In addition, the demand response (DR) is incorporated with the optimization problem as a decision variable to shave the peak load and reduce the total system cost. The environmental damage is converted to expense, and the entire combined problem is converted to a unified function that is possible to solve in one step, where this is suitable for online operation. Furthermore, a set of realistic constraints is considered to make the approach close to a real scenario. To verify the effectiveness and robustness of the proposed model, the analysis is applied to the distribution grids, which include electrical, heating, and cooling systems, where these systems operated cooperatively. The interaction between these systems makes the operation more flexible and economical. The results show that the total cost is reduced through an exchange in energy between the systems. Additionally, the consideration of the demand response reduces the maximum load and decreases the total cost. Full article

The increasing demand for energy, driven by technological advances, population growth, and economic expansion, has intensified the focus on efficient energy management. Tri-generation systems, such as Combined Cooling, Heating, and Power (CCHP) systems, are of particular interest due to their efficiency and sustainability. Integrating renewable energy sources like solar power with traditional fossil fuels further optimizes CCHP systems. This study presents a novel method for enhancing the CCHP system efficiency by identifying the optimal design parameters and assisting decision makers in selecting the best geometric configurations. A mathematical programming model using the Harris Hawks optimizer was developed to maximize the net power and exergy efficiency while minimizing CO₂ emissions in a solar-assisted CCHP system. The optimization resulted in 100 Pareto optimal solutions, offering various choices for performance improvement. This method achieved a higher net power output, satisfactory exergy efficiency, and lower CO₂ emissions compared to similar studies. The study shows that the maximum net power and exergy efficiency, with reduced CO₂ emissions, can be achieved with a system having a low compression ratio and low combustion chamber inlet temperature. The proposed approach surpassed the response surface method, achieving at least a 4.2% reduction in CO₂ emissions and improved exergy values. Full article

The power-to-X strategy for passenger car applications offers a viable solution for using the surplus electrical power from renewable energy sources instead of exporting it to the grid. The innovative system proposed in this study allocates surplus electrical power from a building-integrated biomass-based Combined Cooling Heating and Power (CCHP) system to on-site applications and evaluates the energetic and economic benefits. The system comprises two key components: a 50 kW electric vehicle (EV) charging station for EVs and a 50 kW alkaline electrolyzer system for on-site hydrogen production, which is later dispensed to fuel cell electric vehicles (FCEVs). The primary goal is to decrease the surplus of electricity exports while simultaneously encouraging sustainable transportation. The system’s economic viability is assessed through two scenarios of fuel (e.g., biomass) supply costs (e.g., with and without fuel market costs) and compared to the conventional approach of exporting the excess power. The key findings of this work include a substantial reduction in surplus electricity exports, with only 3.7% allocated for EV charging and 31.5% for hydrogen production. The simple payback period (SPB) is notably reduced, enhancing economic viability. Sensitivity analysis identifies the optimal hydrogen system, featuring a 120 kW electrolyzer and a 37 kg daily hydrogen demand. The results underscore the importance of prioritizing self-consumed energy over exports to the national grid, thereby supporting integrated renewable energy solutions that enhance local energy utilization and promote sustainable transportation initiatives. Full article

With the gradual depletion of fossil energy sources and the diversification of users’ energy demand, combined cooling, heating and power (CCHP) microgrids have become a hot technology to improve energy efficiency and promote efficient and synergistic energy operation. However, the uncertainty and correlation of wind power and photovoltaic (PV) outputs have posed a great challenge to the reliability of CCHP system operation, so CCHP systems are often equipped with energy storage devices to improve system flexibility to ensure the reliability of energy supply. However, system-owned reserves still have shortcomings such as high investment O&M costs and large space requirements. As an emerging model, “shared energy storage” can reduce the investment pressure of users and open up new ways for the economic and stable operation of CCHP systems. Therefore, based on the scenario of wind and solar power correlation and considering different types of load flexibility, this paper proposes to construct a shared energy storage station (SESS)-CCHP double-layer synergistic optimal allocation model. The model incorporates the consideration of the actual operation strategy of the CCHP system in the planning stage of energy storage. An example analysis shows that SESS reduces the total operating cost of the CCHP system by 25.96% and improves the new energy consumption rate by 10.46% compared with no energy storage. Compared with the system independently configured with energy storage, the cost saving is 2.14%, thus validating the effectiveness of the proposed model. Full article

The Combined Cooling, Heat, and Power (CCHP) System is an efficient technology that reduces primary energy consumption and carbon dioxide emissions by generating heat, cold, and electricity simultaneously from the same fuel source. This study developed an economic optimization model using linear mathematical program theory to determine the optimal sizes of different components in a CCHP system. The study found that CCHP systems with internal combustion engines have the largest optimal size due to lower capital expenditure and improved hourly changes in combined energy production by considering electrical and absorption chillers simultaneously. The analysis compared the size determination of CCHP systems with internal combustion engine (ICE), sterling engine (SE), and proton exchange membrane fuel cell (PEMFC) technologies. PEMFC had the highest annual overall cost among the technologies studied. The results of determining the size of the CCHP system are compared with ICE, SE, and PEMFC technologies. It has been noted that PEMFC has the highest annual overall cost among the studied technologies. The usefulness index of the CCHP system increased from 23% to almost 40% when electricity was sold to the grid using internal combustion engine technology. Full article

The traditional centralized optimization method encounters challenges in representing the interaction among multi-agents and cannot consider the interests of each agent. In traditional low-carbon scheduling, the fixed carbon quota trading price can easily cause arbitrage behavior of the trading subject, and the carbon reduction effect is poor. This paper proposes a two-layer dynamic community integrated energy system (CIES) low-carbon collaborative optimization operation method. Firstly, a multi-agent stage feedback carbon trading model is proposed, which calculates carbon trading costs in stages and introduces feedback factors to reduce carbon emissions indirectly. Secondly, a two-layer CIES low-carbon optimal scheduling model is constructed. The upper energy seller (ES) sets energy prices. The lower layer is the combined cooling, heating, and power (CCHP) system and load aggregator (LA), which is responsible for energy output and consumption. The energy supply and consumption are determined according to the ES energy price strategy, which reversely affects the energy quotation. Then, the non-dominated sorting genetic algorithm embedded with quadratic programming is utilized to solve the established scheduling model, which reduces the difficulty and improves the solving efficiency. Finally, the simulation results under the actual CIES example show that compared with the traditional centralized scheduling method, the total carbon emission of the proposed method is reduced by 16.34%, which can improve the income of each subject and make the energy supply lower carbon economy. Full article

The combined cooling, heating, and power (CCHP) system has attracted increasing attention due to its potential outstanding performance in thermodynamics, economics, and the environment. However, the conventional CCHP systems are carbon-intensive. To solve this issue, a low-carbon-emission CCHP system (LC-CCHP) is firstly proposed in this work by integrating a sorption-enhanced steam methane reforming (SE-SMR) process. In the LC-CCHP system, CO₂ is continuously captured by the calcium loop so that low-carbon energy can be generated. Then, the LC-CCHP system thermodynamic model, mainly consisting of a dual fluidized bed reactor which includes the SE-SMR reactor and a CaCO₃ calcination reactor, a hydrogen gas turbine, a CO₂ reheater, and a lithium bromide absorption chiller, is built. To prove that the LC-CCHP model is reliable, the system major sub-unit model predictions are compared against data from the literature in terms of thermodynamics and economics. Finally, the effects of reforming temperature (T_ref), the steam-to-carbon mole ratio (S/C), the calcium-to-carbon mole ratio (R_CC), the equivalent ratio for gas turbine (R_AE), and the hydrogen separation ratio (S_fg) on total energy efficiency (${\eta }_{ten}$), total exergy efficiency (${\eta }_{tex}$), and carbon capture capability ($R_{cm}$) are detected. It is found that the minimum exergy efficiency of 64.5% exists at the calciner unit, while the maximum exergy efficiency of 78.7% appears at the gas turbine unit. The maximum energy efficiency and coefficient of performance of the absorption chiller are 0.52 and 1.33, respectively. When $T_{ref}=600$ °C, $S/C=4.0$, $R_{CC}=7.62$, $R_{AE}=1.20,$ and $S_{fg}=0.27$, the ${\eta }_{ten}$, ${\eta }_{tex,}$ and $R_{cm}$ of the system can be ~61%, ~68%, and ~96%, and the average specific cost of the system is 0.024 USD/kWh, which is advanced compared with the parallel CCHP systems. Full article

A solar-powered combined cooling, heating, and power (CCHP) plant integrated with a water electrolysis unit is investigated in terms of energy, exergy, and exergo-economic (3E) assessments. A comprehensive parametric study and optimization is conducted following the thermodynamic and exergo-economic assessment of the proposed system to evaluate the key performance parameters of the system for efficiency and economic factors. This system employs a heliostat field and a receiver tower by taking advantage of thermal energy from the sun and produces a continuous energy supply with an integrated phase-change material (PCM) tank to store the heat. In addition, a supercritical CO₂ Rankine cycle (RC), an ejector refrigeration cooling (ERC) system, and a PEM water electrolyzer are coupled to produce cooling, heating, power, and hydrogen. Thermodynamic analysis indicates that the system exergy efficiency and energy efficiency are improved to $33.50\mathrm{\%}$ and $40.61\mathrm{\%}$, respectively, while the total cost rate is $2875.74 \mathrm{U}\mathrm{S}\mathrm{D}/\mathrm{h}$ and the total product cost per exergy unit is $25.65 \mathrm{U}\mathrm{S}\mathrm{D}/\mathrm{G}\mathrm{J}$. Additionally, the system produces a net generated power, heating load, and cooling load of $11.70$, $13.92,$ and $2.60$ $\mathrm{M}\mathrm{W}$, respectively, and a hydrogen production rate of 12.95 $\mathrm{g}/\mathrm{s}$. A two-objective optimization approach utilizing a non-dominated sorting genetic algorithm (NSGA) was performed, demonstrating that the system’s ideal design point offers a cost rate of $1263.35 \mathrm{U}\mathrm{S}\mathrm{D}/\mathrm{h}$ and an exergetic efficiency of $34.17\mathrm{\%}$. Full article

With the development of Chinese society, there is an increasing demand for emissions reduction and the stable operation of the power grid. Regional comprehensive energy supply systems have entered the public’s view owing to their advantages of reducing capacity, unified dispatch, improving efficiency, and reducing energy consumption. This paper focuses on a system under construction in Chongqing, which adopts a combined gas tri-supply (combined cooling, heat, and power, CCHP) and dynamic ice storage cooling system as the research object. By establishing a mathematical model for the simulation research, this study examines the start–stop priority sequence of the gas tri-supply subsystem and the heat pump subsystem under the ice storage priority strategy in winter and summer and proposes corresponding optimization solutions. By comparing the annual operating energy consumption of the system, we conclude that the gas tri-supply composite system has good economic efficiency and peak-shaving capability, indicating that regional gas tri-supply composite systems have great application potential in the future. The proposed optimized operation strategy and simulated energy consumption calculation provide theoretical guidance for the construction and operation of both this project and similar projects. Full article