Exergy and thermoeconomic analysis of a combined Allam generation system and absorption cooling system
20 Oct 2021-international journal of energy and environmental engineering (Springer Berlin Heidelberg)-pp 1-7
TL;DR: In this paper, the authors investigated the combined system including Allam cycle and absorption cycle from the perspective of energy, exergy and exergy-economy, and the simulation results showed that the total exergy efficiency of the cogeneration cycle is 0.72.
Abstract: In recent years, the use of Allam cycle based on the closed cycle of carbon dioxide has been considered by researchers due to its high efficiency and reduction of carbon dioxide emissions in the environment. In the present study, the combined system including Allam cycle and absorption cycle has been investigated from the perspective of energy, exergy and exergy–economy. The use of the absorption cycle is to use the waste heat of the power cycle and increase energy efficiency. The simulation results show that the total exergy efficiency of the cogeneration cycle is 0.72. Turbine, compressor and absorption cycle are introduced as primary components that should be considered from the exergy–economic point of view because they account for the highest cost rate of exergy efficiency. Also, the results of parametric analysis indicate that increasing the compressor pressure ratio has a negative effect on the cycle performance, thus reducing the overall work and efficiency of the exergy as well as increasing the cost rate. Similarly, changing the compressor pressure ratio has the greatest impact on the performance of the combined cycle, so that changing the pressure ratio in the range of 2 to 10 resulted in reducing the exergy efficiency by 63%. The key assessment is that the performance of the system increases as the temperature of the cooled water in the evaporator rises. Exergy efficiency works in contrast to the system performance coefficient and the main reason for the return of imperfections in the absorption cooling system is the undesirable heat transfer in the system heat exchangers.
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TL;DR: In this article, a robust optimization method incorporating piecewise linear thermal and electrical efficiency curve is proposed to accommodate the uncertainties of cooling, thermal, and electrical load, as well as photovoltaic (PV) output power.
Abstract: Energy management is facing new challenges due to the increasing supply and demand uncertainties, which is caused by the integration of variable generation resources, inaccurate load forecasts and non-linear efficiency curves. To meet these challenges, a robust optimization method incorporating piecewise linear thermal and electrical efficiency curve is proposed to accommodate the uncertainties of cooling, thermal and electrical load, as well as photovoltaic (PV) output power. Case study results demonstrate that the robust optimization model performs better than the deterministic optimization model in terms of the expected operation cost. The fluctuation of net electrical load has greater effect on the dispatching results of the combined cooling, heating and power (CCHP) microgrid than the fluctuation of the cooling and thermal load. The day-ahead schedule is greatly affected by the uncertainty budget of the load demand. The economy of the optimal decision could be achieved by adjusting different uncertainty budget levels according to control the conservatism of the model.
65 citations
TL;DR: In this paper, a linear programming optimization model was presented for optimum planning and sizing of combined cooling, heat, and power (CCHP) systems in residential buildings in order to reduce total costs relative to conventional systems.
Abstract: Combined cooling, heat, and power (CCHP) system offers numerous potential advantages for the supply of energy to residential buildings in the sense of improved energy efficiency and reduced environmental burdens. To realize the potential for being more beneficial, however, such systems must reduce total costs relative to conventional systems. In this study, a linear programming optimization model was presented for optimum planning and sizing of CCHP systems. The purpose of the model is to give the design of the CCHP system by considering electrical chiller and absorption chiller simultaneously in economic viewpoint. A numerical study was conducted in Tehran to evaluate the CCHP system model. The linear programming (LP) model determines the optimal sizes of the CCHP equipment by considering capital cost of the system. It showed that by considering electricity buyback, the optimum size of the electrical chiller decrease and the optimum size of the combined heat and power (CHP) unit and the absorption chiller increase dramatically with respect to without electricity buyback. Also, the LP model determines the optimal operation strategy of the system by neglecting capital cost. The optimally operated CCHP system encompassing electrical and absorption chiller could result in an 18% decrease in operating cost when compared to a CHP system encompassing electrical chiller only. Without electricity buyback, the profitability of CCHP was 23%, while with electricity buyback, profitability became 39%. Furthermore, a sensitivity analysis was conducted to show how the important parameters affect the entire system performance.
20 citations
TL;DR: Wang et al. as mentioned in this paper summarized the classification, development history, and use status of shallow ground source heat pumps (GSHPs) and analyzed several typical engineering cases of GSHP technology.
Abstract: Ground source heat pumps (GSHPs) are one of the renewable energy technologies with features of high efficiency, energy saving, economic feasibility and environmental protection. In China, GSHPs have been widely used for building heating and cooling in recent years, and have shown great potential for future energy development. This paper summarizes the classification, development history, and use status of shallow GSHPs. Several typical engineering cases of GSHP technology are also specified and analyzed. Finally, promising development trends and some advanced technologies are illustrated.
13 citations
TL;DR: Compared with traditional optimization dispatching methods, the combined cooling, heating, and power optimization dispatches method adopting virtual energy storage fully excavates the potential of the buildings’ virtual storage and every aspect has been improved in terms of economy, environment and energy.
Abstract: Because buildings have certain heat capacity, when the thermal power changes, the indoor temperature has a relative lag of change, while the feeling to comfortable temperature of the human body lies within a certain range. Based on the energy storage characteristics of buildings, this paper structures the optimal dispatch model of a combined cooling, heating, and power system (CCHP) and the virtual energy storage system (VESS) is integrated into the model of optimizing schedule on microgrid. This will achieve the charge and discharge management of microgrid virtual energy storage system, with the optimization objectives of minimizing the economic, environmental and energy indexes through determining the weight coefficient of each index by analytic hierarchy process (AHP) and through the adjustment of the indoor temperature of the building within the range of human comfort. Finally, taking the summer refrigeration scenario as an example and comparing two microgrids of two types of buildings with or without virtual energy storage, this paper concludes that compared with traditional optimization dispatching methods, the combined cooling, heating, and power optimization dispatching method adopting virtual energy storage fully excavates the potential of the buildings’ virtual storage and every aspect has been improved in terms of economy, environment and energy.
12 citations
TL;DR: A multi-agent system (MAS)-based optimal control method is proposed to minimize the operation cost of CCHP systems combined with TES and results show that the optimal operation cost does not change obviously when the rated capacity of TES exceeds a threshold.
Abstract: Combined cooling, heating and power (CCHP) systems have been considered as a potential energy saving technology for buildings due to their high energy efficiency and low carbon emission. Thermal energy storage (TES) can improve the energy efficiency of CCHP systems, since they reduce the mismatch between the energy supply and demand. However, it also increases the complexity of operation optimization of CCHP systems. In this study, a multi-agent system (MAS)-based optimal control method is proposed to minimize the operation cost of CCHP systems combined with TES. Four types of agents, i.e., coordinator agents, building agents, energy management agents and optimization agents, are implemented in the MAS to cooperate with each other. The operation optimization problem is solved by the genetic algorithm. A simulated system is utilized to validate the performance of the proposed method. Results show that the operation cost reductions of 10.0% on a typical summer day and 7.7% on a typical spring day are achieved compared with a rule-based control method. A sensitivity analysis is further performed and results show that the optimal operation cost does not change obviously when the rated capacity of TES exceeds a threshold.
12 citations