Sustainability Assessment of Combined Cooling, Heating, and Power Systems under Carbon Emission Regulations

Abstract

The combined cooling, heating, and power (CCHP) system, which is a sustainable distributed energy system, has attracted increasing attention due to the associated economic, environmental, and energy benefits. Currently, the enforcement of carbon emission regulations has become an increasingly concerning issue globally. In this paper, a multi-objective optimization model is established to evaluate the CCHP system under two different carbon emission regulation policies in terms of economic benefit, environmental sustainability, and energy advantage. A nonlinear programming optimization model is formulated and solved by using the particle swarm optimization (PSO) algorithm. The results from the case studies demonstrate that when considering carbon tax regulation, the cost savings of the optimal CCHP system strategy were on average 10.0%, 9.1%, 17.0%, 22.1%, and 20.9% for the office, supermarket, hotel, school, and hospital in China, respectively, compared with the conventional energy supply system. On the other hand, when considering carbon trading regulation, the optimal CCHP system strategy can lead to a 10.0%, 8.9%, 16.8%, 21.6%, and 20.5% cost-saving for the five different building categories, respectively. Furthermore, the optimal CCHP system strategy for the five buildings, i.e., an average of 39.6% carbon dioxide emission (CDE) reduction and 26.5% primary energy consumption (PEC) saving, can be achieved under carbon emission regulations.

Optimal Economic Modelling of Hybrid Combined Cooling, Heating, and Energy Storage System Based on Gravitational Search Algorithm‐Random Forest Regression

“…e wind turbines and photovoltaic cells belong to renewable energy units, which use natural energy to generate electricity, and natural gas consumption units including gas boilers, fuel cells, and microgas turbines are depicted in Figure 1. ey use natural gas combustion power to provide energy, and microgas turbines and bromine-cooled units have covert the CCHP system and can recycle high-temperature flue gas during power generation [31,32]. When the supply of cold (heat) power is insufficient, it can be used to make up the shortage while the gas boiler is used as auxiliary supply equipment for cold (heat) load [31,32].…”

“…ey use natural gas combustion power to provide energy, and microgas turbines and bromine-cooled units have covert the CCHP system and can recycle high-temperature flue gas during power generation [31,32]. When the supply of cold (heat) power is insufficient, it can be used to make up the shortage while the gas boiler is used as auxiliary supply equipment for cold (heat) load [31,32]. e energy storage unit consists of three parts, battery, cold storage, and hot water storage tank.…”

Optimal design and 4E assessment of typical combined cooling, heating and power systems considering the effects of energy price fluctuation

“…Of which, the exergy of primary energy is approximately equal to the product of its mass and low heat value (LHV), 37 and the exergy of electricity equals to its amount. These items can be calculated by Equations (27) to (31). 38,39 Ex pe = 3600 × m pe × LHV pe , ð27Þ…”

“…As mentioned above, mathematical programming is a common means to get the optimal design scheme of CCHP systems. However, the optimization models generally involve numerous decision variables and nonlinear items that aggravate the difficulty of solving, so some efficient algorithms, such as SQP, 26 PSO, 27 and NSGA‐II, 28 have been widely applied to optimize CCHP systems.…”

Low‐carbon economic operation for integrated energy system considering carbon trading mechanism

“…27 The existing literature on the diversification of the internal equipment and miniaturized IES under the carbon trading mechanism is relatively little. Although some scholars have done some researches in this aspect, for example, Chu et al 28 established a nonlinear optimization model with three objectives of the economic benefit, environmental sustainability, and energy efficiency in the consideration of the carbon trading policy, which was solved by the particle swarm optimization. In the case study, with this optimal system operation strategy, the reducing cost percentage of five different types of public buildings increased with the carbon trading prices growth under different carbon emission quotas.…”