تجزیه و تحلیل حساسیت از مدل بهینه سیستم گرمایشی و سرمایشی و برق ساختمان

The optimization of building cooling heating and power (BCHP) system is helpful to improve its comprehensive performance including energetic, economic and environmental aspects. However, the optimal results are closely dependent on the initial setting parameters. This paper deduces the energy consumption of BCHP system following the electrical load and presents the optimization problem of BCHP system that includes the decision variables, the objective function, the constraint conditions and the solution method. The influences of the initial parameters, which include the technical, economic and environmental parameters, the building loads and the optimization setting parameters, on the optimal decision variables and the performances of BCHP system are analyzed and compared. The contour curves of the performances of BCHP system in comparison to the conventional separation production (SP) system, and the sensitivity of the optimal decision variables to the initial parameters are obtained.

In many counties, buildings account for nearly 40% of energy use, and about 40% of carbon dioxide (CO2) emissions along with other greenhouse gas and air pollutant emissions [1] and [2]. The increasing of energy consumption leads to more problems such as energy security, environmental pollution and climate change. As an energy-efficient and environmental-friendly technology, cogeneration system (combined heating and power (CHP) or combined cooling heating and power (CCHP) system) is broadly identified as a highly efficient way to use both fossil and renewable fuels and to make a significant contribution to the sustainable energy development [3], [4], [5], [6], [7] and [8]. When CCHP system is applied to a building, it is called building cooling heating and power (BCHP) system. BCHP systems have been introduced into various kinds of commercial buildings such as hotels, offices, hospitals and schools [8] and [9]. The performance of cogeneration system is closely dependent on its design and operation strategy. Many researchers have concerned the design [10] and [11], the operation [12] and [13], the modeling [14], the energetic and the environmental aspects [15], [16], [17], [18], [19], [20] and [21] to improve the performances of cogeneration systems. Moreover, aimed to obtain the most benefits achieved by the cogeneration system in comparison to the conventional separation production (SP) system, many optimization models are proposed to optimize the structure, the capacity and/or the operation strategy of cogeneration system [22], [23], [24], [25], [26], [27], [28], [29], [30] and [31]. During the optimization, the initial parameters including technical, economic and environmental parameters are important to obtain the rational optimal results. Different parameters lead to the various optimal results directly. To show the influence on the performances of cogeneration system, some researchers have studied and reported some sensitivity analysis of cogeneration systems. The influence analysis mainly includes the energy demands of building [28], [32], [33] and [34] and the key economic parameters [30], [35], [36], [37], [38], [39] and [40]. The optimal results and the performances of congregation system are closely related to the building energy demands. Li et al. [28] studied the influence of energy demands on the optimal facility scheme and the feasibility of BCHP system for a hotel in terms of different heat-electricity ratio and cooling-electricity ratio. Li et al. [32] analyzed the economic influences of BCHP systems into a hotel and a hospital by the energy demands. Gamou et al. [33] carried out a numerical study on a fuel cell BCHP system installed in an office building and clarified the influence of uncertainties in energy demands on a system’s economics and optimal equipment capacities. Mavrotas et al. [34] employed the uncertain degree of demand satisfaction and used fuzzy set theory to optimize and study the economic performance of BCHP system into a hospital. The sensitivity analysis on the economic parameters mainly includes electricity price [30], [35], [36], [37] and [38] and fuel price [30], [35], [36], [37], [38], [39] and [40]. Fragaki et al. [35] studied a gas engine CHP system with thermal store and analyzed the most economic plant size net present value (NPV) in terms of sensitivity to electricity sale prices and gas price including the climate change levy when applicable. Ren et al. [36] optimized a residential CHP system and presented the sensitivity analysis to show how the optimal solutions would vary due to changes of natural gas price, electricity price, electricity buy-back price and carbon tax, etc. Rentizelas et al. [37] optimized a multi-biomass CCHP system and presented the sensitivity analysis performed for the parameters: interest rate, inflation, investment cost, electricity price, cooling price, biomass cost, oil price and operation and maintenance cost. Streckiene et al. [38] presented the feasibility of a CHP system with thermal store in a spot market and showed which extent the optimal solution would vary by changing investment cost, electricity and natural gas price. Wang et al. [30] analyzed the optimal operation strategy changed with electricity price and gas price and presented the fitting functions. Lozano et al. [39] developed an optimization model for BCHP system into a hospital and carried out the sensitivity analysis by varying the amortization and maintenance factor as well as the natural gas price. Sayyaadi [40] proposed a multi-objective optimization model for a benchmark CHP system and performed the sensitivity analysis on the fuel specific cost and the interest rate. Most literatures about the sensitivity analysis of BCHP system analyzed the influences of load and/or economic parameters, there are few literatures to present the sensitivity analysis of the optimal model and/or the technical parameters. This paper is the extension of Ref. [30] and to pay attention to the sensitivity analysis on the optimal results and the performances of BCHP system in terms of the technical, economic and environmental parameters. Section 2 presents the different points with Ref. [30], analyzes the energy consumption of BCHP system in consideration of the operation strategy, and constructs the optimization model. Section 3 analyzes the influences of criteria weight, building loads, technical parameters, economic parameters and emission factors, etc. Section 4 gives summaries and conclusions.

This paper presented the GA optimization model of the BCHP system. The influences of the technical, economic and environmental parameters to the optimal results were analyzed and compared numerically. The sensitivity analysis is helpful to guide the optimal design of the BCHP system and improve the robustness of the optimal results. This analysis leads to the following conclusions: The integrated and accurate parameters including the technical, economic and environmental parameters, the building loads, and the optimization setting parameters, are the foundation of the BCHP system optimization. The performances of BCHP system are closely related to the optimal results. The PGU capacity influences the performances of BCHP system more largely than the ratio of electric cooling to cool load. The optimal cooling ratio decreases with the increase of the absorption chiller’s COP. When the PGU generation efficiency increases, the decreasing velocity of the cooling ratio will become slow with the increase of the absorption chiller’s COP. The optimal PGU capacity increases with the increasing of the PGU generation efficiency. The influences of cost parameters and CO2 conversion factors on the optimal PGU capacity and the optimal cooling ratio are contrary generally. When the optimal cooling ratio increases, the optimal PGU capacity usually decreases. The optimal PGU capacity will almost remain unchanged when the cost parameters and the CO2 conversion factors decrease/increase to a particular critical value. The BCHP system in this analysis operates following the electric load when the surplus electricity from the BCHP system is not allowed to be sold back to the grid. At this operation strategy, the auxiliary boiler is necessary to compensate the heat shortage when the recovered heat is not enough. However, it is emphasized that feeding a absorption chiller having lower COP with heat supplied by a natural gas boiler is an intrinsically inefficient approach in terms of primary energy consumption. If the generated electricity from BCHP system is allowed to be sold to the grid, the operation strategy of BCHP system following the thermal load is recommended to reduce the energy consumption and CO2 emission.