Life-Cycle Optimization of a Chiller Plant with Quantified Analysis of Uncertainty and Reliability in Commercial Buildings

Conventional and most optimal design methods for chiller plants often address the annual cooling load distribution of buildings and their peak cooling loads based on typical meteorological year (TMY) data, while the peak cooling load only appears a few times during the life-cycle and the sized chiller plant usually operates within its low efficient region. In this paper, a robust optimal design method based on life-cycle total cost was employed to optimize the design of a chiller plant with quantified analysis of uncertainty and reliability. By using the proposed design method, the optimized chiller plant can operate at its highly efficient region under various cooling load conditions, and provide sufficient cooling capacity even alongside some equipment/systems with failures. The minimum life-cycle total cost, which consists of the capital cost, operation, and availability-risk cost, can be achieved through optimizing the total cooling capacity and the numbers/sizes of chillers. A case study was conducted to illustrate the detailed implementation process of the proposed method. The performance of this design method was evaluated by comparing with that of other design methods

Optimal design of a solar water heating system for multiple purposes in low energy buildings

This paper presents a systematic methodology for optimizing the key design parameters of a solar water heating (SWH) system with multiple heating purposes in low energy buildings. The methodology is achieved through two steps. In the first step, a simplified energy model of the SWH system is developed and used to estimate system dynamic characteristics and annual energy performance, which is implemented in a spreadsheet. The behavior of the system with different collector areas and storage volumes can be determined realistically through matching multiple heating loads with the solar heat gains. In the second step, the law of diminishing marginal utility is employed to optimize the sizes of the system in order to maximize the life cycle net energy saving. The law describes that the marginal energy saving of the system decreases with the increase of the system size. Therefore, the optimum values of the system size can be determined in an easy-to-understand way, i.e.: the optimization objective (the maximal net energy saving of a SWH system) is achieved when the marginal operating energy saving equals to the marginal embodied energy. A case study on the application of the proposed method in a low-energy building is presented as well

A multi-timescale cold storage system within energy flexible buildings for power balance management of smart grids

© 2020 Elsevier Ltd Energy storage is widely used in energy flexible buildings, which have great potential for relieving the power imbalance of electrical grids. However, most of the existing energy storage systems are designed for short-term storage, and only a few systems reported for long-term or multi-time scale storage. This paper introduces a new type of multi-timescale cold storage system consisted of a heat pipe-based natural ice storage subsystem and a dual-operation chiller for buildings to enhance their energy flexibility. The proposed system operated in different modes to provide the seasonal cold storage, nighttime chilled water storage, and urgent demand response services, which can be used for relieving the power imbalance in the timescale of the long-term, short-term and real-time respectively. The working principle, system configuration, operation modes, and the implementation of the proposed system for multi-timescale power management, are presented. A case study has been conducted in a building in Beijing to demonstrate the application and effectiveness. Results show that building load factors are greatly improved seasonally (from 19.5% to 49.5%) and daily (from 55.7% to 72.2%), and the power consumption is also considerably decreased (41.2%) during the demand response (DR) event

A multi-timescale cold storage system within energy flexible buildings for power balance management of smart grids

Energy storage is widely used in energy flexible buildings, which have great potential for relieving the power imbalance of electrical grids. However, most of the existing energy storage systems are designed for short-term storage, and only a few systems reported for long-term or multi-time scale storage. This paper introduces a new type of multi-timescale cold storage system consisted of a heat pipe-based natural ice storage subsystem and a dual-operation chiller for buildings to enhance their energy flexibility. The proposed system operated in different modes to provide the seasonal cold storage, nighttime chilled water storage, and urgent demand response services, which can be used for relieving the power imbalance in the timescale of the long-term, short-term and real-time respectively. The working principle, system configuration, operation modes, and the implementation of the proposed system for multi-timescale power management, are presented. A case study has been conducted in a building in Beijing to demonstrate the application and effectiveness. Results show that building load factors are greatly improved seasonally (from 19.5% to 49.5%) and daily (from 55.7% to 72.2%), and the power consumption is also considerably decreased (41.2%) during the demand response (DR) event.Peer reviewe

A simplified method for optimal design of solar water heating systems based on life-cycle energy analysis

Significant energy mismatch exists in solar water heating systems as the time and amount of solar energy supply are usually different from that of hot water demand. Using a hot water storage tank can reduce or eliminate such mismatch in short term while it is difficult to avoid this mismatch in long term. In many optimal design and life-cycle analysis methods, the energy mismatch is ignored which causes the system performance to be overestimated and also misleads the optimal design of the system. This paper presents a simplified method for optimizing the key parameters of solar water heating systems based on life-cycle energy analysis. This optimal method considering the energy mismatch phenomenon can be implemented through two steps. In the first step, a simplified energy model based hourly energy matching different components of the system, is developed for determining the operating performance of system with different solar collector areas and water storage volumes. In the second step, the law of diminishing marginal utility is employed to determine the optimum size of the system. The optimum size is identified when the maximal life-cycle net energy saving is achieved. A case study on the application of the proposed method in a building is presented as well

Optimal design and application of a compound cold storage system combining seasonal ice storage and chilled water storage

\u3cp\u3eSeasonal cold storage using natural cold sources for cooling is a sustainable cooling technique. However, this technique suffers from limitations such as large storage space and poor reliability. Combining seasonal storage with short-term storage might be a promising solution while it is not explored sufficiently. This paper presents a compound cold storage system that combines a heat pipe-based seasonal ice storage system with a chilled water storage system. The seasonal ice storage system automatically charges winter cold energy in the form of ice. In summer, the stored ice is extracted for cooling, and then the melting ice is used as a chilling medium for chilled water storage. Design optimization of the seasonal ice storage system and the compound storage system is addressed, including the sizes of heat pipes, the configuration and volume of the cold storage tank and the chiller capacity. A case study is conducted to demonstrate the design and the application of the proposed system in a real building in Beijing. Results show that the appropriate combination of the two types of cold storage can greatly improve the applicability of the seasonal cold storage and reduce the life-cycle cost of a building cooling system by 40%.\u3c/p\u3

A Novel Optimization Method for Conventional Primary and Secondary School Classrooms in Southern China Considering Energy Demand, Thermal Comfort and Daylighting

The classroom environment is of great significance for the health of primary and secondary school students, but a comfortable indoor environment often requires higher energy consumption. This paper presents a multi-objective optimization method based on an artificial neural network (ANN) model, which can help designers efficiently optimize the design of primary and secondary school classrooms in southern China. In this optimization method, first, the optimization objectives and variables are determined according to building characteristics, and the physical model is established through simulation software (EnergyPlus) to generate the sample space. Second, sensitivity analysis is carried out for each optimization variable, and the physical model is modified according to the results to regenerate the sample space. Third, the ANN model is trained by using the regenerated sample space, and the Pareto optimal solution is generated through the use of the non-dominated sorting genetic algorithm II (NSGA-II). Finally, the effectiveness of the multi-objective optimization method is proven through a typical case of primary and secondary school classrooms in Nanjing, China. The results show that, compared with the benchmark scheme, TES decreased by 810.8 kWh at most, PT increased by 47.8% at most and DI increased by 4.2% at most