Optimum control strategy for all-variable speed chiller plant

The optimum control strategy and the saving potential of all variable chiller plant under the conditions of changing building cooling load and cooling water supply temperature were investigated. Based on a simulation model of water source chiller plant established in dynamic transient simulation program (TRNSYS),the four-variable quadratic orthogonal regression experiments were carried out by taking cooling load,cooling water supply temperature,cooling water flow rate and chilled water flow rate as variables,and the fitting formulas expressing the relationships between the total energy consumption of chiller plant with the four selected parameters was obtained. With the SAS statistical software and MATHEMATICA mathematical software,the optimal chilled water flow rate and cooling water flow rate which result in the minimum total energy consumption were determined under continuously varying cooling load and cooling water supply temperature. With regard to a chiller plant serving an office building in Shanghai,the total energy consumptions under different control strategies were computed in terms of the forecasting function of cooling load and water source temperature. The results show that applying the optimal control strategy to the chiller plant can bring a saving of 23.27% in power compared with the corresponding conventional variable speed plant,indicating that the optimal control strategy can improve the energy efficiency of chiller plant.

Hybrid Chiller Plant Optimization Strategies for Hotel Building on Nile River of Egypt

Hybrid chiller plants (HCPs) using multiple chillers and different energy sources are highly recommended in several energy applications in non-residential buildings such as hospitals and hotels. Time of use and cooling load profiles are significant factors that should be carefully considered either in chiller plant design or in chiller sequencing operation. This article aims to present an operation planning of HCP which consists of both electric and non-electric chillers. Four operational strategies are proposed and solved to compare their coefficients of performance and economics of running costs. A typical hotel building located on the Nile river in Egypt is selected to perform the current thermal and economic case study. The total cooling load profile of this hotel building is 4000 refrigeration tonnage (TR), which is simulated to optimize chiller sequence of operation and to select optimal design conditions of both numbers for electric and non-electric chillers used in HCP. The results of this comparative study for running cost are defined using various design configurations with different several chiller sequences available for each configuration. Then, the results of COPs, and operational running cost and initial cost are presented in this article also. The comparison aims to find the optimal design and operational sequencing for HCPs on thermal basis and economic analysis which were attached in this article. Recommendations and suggestions for future work are attached at the end of this article.

An optimization-oriented modeling approach using input convex neural networks and its application on optimal chiller loading

Optimization for the multi-chiller system is an indispensable approach for the operation of highly efficient chiller plants.The optima obtained by model-based optimization algorithms are dependent on precise and solvable objective functions.The classical neural networks cannot provide convex input-output mappings despite capturing impressive nonlinear fitting capabilities,resulting in a reduction in the robustness of model-based optimization.In this paper,we leverage the input convex neural networks(ICNN)to identify the chiller model to construct a convex mapping between control variables and the objective function,which enables the NN-based OCL as a convex optimization problem and apply it to multi-chiller optimization for optimal chiller loading(OCL).Approximation performances are evaluated through a four-model comparison based on an experimental data set,and the statistical results show that,on the premise of retaining prior convexities,the proposed model depicts excellent approximation power for the data set,especially the unseen data.Finally,the ICNN model is applied to a typical OCL problem for a multi-chiller system and combined with three types of optimization strategies.Compared with conventional and meta-heuristic methods,the numerical results suggest that the gradient-based BFGS algorithm provides better energy-saving ratios facing consecutive cooling load inputs and an impressive convergence speed.

A non-cooperative game-based distributed optimization method for chiller plant control

The heating,ventilation,and air-conditioning(HVAC)systems account for about half of the building energy consumption.The optimization methodology access to optimal control strategies of chiller plant has always been of great concern as it significantly contributes to the energy use of the whole HVAC system.Given that conventional centralized optimization methods relying on a central operator may suffer from dimensionality and a tremendous calculation burden,and show poorer flexibility when solving complex optimization issues,in this paper,a novel distributed optimization approach is presented for chiller plant control.In the proposed distributed control scheme,both trade-offs of coupled subsystems and optimal allocation among devices of the same subsystem are considered by developing a double-layer optimization structure.Non-cooperative game is used to mathematically formulate the interaction between controlled components as well as to divide the initial system-scale nonlinear optimization problem into local-scale ones.To solve these tasks,strategy updating mechanisms(PSO and IPM)are utilized.In this way,the approximate global optimal controlled variables of devices in the chiller plant can be obtained in a distributed and local-knowledge-enabled way without neither global information nor the central workstation.Furthermore,the existence and effectiveness of the proposed distributed scheme were verified by simulation case studies.Simulation results indicate that,by using the proposed distributed optimization scheme,a significant energy saving on a typical summer day can be obtained(1809.47 kW·h).The deviation from the central optimal solution is 3.83%.