This chapter describes building temperature controls and the associated flow and pressure controls. Flow control loops are cascaded with temperature control loops in pressure-independent variable-air-volume boxes and are used in air-handling units to regulate the outdoor air flow rate. For outdoor air flow control loops and cooling based on the use of cool outdoor air, overshooting may be a problem when the outdoor air temperature is below freezing. The chapter considers algorithms for modulating valves, dampers, and other devices to control temperature, pressure, or flow. The temperature difference between the water leaving the condenser and the water leaving the evaporator is strongly correlated with the pressure difference across the compressor. Therefore, the chiller power can be reduced if the leaving water temperature difference can be reduced. The temperature difference between the water leaving the condenser and the water leaving the evaporator is strongly correlated with the pressure difference across the compressor.

This paper reports a comparison of models for estimating the return time from a night setback condition. Fifty-seven models are compared using simulation data that include the influence of climate, building mass, controller tuning, room orientation, and the unoccupied control strategy on return time. Two-parameter models are recommended for estimating the return time for both heating and cooling. The models use the room air temperature and an EWMA of the normalized heating demand (for the heating model) or cooling demand (for the cooling model) as predictor variables. The outdoor air temperature, a common input for predicting return time, is not used in the recommended models, but influences the return time through its effect on the heating and cooling demands.

A major class of extremum seeking control is based on the use of periodic dither perturbation of plant input for extracting the gradient information. Presence of the dither input into the steady state operation is undesirable in practice due to the possible excessive wear of actuators. It is thus beneficial to stop the dithering action after the extremum seeking process reaches its steady state. In this paper, we propose a method for automatically discriminate between the steady state and the transient state modes of extremum seeking control process using the sinusoidal detection techniques. Some design guidelines are proposed for the parameter selection of the relevant sinusoidal detection scheme. The proposed scheme is validated with simulation study.

For wind turbine operation, wind variations around the rated wind speed can lead to frequent controller switching actions, which may result in significant fluctuation in power output and structural load. This paper presents a bumpless transfer scheme for the inter-region controller switching for variable-speed variable-pitch wind turbines, which aims to reduce the associated power fluctuation and fatigue load. The study follows a typical partition of Region 2 (maximum power capture control), Region 2.5 (rotor speed regulation), and Region 3 (constant power control) around the rated wind speed. Two relatively simple bumpless transfer techniques, i.e., 1)the conditioning technique and 2)the linear quadratic (LQ) technique, respectively, are employed for different situations of inter-region controller switching. The conditioning bumpless transfer approach is adopted for switching between Regions 2 and 2.5 via generator torque control. The LQ bumpless transfer technical is applied to the switching between Regions 2.5 and 3, when the generator torque is saturated at its rated value, the pitch controller takes over so as to limit the load of wind turbine. The simulation results demonstrated the effectiveness of the proposed scheme of inter-region switching, with significant reduction of power flicker and structural load.

This paper presents a multivariable Newton-based extremum seeking control (ESC) scheme for efficient operation of a chilled-water plant. A MODELICA-based dynamic simulation model of the chilled-water plant consists of one screw chiller and one counter-flow cooling tower was adopted for evaluation of proposed two-input Newton-based ESC controller. The ESC controller takes the total power of the chiller compressor, the cooling-tower fan, and the condenser water (CW) pump as feedback signal and discovers the optimum outputs of cooling-tower fan speed and the condenser-loop water flow rate to maximize the power efficiency in real time with the cooling load being satisfied. Remarkable energy saving is observed for several testing conditions.

Maximum power point tracking (MPPT) and fault diagnosis are two important aspects of reducing the cost of energy for photovoltaic (PV) systems. Many mechanisms of PV degradation are associated with change in the internal resistance, especially the shunt resistance. This brief proposes a cost-effective scheme for detecting the change of PV internal resistance using the signals available in extremum-seeking control (ESC)-based MPPT. With the square-wave dither inputs, the steady-state trajectories of PV output signals effectively consist of a train of small-amplitude step responses. The transient characteristics of such step responses are affected by the PV internal resistance. A small-signal transfer function analysis is performed for the PV buck system, which justifies the impact of the internal resistance on the transient characteristics. A simulation study is first conducted for single-string PV systems, and the simulation results show that ESC can achieve satisfactory MPPT under a square-wave dither input. The transient characteristics, such as integrated absolute error, show a strong correlation with the internal resistance. The applicability of this scheme to multistring PV is demonstrated with a multi-input ESC based on the total power feedback, with the internal resistance of individual modules detectable from one output signal.

This paper presents a self-optimizing robust control scheme that can maximize the power generation for a variable speed wind turbine with Doubly-Fed Induction Generator (DFIG) operated in Region 2. A dual-loop control structure is proposed to synergize the conversion from aerodynamic power to rotor power and the conversion from rotor power to the electrical power. The outer loop is an Extremum Seeking Control (ESC) based generator torque regulation via the electric power feedback. The ESC can search for the optimal generator torque constant to maximize the rotor power without wind measurement or accurate knowledge of power map. The inner loop is a vector-control based scheme that can both regulate the generator torque requested by the ESC and also maximize the conversion from the rotor power to grid power. An ℋ(∞) controller is synthesized for maximizing, with performance specifications defined based upon the spectrum of the rotor power obtained by the ESC. Also, the controller is designed to be robust against the variations of some generator parameters. The proposed control strategy is validated via simulation study based on the synergy of several software packages including the TurbSim and FAST developed by NREL, Simulink and SimPowerSystems.

This paper proposes a nested-loop extremum seeking control (NLESC) scheme for optimizing the energy capture of wind farm that is formed by a wind turbine array along the prevailing wind direction. It has been shown in earlier work that the axial induction factors of individual wind turbines can be optimized from downstream to upstream units in a sequential manner, which is a spatial domain analogy to the principle of optimality in dynamic programing. Therefore, it is proposed to optimize the turbine operation by a nested-loop optimization framework from the downstream to upstream turbines, based on feedback of the power of the immediate turbine and its downstream units. The extremum seeking control (ESC) based on dither–demodulation scheme is selected as a model-free real-time optimization solution for the individual loops. First, the principle of optimality for optimizing wind farm energy capture is proved for the cascaded wind turbine array based on the disk model. Analysis shows that the optimal torque gain of each turbine in a cascade of turbines is invariant with wind speed if the wind direction does not change. Then, the NLESC scheme is proposed, with the array power coefficient selected as the performance index to be optimized in real-time. As changes of upstream turbine operation affect downstream turbines with significant delays due to wind propagation, a cross-covariance based delay estimate is used to improve the determination of the array power coefficient. The proposed scheme is evaluated with simulation study using a three-turbine wind farm with the simwindfarm simulation platform. Simulation study is performed under both smooth and turbulent winds, and the results indicate the convergence to the actual optimum. Also, simulation under different wind speeds supports the earlier analysis results that the optimal torque gains of the cascaded turbines are invariant to wind speed.

The Hybrid Ground Source Heat Pump (GSHP) systems combine the renewable geothermal energy and cooling tower for rejecting the cooling load, which is often adopted for high cooling demand. Model based control can be limited due to variations in ambient conditions, ground-loop heat exchanger (GHE) and equipment characteristics, cost and reliability of sensors. A self-optimizing control scheme is proposed for efficient operation of the hybrid GSHP based on Extremum Seeking Control (ESC), with feedback of the total power consumption and the control inputs of the relative flow rate of cooling tower and the water pump speed. The cooling capacity of the heat pump regulates the evaporator leaving water at 7 degrees C. A Modelica based dynamic simulation model is developed for a Hybrid GSHP system, with the vertical GHE model adopted from Modelica Buildings Library. The transient heat transfer is implemented with a finite volume method inside and outside the borehole. The proposed ESC scheme is evaluated under the scenarios of fixed cooling load, ramp change in the evaporator inlet water temperature, diurnal sinusoidal cycle of air wet-bulb temperature, and realistic ambient and cooling load condition. Simulation results show the proposed ESC strategy effectively achieves nearly optimal efficiency without the need for plant model. (C) 2015 Elsevier Ltd. All rights reserved.

In wind farm operation, the performance and loads of downstream turbines are heavily influenced by the wake of the upstream turbines. Furthermore, the actual wake is more challenging due to the dynamic phenomenon of wake meandering, i.e. the turbine wake often demonstrates dynamic shift over time. To deal with the time-varying characteristics of wake meandering, a multiple model predictive control (MMPC) scheme is applied to the individual pitch control (IPC) based load reduction. The coherence function in the spectral method is used to generate the stochastic wind profile including wake meandering at upstream turbine, and a simplified wake meandering model is developed to emulate the trajectory of the wake center at downstream turbine. The Larsen wake model and Gaussian distribution of wake deficit are applied for composing wind profiles across the rotor of downstream turbines. A set of MMPC controllers are designed based on different linearized state-space models, and are applied in a smooth switching manner. Simulation results show significant reduction in the variation of both rotor speed and blade-root flapwise bending moment using the MMPC based IPC by including the wake meandering, as compared to a benchmark PI controller designed by NREL.

The air-side economizers have been developed as a major class of energy-saving equipment to enhance the energy efficiency of central air-conditioning systems by taking advantage of outdoor air during cool or cold weather. In current practice, the outdoor air damper is controlled to maintain either the maximum or minimum opening by comparing the outdoor air temperature/enthalpy with the setpoint temperature/enthalpy or return-air temperature/enthalpy. However, in practice many economizers do not behave as expected or even waste more energy due to the erroneous damper actions because of the inaccurate or failed temperature and/or relative humidity (RH) sensors. Recently, a self-optimizing controller based on extremum seeking control (ESC) has been proposed in an earlier study by Li et al. (2010) for efficient operation of an air-side economizer. This paper presents two experimental studies of the ESC air-side economizer control: one is a laboratory setup with a direct-expansion air conditioning unit, and the other is a chilled-water based air handling unit (AHU) facility at Iowa Energy Center. Experimental results from both studies validate the effectiveness of the ESC scheme as a model free optimal control strategy for air-side economizer operation.

This article is the second in the two-part series examining recent advances in the dynamic modeling of HVAC systems, which can be challenging due to the multi-physical and multi-scale processes of such systems. Part I reviewed the progress in dynamic modeling of major types of HVAC equipment. Part II presents a detailed review of dynamic modeling of HVAC equipment using Modelica, an object oriented modeling platform that has demonstrated potential in addressing HVAC equipment challenges. The Modelica-based modeling platform offers some desirable features, such as object-oriented and acausal modeling, that could significantly facilitate modeling efforts and reduce the time of model development. Currently, there are many numerically robust and efficient integrated simulation environments that support the Modelica-based modeling platform, such as Dymola, SimulationX, and MapleSim. This article reviews historical and recent modeling and simulation tools, and later examines previous work on the Modelica-based dynamic modeling of HVAC equipment. It also presents current issues and possible future directions of dynamic modeling for HVAC equipment.

In this study, a multi-variable extremum seeking control (ESC) scheme is proposed for a variable-speed mini-split air-conditioning system. The control inputs are the evaporator and condenser fan speeds, respectively. While the total power consumption is used as the feedback. The multi-variable ESC can optimize the control inputs for each channel in real-time, without relying on the accurate model of the system. This nearly model free feature makes the system more easily to be designed and deployed. First, the multi-variable ESC algorithm is deployed on a Dymola-based ASHP model to show its effectiveness in searching the optimal working point. Then, an experiment set-up is built to further demonstrate the promising performance in improving the efficiency of the mini-split AC system via multi-variable ESC.

Dynamic modeling of HVAC equipment is a subject of particular importance for control system design and fault detection and diagnosis, while the transient behaviors of the associated processes are, in principle, very complicated and feature strong interactions among multiple physical domains. Part I of this article reviews the research advancement in dynamic modeling of HVAC equipment, focusing on advancement of the past several years, including vapor compression cycles, air-handling units, major types of chillers, cooling tower, heating systems, and renewable-energy driven systems. In Part II, we will present a detailed review of advances in dynamic modeling of HVAC equipment using Modelica, an equation-based multi-physical dynamic simulation platform.

The chilled water system, typically consisting of chiller and cooling tower, plays a major role in the ventilation and air-conditioning systems in commercial buildings. Due to the significant power consumption of such system, improvement of its efficiency would lead to significant benefit in energy saving. As the system characteristics and operational conditions can vary dramatically in practice, model-free self-optimizing control is of high interest in practice. In this study, the chilled-water plant being studied consists of one screw chiller and one counter-flow cooling tower A multi-variable Newton-based extremum seeking control (ESC) scheme is applied to maximize the power efficiency in real time with the cooling load being satisfied. The feedback for the ESC controller is the total power of the chiller compressor the cooling tower fan and the condenser water pump, while the inputs are cooling-tower fan speed and the condenser-loop water flow rate. The two-input Newton-based ESC controller is simulated with a Modelica based dynamic simulation model of the chiller-tower system. Two inner-loop PI controllers are used to regulate the temperatures of evaporator superheat and evaporator leaving water at their respective setpoints. Simulation results validate the effectiveness of the proposed control strategy. Remarkable energy saving is observed for several testing conditions.

This paper proposes a novel control approach for optimizing wind farm energy capture with a nested-loop scheme of extremum seeking control (ESC). Similar to Bellman’s Principle of Optimality, it has been shown in earlier work that the axial induction factors of individual wind turbines can be optimized from downstream to upstream units in a sequential manner, i.e. the turbine operation can be optimized based on the power of the immediate turbine and its downstream units. In this study, this scheme is illustrated for wind turbine array with variable-speed turbines for which torque gain is controlled to vary axial induction factors. The proposed nested-loop ESC is demonstrated with a 3-turbine wind farm using the SimWindFarm simulation platform. Simulation under smooth and turbulent winds show the effectiveness of the proposed scheme. Analysis shows that the optimal torque gain of each turbine in a cascade of turbines is invariant with wind speed if the wind direction does not change, which is supported by simulation results for smooth wind inputs. As changes of upstream turbine operation affects the downstream turbines with significant delays due to wind propagation, a cross-covariance based delay estimate is proposed as adaptive phase compensation between the dither and demodulation signals.