Optimal Setpoints for HVAC Systems via Iterative Cooperative Neighbor Communication

2014 ◽  
Vol 137 (1) ◽  
Author(s):  
Matthew Elliott ◽  
Bryan P. Rasmussen
Keyword(s):  
Energy Savings ◽  
Optimization Technique ◽  
Optimal Solution ◽  
Hvac Systems ◽  
Global Optimum ◽  
Cost Information ◽  
Steady State Condition ◽  
Air Conditioning Systems ◽  
The Cost ◽  
Dynamic Subsystem

Heating, ventilation, and air conditioning systems in large buildings frequently feature a network topology wherein the outputs of each dynamic subsystem act as disturbances to other subsystems. The distributed optimization technique presented in this paper leverages this topology without requiring a centralized controller or widespread knowledge of the interaction dynamics between subsystems. Each subsystem's controller calculates an optimal steady state condition. The output corresponding to this condition is then communicated to downstream neighbors only. Similarly, each subsystem communicates to its upstream neighbors the predicted costs imposed by the neighbors' own calculated outputs. By judicious construction of the cost functions, all of the cost information is propagated through the network, allowing a Pareto optimal solution to be reached. The novelty of this approach is that communication between all plants is not necessary to achieve a global optimum. Since each optimizer does not require knowledge of its neighbors' dynamics, changes in one controller do not require changes to all controllers in the network. Proofs of convergence to Pareto optimality under certain conditions are presented, and convergence under the approach is demonstrated with a simulation example. The approach is also applied to a laboratory-based water chiller system; several experiments demonstrate the features of the approach and potential for energy savings.

Pareto Optimal Setpoints for HVAC Networks via Iterative Nearest Neighbor Communication

2013 ◽  
Author(s):  
Matthew S. Elliott ◽  
Christopher J. Bay ◽  
Bryan P. Rasmussen
Keyword(s):  
Nearest Neighbor ◽  
Optimization Technique ◽  
Optimal Solution ◽  
Hvac Systems ◽  
Global Optimum ◽  
Pareto Optimal Solution ◽  
Pareto Optimal ◽  
Cost Information ◽  
The Cost ◽  
Dynamic Subsystem

HVAC systems in large buildings frequently feature a network topology wherein the outputs of each dynamic subsystem act as disturbances to other subsystems in a well-defined local neighborhood. The distributed optimization technique presented in this paper leverages this topology without requiring a centralized optimizer or widespread knowledge of the interaction dynamics between subsystems. Each subsystem’s optimizer communicates to its neighbors its calculated optimum setpoint, as well as the costs imposed by the neighbor’s calculated set-points. By judicious construction of the cost functions, all of the cost information is propagated through the network, allowing a Pareto optimal solution to be reached. The novelty of this approach is that communication between all plants is not necessary to achieve a global optimum, and that changes in one controller do not require changes to all controllers in the network. Proofs of Pareto optimality are presented, and convergence under the approach is demonstrated with a numerical and experimental example.

scholarly journals Dynamic simulation of indirect air conditioning systems with optimized computational time

2019 ◽  
Vol 111 ◽  
pp. 04042
Author(s):  
Nicolás Ablanque ◽  
Santiago Torras ◽  
Carles Oliet ◽  
Joaquim Rigola ◽  
Carlos-David Pérez-Segarra
Keyword(s):  
Air Conditioning ◽  
Energy Savings ◽  
Control Strategies ◽  
Model Potential ◽  
Hvac Systems ◽  
Object Oriented Programming ◽  
Computational Time ◽  
Air Conditioning System ◽  
Numerical Resolution ◽  
Air Conditioning Systems

The simulation of HVAC systems is a powerful tool to improve the energy efficiency in buildings. The modelling of such systems faces several obstacles due to both the physical phenomenology present and the numerical resolution difficulties. The present work is an attempt to develop a robust, fast, and accurate model for HVAC systems that can interact with the other relevant systems involved in buildings thermal management. The whole system model has been developed in the form of libraries under the Modelica language to exploit its advantageous characteristics: object-oriented programming, equationbased modelling, and handling of multi-physics. The global resolution is carried out dynamically so that not only steady-state predictions can be conducted but also control strategies can be studied over meaningful periods of time. This latter aspect is crucial for optimizing energy savings. The libraries include models for all the system individual components such as pumps, compressors or heat exchangers (operating with twophase flows and/or moist air) and also models assemblies to account for vapour compression units and liquid circuits. An illustrative example of an indirect air conditioning system is detailed in the present work in order to highlight the model potential.

Optimal Rescheduling of Generators for Congestion Management and Benefit Maximization in a Decentralized Bilateral Multi-transactions Power Network

2013 ◽  
Vol 14 (1) ◽  
pp. 25-32 ◽  
Author(s):  
Brijesh Singh ◽  
Ranjit Mahanty ◽  
S.P. Singh
Keyword(s):  
Power Flow ◽  
Optimal Power Flow ◽  
Optimization Technique ◽  
Optimal Solution ◽  
Congestion Management ◽  
Global Optimum ◽  
Market Model ◽  
Optimal Dispatch ◽  
Optimum Solution ◽  
Decentralized Market

Abstract This paper presents a framework to achieve an optimal power flow solution in a decentralized bilateral multitransaction-based market. An independent optimal dispatch solution has been used for each market. The interior point (IP)-based optimization technique has been used for finding a global economic optimal solution of the whole system. In this method, all the participants try to maximize their own profits with the help of system information announced by the operator. In the present work, a parallel algorithm has been used to find out a global optimum solution in decentralized market model. The study has been carried out on a modified IEEE-30 bus system. The results show that the suggested decentralized approach can provide a better optimal solution. The obtained results show the effectiveness of IP optimization-based optimal generator schedule and congestion management in the decentralized market.

Layer Separation for Optimization of Composite Laminates

2008 ◽  
Author(s):  
Hossein Ghiasi ◽  
Damiano Pasini ◽  
Larry Lessard
Keyword(s):  
Composite Laminates ◽  
Optimization Technique ◽  
Optimal Solution ◽  
Global Optimum ◽  
Important Variable ◽  
Optimization Techniques ◽  
Thin Layers ◽  
Stacking Sequence ◽  
Layer Separation ◽  
Number Of Layers

The excellent mechanical properties of laminated composites cannot be exploited without a careful design of stacking sequence of the layers. An important variable in the search of the optimum stacking sequence is the number of layers. The larger is this number, the harder as well as longer is the search for an optimal solution. To tackle efficiently such a variable-dimensional problem, we introduce here a multi-level optimization technique. The proposed method, called Layer Separation (LS), increases or decreases the number of layers by gradually separating a layer into two, or by merging two layers into one. LS uses different levels of laminate representation ranging from a coarse level parameterization, which corresponds to a small number of thick layers, to a fine level parameterization, which corresponds to a large number of thin layers. A benefit of such differentiation is an increase of the probability of finding the global optimum. In this paper, LS is applied to the design of composite laminates under single and multiple loadings. The results show that LS convergence rate is not inferior to that of other optimization techniques available in the literature. It is faster than an evolutionary algorithm, more efficient than a layerwise method, simple to perform, and it has the advantage of possibility of termination at any point during the optimization process.

scholarly journals Two-Stage Optimization Method for the Bearing Layout of Isolated Structure

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Yu Dang ◽  
GenXiong Zhao ◽  
HongTu Tian ◽  
Guobao Li
Keyword(s):  
Optimization Technique ◽  
Optimal Solution ◽  
Nonlinear Behavior ◽  
Optimization Procedure ◽  
Optimization Method ◽  
Design Parameters ◽  
Two Stage ◽  
Factors Affecting ◽  
Lead Rubber Bearing ◽  
The Cost

Design of seismic isolated building is often a highly iterative and tedious process due to the nonlinear behavior of the system, a large range of design parameters, and uncertainty of ground motions. It is needed to consider a comprehensive optimization procedure in the design of isolated buildings with optimized performances. This can be accomplished by applying a rigorous optimization technique. However, due to many factors affecting the performance of isolated buildings, possible solutions are abundant, and the optimal solution is difficult to obtain. In order to simplify the optimization process, an isolated building is always modeled as a shear-type structure supported on the isolated layer, and the optimal results are the parameters of the isolated layer which could not be used as a practical design of the isolated structure. A two-stage optimization method for designing isolated buildings as a practical and efficient guide is developed. In the first stage, a 3D isolated building model is adopted that takes into account of nonlinear behavior in building and isolation devices. The isolation devices are simplified as a kind of lead-rubber bearing. The genetic algorithm is used to find the optimal parameters of the isolated layer. In the second stage, the location parameters of isolation bearing layout are optimized. Moreover, the cost of the isolation bearing layout should be as low as possible. An integer programming method is adopted to optimize the number of each type of isolator. Considering vertical bearing capacity of isolators and the minimum eccentricity ratio of the isolated layer, the optimal bearing layout of the isolated building can be obtained. The proposed method is demonstrated in a typical isolated building in China. The optimum bearing layout of the isolated building effectively suppresses the structural seismic responses, but the cost of the isolated layer might slightly increase.

scholarly journals Economic Analysis of Lagrangian and Genetic Algorithm for the Optimal Capacity Planning of Photovoltaic Generation

2015 ◽  
Vol 2015 ◽  
pp. 1-7 ◽  
Author(s):  
Jeeng-Min Ling ◽  
Ping-Hsun Liu
Keyword(s):  
Genetic Algorithm ◽  
Capacity Planning ◽  
Optimal Allocation ◽  
Optimization Problems ◽  
Optimization Technique ◽  
Global Optimum ◽  
Probability Method ◽  
Optimal Capacity ◽  
Nonlinear Features ◽  
The Cost

The optimal allocation problem for a stand-alone photovoltaic (SPV) generation can be achieved by good compromise between system objective and constraint requirements. The Lagrange technique (LGT) is a traditional method to solve such constrained optimization problem. To consider the nonlinear features of reliability constraints evolving from the consideration of different scenarios, including variations of component cost, load profile and installation location, the implementation of SPV generation planning is time-consuming and conventionally implemented by a probability method. Genetic Algorithm (GA) has been successfully applied to many optimization problems. For the optimal allocation of photovoltaic and battery devices, the cost function minimization is implemented by GA to attain global optimum with relative computation simplicity. Analytical comparisons between the results from LGT and GA were investigated and the performance of simulation was discussed. Different planning scenarios show that GA performs better than the Lagrange optimization technique.

scholarly journals Study of Hybrid PV-Wind Energy System to Isolated Micro-grid

2015 ◽  
Vol 16 (2) ◽  
pp. 221
Author(s):  
Samir M. Dawoud ◽  
Xiangning Lin
Keyword(s):  
Renewable Energy Sources ◽  
Optimization Technique ◽  
Optimal Solution ◽  
Energy System ◽  
Hybrid Microgrid ◽  
Load Demand ◽  
Cost Of Energy ◽  
Wind Energy System ◽  
One Year ◽  
The Cost

The optimal sizing of the isolated hybrid microgrid using an optimization technique was proposed. The hybrid system features WT, PV and conversion systems were used to feed the electrical load demand. A HOMER software was used to model system performance during a time of one year, considering Sensitivity variations in both the availability of renewable energy sources and variations in the load demand. The optimal solution was obtained with respect to decrease the cost of energy (COE) and the loss of power supply probability (LPSP) over a project lifetime of 25 years to improve the isolated operation of the microgrid. The aim of this study is to investigate an optimum combination of different energy systems which can supply electricity to a rural area in Egypt. The results show the COE for the optimal model was found 0.139 $/kWh which is less than half of the PV or WT system.

OPTIMAL FEASIBLE SOLUTIONS TO A ROAD FREIGHT TRANSPORTATION PROBLEM

2020 ◽  
Vol 5 (1) ◽  
pp. 456
Author(s):  
Tolulope Latunde ◽  
Joseph Oluwaseun Richard ◽  
Opeyemi Odunayo Esan ◽  
Damilola Deborah Dare
Keyword(s):  
Transportation Problem ◽  
Optimal Solution ◽  
Transportation Cost ◽  
North West ◽  
Life Problems ◽  
Basic Feasible Solutions ◽  
Feasible Solutions ◽  
Road Freight Transportation ◽  
The Cost ◽  
Cost Of Transportation

For twenty decades, there is a visible ever forward advancement in the technology of mobility, vehicles and transportation system in general. However, there is no "cure-all" remedy ideal enough to solve all life problems but mathematics has proven that if the problem can be determined, it is most likely solvable. New methods and applications will keep coming to making sure that life problems will be solved faster and easier. This study is to adopt a mathematical transportation problem in the Coca-Cola company aiming to help the logistics department manager of the Asejire and Ikeja plant to decide on how to distribute demand by the customers and at the same time, minimize the cost of transportation. Here, different algorithms are used and compared to generate an optimal solution, namely; North West Corner Method (NWC), Least Cost Method (LCM) and Vogel’s Approximation Method (VAM). The transportation model type in this work is the Linear Programming as the problems are represented in tables and results are compared with the result obtained on Maple 18 software. The study shows various ways in which the initial basic feasible solutions to the problem can be obtained where the best method that saves the highest percentage of transportation cost with for this problem is the NWC. The NWC produces the optimal transportation cost which is 517,040 units.

scholarly journals Inclusion of Hydraulic Controls in Rehabilitation Models of Drainage Networks to Control Floods

Water ◽  
2021 ◽  
Vol 13 (4) ◽  
pp. 514
Author(s):  
Leonardo Bayas-Jiménez ◽  
F. Javier Martínez-Solano ◽  
Pedro L. Iglesias-Rey ◽  
Daniel Mora-Melia ◽  
Vicente S. Fuertes-Miquel
Keyword(s):  
Genetic Algorithm ◽  
Drainage System ◽  
Optimal Solution ◽  
Hydraulic Control ◽  
Drainage Systems ◽  
Storm Water Management Model ◽  
Drainage Networks ◽  
Extreme Rain ◽  
Rain Events ◽  
The Cost

A problem for drainage systems managers is the increase in extreme rain events that are increasing in various parts of the world. Their occurrence produces hydraulic overload in the drainage system and consequently floods. Adapting the existing infrastructure to be able to receive extreme rains without generating consequences for cities’ inhabitants has become a necessity. This research shows a new way to improve drainage systems with minimal investment costs, using for this purpose a novel methodology that considers the inclusion of hydraulic control elements in the network, the installation of storm tanks and the replacement of pipes. The presented methodology uses the Storm Water Management Model for the hydraulic analysis of the network and a modified Genetic Algorithm to optimize the network. In this algorithm, called the Pseudo-Genetic Algorithm, the coding of the chromosomes is integral and has been used in previous studies of hydraulic optimization. This work evaluates the cost of the required infrastructure and the damage caused by floods to find the optimal solution. The main conclusion of this study is that the inclusion of hydraulic controls can reduce the cost of network rehabilitation and decrease flood levels.

scholarly journals A Computer Vision-Based Occupancy and Equipment Usage Detection Approach for Reducing Building Energy Demand

Energies ◽  
2020 ◽  
Vol 14 (1) ◽  
pp. 156
Author(s):  
Paige Wenbin Tien ◽  
Shuangyu Wei ◽  
John Calautit
Keyword(s):  
Deep Learning ◽  
Real Time ◽  
Energy Demand ◽  
Energy Savings ◽  
Internal Heat ◽  
Electrical Equipment ◽  
Building Energy ◽  
Hvac Systems ◽  
Equipment Usage

Because of extensive variations in occupancy patterns around office space environments and their use of electrical equipment, accurate occupants’ behaviour detection is valuable for reducing the building energy demand and carbon emissions. Using the collected occupancy information, building energy management system can automatically adjust the operation of heating, ventilation and air-conditioning (HVAC) systems to meet the actual demands in different conditioned spaces in real-time. Existing and commonly used ‘fixed’ schedules for HVAC systems are not sufficient and cannot adjust based on the dynamic changes in building environments. This study proposes a vision-based occupancy and equipment usage detection method based on deep learning for demand-driven control systems. A model based on region-based convolutional neural network (R-CNN) was developed, trained and deployed to a camera for real-time detection of occupancy activities and equipment usage. Experiments tests within a case study office room suggested an overall accuracy of 97.32% and 80.80%. In order to predict the energy savings that can be attained using the proposed approach, the case study building was simulated. The simulation results revealed that the heat gains could be over or under predicted when using static or fixed profiles. Based on the set conditions, the equipment and occupancy gains were 65.75% and 32.74% lower when using the deep learning approach. Overall, the study showed the capabilities of the proposed approach in detecting and recognising multiple occupants’ activities and equipment usage and providing an alternative to estimate the internal heat emissions.

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