Parametric Study of a Simplified Ice Storage Model Operating Under Conventional and Optimal Control Strategies*

2003 ◽  
Vol 125 (1) ◽  
pp. 2-12 ◽  
Author(s):  
Gregor P. Henze
Keyword(s):  
Optimal Control ◽  
Control Strategies ◽  
Storage System ◽  
Operating Cost ◽  
Load Forecasting ◽  
Cost Savings ◽  
Ice Storage ◽  
Storage Losses ◽  
Constant Proportion ◽  
The Impact

A simplified ice storage system model was developed in which the icemaking mode is reflected by a higher power consumption per unit cooling than in chilled-water mode. The performance of four control strategies for ice storage systems is evaluated. The four control strategies investigated are chiller-priority and constant-proportion as conventional, instantaneous controls, while storage-priority and optimal control represent sophisticated controls employing load forecasting. Six parameters were investigated with respect to their influence on the ice storage system performance: Storage losses, utility rate structures, rate periods, penalty for icemaking, storage capacity, and the impact of load forecasting. Optimal control was determined to provide maximal operating cost savings. The storage-priority control yields operating costs only slightly higher than those of optimal control. Chiller-priority control realized savings that were typically on the order of 50% of what is theoretically possible (optimal control). Constant-proportion control proved to be a simple control strategy yielding higher savings than chiller-priority, yet lower than storage-priority control.

Parametric Study of a Simplified Ice Storage Model Operating Under Conventional and Optimal Control Strategies

Solar Energy ◽  
2002 ◽  
Author(s):  
Gregor P. Henze
Keyword(s):  
Optimal Control ◽  
Control Strategies ◽  
Storage System ◽  
Operating Cost ◽  
Load Forecasting ◽  
Cost Savings ◽  
Ice Storage ◽  
Storage Losses ◽  
Constant Proportion ◽  
The Impact

A simplified ice storage system model was developed in which the icemaking mode is reflected by a higher power consumption per unit cooling than in chilled-water mode. The performance of four control strategies for ice storage systems is evaluated. The four control strategies investigated are chiller-priority and constant-proportion as conventional, instantaneous controls, while storage-priority and optimal control represent sophisticated controls employing load forecasting. Six parameters were investigated with respect to their influence on the ice storage system performance: Storage losses, utility rate structures, rate periods, penalty for icemaking, storage capacity, and the impact of load forecasting. Optimal control was determined to provide maximal operating cost savings. The storage-priority control yields operating costs only slightly higher than those of optimal control. Chiller-priority control realized savings that were typically on the order of 50% of what is theoretically possible (optimal control). Constant-proportion control proved to be a simple control strategy yielding higher savings than chiller-priority, yet lower than storage-priority control.

Optimal Control Strategy for Ice-Storage System Based on Hourly Dynamic Load Simulation

2013 ◽  
Vol 671-674 ◽  
pp. 2515-2519
Author(s):  
Xue Mei Wang ◽  
Zhen Hai Wang ◽  
Xing Long Wu
Keyword(s):  
Optimal Control ◽  
Air Conditioning ◽  
Control Strategies ◽  
Storage System ◽  
Simulation Software ◽  
Ice Storage ◽  
Optimal Control Strategy ◽  
Air Conditioning System ◽  
Energy Plus ◽  
Load Simulation

This project aims to study the optimal control model of the ice-storage system which is theoretically close to the optimal control and also applicable to actual engineering. Using Energy Plus, the energy consumption simulation software, and the simple solution method of optimal control, researchers can analyze and compare the annual operation costs of the ice-storage air-conditioning system of a project in Beijing under different control strategies. Researchers obtained the power rates of the air-conditioning system in the office building under the conditions of chiller-priority and optimal contro1 throughout the cooling season. Through analysis and comparison, they find that after the implementation of optimal control, the annually saved power bills mainly result from non-design conditions, especially in the transitional seasons.

Ice Storage System Controls for the Reduction of Operating Cost and Energy Use

1998 ◽  
Vol 120 (4) ◽  
pp. 275-281 ◽  
Author(s):  
G. P. Henze ◽  
M. Krarti
Keyword(s):  
Optimal Control ◽  
Control Strategy ◽  
Energy Use ◽  
Storage Systems ◽  
Storage System ◽  
Operating Cost ◽  
Optimal Strategies ◽  
Excess Energy ◽  
Ice Storage ◽  
Optimal Control Strategy

Ice storage systems have the reputation of saving cost for operating building cooling plants by appropriately recognizing time-of-use incentives in the utility rate structure. However, many systems can consume more electrical energy than a conventional cooling plant without ice storage. This excess energy problem is illustrated in this paper by a simplified cooling plant model employed in a simulation environment that allows the assessment of the control performance of various conventional and optimal strategies. The optimal control strategy of minimizing operating cost only is introduced and subsequently is modified to allow the simultaneous consideration of operating cost and energy consumption. This proposed optimal control strategy could be valuable if ice storage systems are to stand on their own merits in a deregulated utility environment. Due to the lack of demand charges under real-time pricing, even small energy penalties and their associated excess energy cost may jeopardize the feasibility of the ice storage system.

scholarly journals Optimum Energy Flow Management of a Grid-Tied Photovoltaic-Wind-Battery System considering Cost, Reliability, and CO2 Emission

2021 ◽  
Vol 2021 ◽  
pp. 1-20
Author(s):  
Meryeme Azaroual ◽  
Mohammed Ouassaid ◽  
Mohamed Maaroufi
Keyword(s):  
Greenhouse Gas Emission ◽  
Storage System ◽  
Operating Cost ◽  
Cost Savings ◽  
Substantial Effect ◽  
Energy Management Strategy ◽  
Optimum Energy ◽  
Ghg Reduction ◽  
Reliable Model ◽  
Cover Ratio

The main goal of this paper is to explore the performance of a residential grid-tied hybrid (GTH) system which relies on economic and environmental aspects. A photovoltaic- (PV-) wind turbine- (WT-) battery storage system with maximizing self-consumption and time-of-use (ToU) pricing is conducted to examine the system efficiency. In so doing, technical optimization criteria with taking into consideration renewable energy benefits including feed-in-tariff (FIT) and greenhouse gas emission (GHG) reduction are analyzed. As the battery has a substantial effect on the operational cost of the system, the energy management strategy (EMS) will incorporate the daily operating cost of the battery and the effect of the degradation. The model can give the opportunity to the network to sell or purchase energy from the system. The simulation results demonstrate the effectiveness of the proposed approach in which the new objective function achieves the maximum cost-saving (99.81%) and income (5.16 $/day) compared to other existing strategies as well as the lowest GHG emission. Furthermore, the battery enhances the best daily self-consumption and load cover ratio. Then, as the model is nonlinear, a comparison with other existing algorithms is performed to select the feasible, robust, and reliable model for the residential application. A hybrid algorithm (HGAFMINCON) is developed to demonstrate the superiority of the algorithm over FMINCON and GA shown in terms of cost savings and income.

Effect of Design Parameters on the Performance of Thermal Energy Storage Systems

Solar Energy ◽  
2004 ◽  
Author(s):  
Gregor P. Henze
Keyword(s):  
Energy Storage ◽  
Thermal Energy ◽  
Thermal Energy Storage ◽  
Large Scale ◽  
Control Strategies ◽  
Storage System ◽  
Operating Cost ◽  
Energy Storage System ◽  
Design Parameters ◽  
Wide Range

This paper describes simulation-based results of a large-scale investigation of a commercial cooling plant including a thermal energy storage system. A cooling plant with an ice-on-coil system with external melt and a reciprocating compressor operating in a large office building was analyzed under four different control strategies. Optimal control as the strategy that minimizes the total operating cost (demand and energy charges) served as a benchmark to assess the performance of the three conventional controls. However, all control strategies depend on properly selected design parameters. The storage and chiller capacities as the primary design parameters were varied over a wide range and the dependence of the system’s cost saving performance on these parameters was evaluated.

scholarly journals Modeling the Effects of Helminth Infection on the Transmission Dynamics of Mycobacterium tuberculosis under Optimal Control Strategies

2020 ◽  
Vol 2020 ◽  
pp. 1-21
Author(s):  
Aristide G. Lambura ◽  
Gasper G. Mwanga ◽  
Livingstone Luboobi ◽  
Dmitry Kuznetsov
Keyword(s):  
Optimal Control ◽  
Equilibrium Point ◽  
Drug Administration ◽  
Mass Drug Administration ◽  
Helminth Infection ◽  
Reproduction Number ◽  
Control Strategies ◽  
Active Tuberculosis ◽  
Control Measures ◽  
The Impact

A deterministic mathematical model for the transmission and control of cointeraction of helminths and tuberculosis is presented, to examine the impact of helminth on tuberculosis and the effect of control strategies. The equilibrium point is established, and the effective reproduction number is computed. The disease-free equilibrium point is confirmed to be asymptotically stable whenever the effective reproduction number is less than the unit. The analysis of the effective reproduction number indicates that an increase in the helminth cases increases the tuberculosis cases, suggesting that the control of helminth infection has a positive impact on controlling the dynamics of tuberculosis. The possibility of bifurcation is investigated using the Center Manifold Theorem. Sensitivity analysis is performed to determine the effect of every parameter on the spread of the two diseases. The model is extended to incorporate control measures, and Pontryagin’s Maximum Principle is applied to derive the necessary conditions for optimal control. The optimal control problem is solved numerically by the iterative scheme by considering vaccination of infants for Mtb, treatment of individuals with active tuberculosis, mass drug administration with regular antihelminthic drugs, and sanitation control strategies. The results show that a combination of educational campaign, treatment of individuals with active tuberculosis, mass drug administration, and sanitation is the most effective strategy to control helminth-Mtb coinfection. Thus, to effectively control the helminth-Mtb coinfection, we suggest to public health stakeholders to apply intervention strategies that are aimed at controlling helminth infection and the combination of vaccination of infants and treatment of individuals with active tuberculosis.

scholarly journals State-Based Switching for Optimal Control of Computer Virus Propagation with External Device Blocking

2018 ◽  
Vol 2018 ◽  
pp. 1-10 ◽  
Author(s):  
Qingyi Zhu ◽  
Seng W. Loke ◽  
Ye Zhang
Keyword(s):  
Optimal Control ◽  
Control Strategies ◽  
Minimum Principle ◽  
Optimal Solution ◽  
Computer Virus ◽  
Numerical Results ◽  
Difference Approximation ◽  
External Device ◽  
Virus Propagation ◽  
The Impact

The rapid propagation of computer virus is one of the greatest threats to current cybersecurity. This work deals with the optimal control problem of virus propagation among computers and external devices. To formulate this problem, two control strategies are introduced: (a) external device blocking, which means prohibiting a fraction of connections between external devices and computers, and (b) computer reconstruction, which includes updating or reinstalling of some infected computers. Then the combination of both the impact of infection and the cost of controls is minimized. In contrast with previous works, this paper takes into account a state-based cost weight index in the objection function instead of a fixed one. By using Pontryagin’s minimum principle and a modified forward-backward difference approximation algorithm, the optimal solution of the system is investigated and numerically solved. Then numerical results show the flexibility of proposed approach compared to the regular optimal control. More numerical results are also given to evaluate the performance of our approach with respect to various weight indexes.

scholarly journals Modeling the Impact of Optimal Control Strategies on the Dynamics of Zika Virus Disease Using the Sterile Insect Technology

2020 ◽  
pp. 13-33
Author(s):  
Atokolo William ◽  
Akpa Johnson ◽  
Daniel Musa Alih ◽  
Olayemi Kehinde Samuel ◽  
C. E. Mbah Godwin
Keyword(s):  
Optimal Control ◽  
Control Strategy ◽  
Zika Virus ◽  
Human Population ◽  
Necessary Conditions ◽  
Virus Disease ◽  
Control Strategies ◽  
Control Measures ◽  
Optimal Control Strategy ◽  
The Impact

This work is aimed at formulating a mathematical model for the control of zika virus infection using Sterile Insect Technology (SIT). The model is extended to incorporate optimal control strategy by introducing three control measures. The optimal control is aimed at minimizing the number of Exposed human, Infected human and the total number of Mosquitoes in a population and as such reducing contacts between mosquitoes and human, human to human and above all, eliminates the population of Mosquitoes. The Pontryagin’s maximum principle was used to obtain the necessary conditions, find the optimality system of our model and to obtain solution to the control problem. Numerical simulations result shows that; reduction in the number of Exposed human population, Infected human population and reduction in the entire population of Mosquito population is best achieved using the optimal control strategy.

scholarly journals A Deep Learning-Based Fault Detection Model for Optimization of Shipping Operations and Enhancement of Maritime Safety

Sensors ◽  
2021 ◽  
Vol 21 (16) ◽  
pp. 5658
Author(s):  
Panayiotis Theodoropoulos ◽  
Christos C. Spandonidis ◽  
Fotis Giannopoulos ◽  
Spilios Fassois
Keyword(s):  
Condition Monitoring ◽  
Continuous Process ◽  
Operating Cost ◽  
Essential Element ◽  
Cost Savings ◽  
Process Improvements ◽  
Detection Model ◽  
Efficiency Increase ◽  
Marine Engineering ◽  
The Impact

The ability to exploit data for obtaining useful and actionable information and for providing insights is an essential element for continuous process improvements. Recognizing the value of data as an asset, marine engineering puts data considerations at the core of system design. Used wisely, data can help the shipping sector to achieve operating cost savings and efficiency increase, higher safety, wellness of crew rates, and enhanced environmental protection and security of assets. The main goal of this study is to develop a methodology able to harmonize data collected from various sensors onboard and to implement a scalable and responsible artificial intelligence framework, to recognize patterns that indicate early signs of defective behavior in the operational state of the vessel. Specifically, the methodology examined in the present study is based on a 1D Convolutional Neural Network (CNN) being fed time series directly from the available dataset. For this endeavor, the dataset undergoes a preprocessing procedure. Aspiring to determine the effect of the parameters composing the networks and the values that ensure the best performance, a parametric inquiry is presented, determining the impact of the input period and the degree of degradation that our models identify adequately. The results provide an insightful picture of the applicability of 1D-CNN models in performing condition monitoring in ships, which is not thoroughly examined in the maritime sector for condition monitoring. The data modeling along with the development of the neural networks was undertaken with the Python programming language.

Optimal Design and Control Strategies for Novel Combined Heat and Power (CHP) Fuel Cell Systems: Part I of II—Datum Design Conditions and Approach

2010 ◽  
Author(s):  
Whitney G. Colella
Keyword(s):  
Fuel Cell ◽  
Control Strategies ◽  
Cost Savings ◽  
Optimal Strategies ◽  
Combined Heat And Power ◽  
Base Case ◽  
Cell Systems ◽  
Operating Strategies ◽  
Carbon Dioxide Co2 ◽  
The Impact

Energy network optimization (ENO) models identify new strategies for designing, installing, and controlling stationary combined heat and power (CHP) fuel cell systems (FCSs) with the goals of 1) minimizing electricity and heating costs for building owners and 2) reducing emissions of the primary greenhouse gas (GHG) — carbon dioxide (CO2). A goal of this work is to employ relatively inexpensive simulation studies to discover more financially and environmentally effective approaches for installing CHP FCSs. ENO models quantify the impact of different choices made by power generation operators, FCS manufacturers, building owners, and governments with respect to two primary goals — energy cost savings for building owners and CO2 emission reductions. These types of models are crucial for identifying cost and CO2 optima for particular installations. Optimal strategies change with varying economic and environmental conditions, FCS performance, the characteristics of building demand for electricity and heat, and many other factors. ENO models evaluate both “business-as-usual” and novel FCS operating strategies. For the scenarios examined here, relative to a base case of no FCSs installed, model results indicate that novel strategies could reduce building energy costs by 25% and CO2 emissions by 80%. Part I of II articles discusses model assumptions and methodology. Part II of II articles illustrates model results for a university campus town and generalizes these results for diverse communities.

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