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Records with Keyword: Scheduling
Orchestrating an Effective Formulation to Investigate the Impact of EMSs (Energy Management Systems) for Residential Units Prior to Installation
Danish Mahmood, Nadeem Javaid, Sheraz Ahmed, Imran Ahmed, Iftikhar Azim Niaz, Wadood Abdul, Sanaa Ghouzali
December 10, 2019 (v1)
Keywords: appliance utility, BPSO, DR programs, DSM, EMS, energy efficiency gap, Scheduling, user comfort
Demand Response (DR) programs under the umbrella of Demand Side Management (DSM) tend to involve end users in optimizing their Power Consumption (PC) patterns and offer financial incentives to shift the load at “low-priced” hours. However, users have their own preferences of anticipating the amount of consumed electricity. While installing an Energy Management System (EMS), the user must be assured that this investment gives optimum comfort of bill savings, as well as appliance utility considering Time of Use (ToU). Moreover, there is a difference between desired load distribution and optimally-scheduled load across a 24-h time frame for lowering electricity bills. This difference in load usage timings, if it is beyond the tolerance level of a user, increases frustration. The comfort level is a highly variable phenomenon. An EMS giving optimum comfort to one user may not be able to provide the same level of satisfaction to another who has different preferences regarding electricity bill... [more]
Towards the Grand Unification of Process Design, Scheduling, and Control—Utopia or Reality?
Baris Burnak, Nikolaos A. Diangelakis, Efstratios N. Pistikopoulos
September 23, 2019 (v1)
Keywords: integration, process control, process design, Scheduling
As a founder of the Process Systems Engineering (PSE) discipline, Professor Roger W.H. Sargent had set ambitious goals for a systematic new generation of a process design paradigm based on optimization techniques with the consideration of future uncertainties and operational decisions. In this paper, we present a historical perspective on the milestones in model-based design optimization techniques and the developed tools to solve the resulting complex problems. We examine the progress spanning more than five decades, from the early flexibility analysis and optimal process design under uncertainty to more recent developments on the simultaneous consideration of process design, scheduling, and control. This formidable target towards the grand unification poses unique challenges due to multiple time scales and conflicting objectives. Here, we review the recent progress and propose future research directions.
Efficient Energy Consumption Scheduling: Towards Effective Load Leveling
Yuan Hong, Shengbin Wang, Ziyue Huang
July 26, 2019 (v1)
Keywords: demand response, demand side management, load leveling, Scheduling, smart grid
Different agents in the smart grid infrastructure (e.g., households, buildings, communities) consume energy with their own appliances, which may have adjustable usage schedules over a day, a month, a season or even a year. One of the major objectives of the smart grid is to flatten the demand load of numerous agents (viz. consumers), such that the peak load can be avoided and power supply can feed the demand load at anytime on the grid. To this end, we propose two Energy Consumption Scheduling (ECS) problems for the appliances held by different agents at the demand side to effectively facilitate load leveling. Specifically, we mathematically model the ECS problems as Mixed-Integer Programming (MIP) problems using the data collected from different agents (e.g., their appliances’ energy consumption in every time slot and the total number of required in-use time slots, specific preferences of the in-use time slots for their appliances). Furthermore, we propose a novel algorithm to efficie... [more]
Realizing Energy Savings in Integrated Process Planning and Scheduling
Liangliang Jin, Chaoyong Zhang, Xinjiang Fei
July 5, 2019 (v1)
Keywords: carbon emission, energy saving, integrated process planning &, MILP models, multi-objective optimization, Scheduling, TOPSIS
The integration of scheduling and process planning can eliminate resource conflicts and hence improve the performance of a manufacturing system. However, the focus of most existing works is mainly on the optimization techniques to improve the makespan criterion instead of more efficient uses of energy. In fact, with a deteriorating global climate caused by massive coal-fired power consumption, carbon emission reduction in the manufacturing sector is becoming increasingly imperative. To ease the environmental burden caused by energy consumption, e.g., coal-fired power consumption in use of machine tools, this research considers both makespan as well as environmental performance criteria, e.g., total power consumption, in integrated process planning and scheduling using a novel multi-objective memetic algorithm to facilitate a potential amount of energy savings; this can be realized through a better use of resources with more efficient scheduling schemes. A mixed-integer linear programmi... [more]
Optimal Multiscale Capacity Planning in Seawater Desalination Systems
Hassan Baaqeel, Mahmoud M. El-Halwagi
July 31, 2018 (v1)
Subject: Optimization
Keywords: desalination, membrane distillation, multi-effect distillation, Optimization, process integration, Scheduling
The increasing demands for water and the dwindling resources of fresh water create a critical need for continually enhancing desalination capacities. This poses a challenge in distressed desalination network, with incessant water demand growth as the conventional approach of undertaking large expansion projects can lead to low utilization and, hence, low capital productivity. In addition to the option of retrofitting existing desalination units or installing additional grassroots units, there is an opportunity to include emerging modular desalination technologies. This paper develops the optimization framework for the capacity planning in distressed desalination networks considering the integration of conventional plants and emerging modular technologies, such as membrane distillation (MD), as a viable option for capacity expansion. The developed framework addresses the multiscale nature of the synthesis problem, as unit-specific decision variables are subject to optimization, as well... [more]
Using Simulation for Scheduling and Rescheduling of Batch Processes
Girish Joglekar
July 31, 2018 (v1)
Keywords: Batch Process, coordination control, rescheduling, Scheduling, Simulation
The problem of scheduling multiproduct and multipurpose batch processes has been studied for more than 30 years using math programming and heuristics. In most formulations, the manufacturing recipes are represented by simplified models using state task network (STN) or resource task network (RTN), transfers of materials are assumed to be instantaneous, constraints due to shared utilities are often ignored, and scheduling horizons are kept small due to the limits on the problem size that can be handled by the solvers. These limitations often result in schedules that are not actionable. A simulation model, on the other hand, can represent a manufacturing recipe to the smallest level of detail. In addition, a simulator can provide a variety of built-in capabilities that model the assignment decisions, coordination logic and plant operation rules. The simulation based schedules are more realistic, verifiable, easy to adapt for changing plant conditions and can be generated in a short perio... [more]
Combined Noncyclic Scheduling and Advanced Control for Continuous Chemical Processes
Damon Petersen, Logan D. R. Beal, Derek Prestwich, Sean Warnick, John D. Hedengren
July 31, 2018 (v1)
Keywords: dynamic market, Model Predictive Control, nonlinear, process disturbances, Scheduling
A novel formulation for combined scheduling and control of multi-product, continuous chemical processes is introduced in which nonlinear model predictive control (NMPC) and noncyclic continuous-time scheduling are efficiently combined. A decomposition into nonlinear programming (NLP) dynamic optimization problems and mixed-integer linear programming (MILP) problems, without iterative alternation, allows for computationally light solution. An iterative method is introduced to determine the number of production slots for a noncyclic schedule during a prediction horizon. A filter method is introduced to reduce the number of MILP problems required. The formulation’s closed-loop performance with both process disturbances and updated market conditions is demonstrated through multiple scenarios on a benchmark continuously stirred tank reactor (CSTR) application with fluctuations in market demand and price for multiple products. Economic performance surpasses cyclic scheduling in all scenarios... [more]
Economic Benefit from Progressive Integration of Scheduling and Control for Continuous Chemical Processes
Logan D. R. Beal, Damon Petersen, Guilherme Pila, Brady Davis, Sean Warnick, John D. Hedengren
July 31, 2018 (v1)
Keywords: dynamic market, integration, market fluctuations, Model Predictive Control, nonlinear, process disturbances, Scheduling
Performance of integrated production scheduling and advanced process control with disturbances is summarized and reviewed with four progressive stages of scheduling and control integration and responsiveness to disturbances: open-loop segregated scheduling and control, closed-loop segregated scheduling and control, open-loop scheduling with consideration of process dynamics, and closed-loop integrated scheduling and control responsive to process disturbances and market fluctuations. Progressive economic benefit from dynamic rescheduling and integrating scheduling and control is shown on a continuously stirred tank reactor (CSTR) benchmark application in closed-loop simulations over 24 h. A fixed horizon integrated scheduling and control formulation for multi-product, continuous chemical processes is utilized, in which nonlinear model predictive control (NMPC) and continuous-time scheduling are combined.
Incorporating Enhanced Decision-Making Capabilities into a Hybrid Simulator for Scheduling of Batch Processes
Girish Joglekar
July 30, 2018 (v1)
Keywords: batch processes, heuristics, hybrid simulation, recipe modeling, Scheduling
A simulation model can accurately capture the details of product recipes in a batch process. By incorporating enhanced capabilities for making key assignment decisions in the simulation executive a model can mimic the experiential knowledge and rules employed in operating a process. As the process complexity and problem size increase using the mathematical programming (MP) techniques to generate schedules becomes increasingly difficult. A simulation run typically takes very little computation time and generates a schedule that is verifiable. Moreover, the model can be used to explore a wide range of parametric space to evaluate alternate policies and the impact of process uncertainties. Although there is no guarantee of optimality, the quality of schedules thus generated is very good and can be deployed in operations. In this paper the decision-making capabilities of the BATCHES simulator are presented with its application to a set of scheduling problems reported extensively in the lit... [more]
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