scholarly journals Integrated Process Re-Design with Operation in the Digital Era: Illustration through an Industrial Case Study

Processes ◽  
2021 ◽  
Vol 9 (7) ◽  
pp. 1203
Author(s):  
Maria Marcos ◽  
José Luis Pitarch ◽  
Cesar de Prada
Keyword(s):  
Cooling Water ◽  
Heat Pumps ◽  
Optimal Operation ◽  
Operating Conditions ◽  
Mixed Integer ◽  
Industrial Case Study ◽  
Non Linear Programming ◽  
Digital Era ◽  
Network Operation

This work discusses what should be the desirable path and correct tools for the optimal re-design and operation of processes in the Industry 4.0 framework, as illustrated in a challenging case study corresponding to a complex network of evaporation plants in a viscose-fiber factory. The goal is to integrate optimal design, to improve the existing cooling systems, together with the optimal operation of the whole network, balancing the initial investment with the potentially achievable savings. A rigorous mathematical model for such optimization purpose has been built. The model explicitly considers different structural alternatives as a superstructure for the incorporation of new equipment into the network. The uncertainty associated to future operating conditions is also considered by using a two-stage stochastic formulation. Furthermore, the model is also the base from which a deterministic real-time optimization (RTO) builds upon to support the daily management of the future network operation. The RTO tool suggests the allocation of different products to evaporation plants, the distribution of the cooling water and the suitable number of heat pumps to switch on for optimal economic operation. Design and operation problems are formulated and solved via mixed-integer non-linear programming and the results have been tested with historical plant data.

scholarly journals Approximating Nonlinear Relationships for Optimal Operation of Natural Gas Transport Networks

Processes ◽  
2018 ◽  
Vol 6 (10) ◽  
pp. 198 ◽  
Author(s):  
Kody Kazda ◽  
Xiang Li
Keyword(s):  
Natural Gas ◽  
Piecewise Linear ◽  
Approximation Error ◽  
Compressibility Factor ◽  
Optimal Operation ◽  
Operating Conditions ◽  
Mixed Integer ◽  
Nonlinear Relationships ◽  
The Common

The compressor fuel cost minimization problem (FCMP) for natural gas pipelines is a relevant problem because of the substantial energy consumption of compressor stations transporting the large global demand for natural gas. The common method for modeling the FCMP is to assume key modeling parameters such as the friction factor, compressibility factor, isentropic exponent, and compressor efficiency to be constants, and their nonlinear relationships to the system operating conditions are ignored. Previous work has avoided the complexity associated with the nonlinear relationships inherent in the FCMP to avoid unreasonably long solution times for practical transportation systems. In this paper, a mixed-integer linear programming (MILP) based method is introduced to generate piecewise-linear functions that approximate the previously ignored nonlinear relationships. The MILP determines the optimal break-points and orientation of the linear segments so that approximation error is minimized. A novel FCMP model that includes the piecewise-linear approximations is applied in a case study on three simple gas networks. The case study shows that the novel FCMP model captures the nonlinear relationships with a high degree of accuracy and only marginally increases solution time compared to the common simplified FCMP model. The common simplified model is found to produce solutions with high error and infeasibility when applied on a rigorous simulation.

scholarly journals Optimization of an Inter-Plant Hydrogen Network: A Simultaneous Approach to Solving Multi-Period Optimization Problems

Processes ◽  
2020 ◽  
Vol 8 (12) ◽  
pp. 1548
Author(s):  
Rusong Han ◽  
Lixia Kang ◽  
Yinghua Jiang ◽  
Jing Wang ◽  
Yongzhong Liu
Keyword(s):  
Hydrogen Exchange ◽  
Optimization Problems ◽  
Operating Conditions ◽  
Utilization Efficiency ◽  
Simultaneous Optimization ◽  
Optimization Approach ◽  
Industrial Case Study ◽  
Scheduling Scheme ◽  
Hydrogen Network

Inter-plant hydrogen integration can reduce the consumption of hydrogen utility in petrochemical parks. However, the fluctuation of operating conditions will lead to complex multi-period problems of hydrogen network integration. This work develops a simultaneous optimization approach to solving multi-period optimization problems for the inter-plant hydrogen network. To do this, we consider the inter-plant hydrogen integration and the fluctuation of operating conditions in each plant at the same time, and aim to minimize the total annualized cost of the entire hydrogen system of all plants involved. An industrial case study of a three-plant hydrogen network with seven subperiods was adopted to verify the effectiveness of the proposed method. Results show that the optimal structure and the corresponding scheduling scheme can be obtained when the lowest cost of the system is targeted. Compared with the stepwise methods, the proposed approach features taking the characteristics of all subperiods into account simultaneously and making the structure of the hydrogen network much more effective and economical. For the scheduling schemes, the utilization efficiency of the internal hydrogen sources is increased by hydrogen exchange among the plants.

Increasing the Flexibility of Combined Heat and Power Plants With Heat Pumps and Thermal Energy Storage

2017 ◽  
Vol 140 (2) ◽  
Author(s):  
Eike Mollenhauer ◽  
Andreas Christidis ◽  
George Tsatsaronis
Keyword(s):  
Thermal Energy ◽  
Electricity Market ◽  
Power Plants ◽  
Combined Heat And Power ◽  
Heat Pumps ◽  
Optimal Operation ◽  
Mixed Integer ◽  
Steam Turbines ◽  
Mixed Integer Linear Program ◽  
District Heating System

Combined heat and power (CHP) plants are efficient regarding fuel, costs, and emissions compared to the separate generation of heat and electricity. Sinking revenues from sales of electricity due to sinking market prices endanger the economically viable operation of the plants. The integration of heat pumps (HP) and thermal energy storages (TESs) represents an option to increase the flexibility of CHP plants so that electricity can be produced only when the market conditions are favorable. The investigated district heating system is located in Germany, where the electricity market is influenced by a high share of renewable energies. The price-based unit-commitment and dispatch problem is modeled as a mixed integer linear program (MILP) with a temporal resolution of 1 h and a planning horizon of 1 yr. This paper presents the optimal operation of a TES unit and a HP in combination with CHP plants as well as synergies or competitions between them. Coal and gas-fired CHP plants with back pressure or extraction condensing steam turbines (STs) are considered, and their results are compared to each other.

scholarly journals Optimal Operating Schedule for Energy Storage System: Focusing on Efficient Energy Management for Microgrid

Processes ◽  
2019 ◽  
Vol 7 (2) ◽  
pp. 80 ◽  
Author(s):  
Sooyoung Jung ◽  
Yong Tae Yoon
Keyword(s):  
Energy Storage ◽  
Energy Management ◽  
Power Grid ◽  
Optimal Operation ◽  
Operating Conditions ◽  
Mixed Integer ◽  
Small Scale ◽  
Basic Operation ◽  
Electricity Use ◽  
Operation Schedule

A microgrid is a group of many small-scale distributed energy resources, such as solar/wind energy sources, diesel generators, energy storage units, and electric loads. As a small-scale power grid, it can be operated independently or within an existing power grid(s). The microgrid energy management system is a system that controls these components to achieve optimized operation in terms of price by reducing costs and maximizing efficiency in energy consumption. A post-Industry-4.0 consumer requires an optimal design and control of energy storage based on a demand forecast, using big data to stably supply clean, new, and renewable energy when necessary while maintaining a consistent level of quality. Thus, this study focused on software technology through which an optimized operation schedule for energy storage in a microgrid is derived. This energy storage operation schedule minimizes the costs involved in electricity use. For this, an optimization technique is used that sets an objective function representing the information and costs pertaining to electricity use, while minimizing its value by using Mixed Integer Linear Programming or a Genetic Algorithm. The main feature of the software is that an optimal operation schedule derivation function has been implemented with MATLAB for the following circumstances: when the basic operation rules are applied, when operating with another grid, when the external operating conditions are applied, and when the internal operating conditions are applied.

Optimal Power Generation Unit Sizing for Combined Heating and Power Systems With Uncertain Loads and Fuel/Electricity Prices

2011 ◽  
Author(s):  
Aaron Smith ◽  
Kyungtae Yun ◽  
Robert Thomas ◽  
Rogelio Luck
Keyword(s):  
Power Systems ◽  
Optimal Solution ◽  
Optimal Operation ◽  
Computational Effort ◽  
Mixed Integer ◽  
Weather Data ◽  
Optimal Sizing ◽  
Electricity Cost ◽  
Analytical Scheme

An optimal sizing method is developed in this work based on an analytical scheme for determining optimal operation decisions. Using the analytic optimal operation scheme allows for a more thorough optimal sizing method because of the minimal computational effort required as compared to mixed integer programming approaches. For example, an optimal sizing method based on this approach can more feasibly consider several years of weather data and the range of likely fuel/electricity costs for the term of operation of the PGU. The optimal sizing method in this work takes advantage of this efficient optimal operation scheme and provides a robust optimal solution with respect to weather and fuel/electricity cost uncertainty. A case study of a medium sized office building is carried out by testing the algorithm for a range of 20 commercially available diesel engine PGUs.

The Reverse Osmosis Membrane System Design for Freshwater Production

2011 ◽  
Vol 332-334 ◽  
pp. 1539-1544
Author(s):  
Yan Yue Lu ◽  
An Ping Liao ◽  
Yang Dong Hu
Keyword(s):  
Reverse Osmosis ◽  
Design Method ◽  
Membrane System ◽  
Optimization Method ◽  
Optimal Number ◽  
Operating Conditions ◽  
System Structure ◽  
Mixed Integer ◽  
Non Linear Programming ◽  
Minlp Problem

The reverse osmosis (RO) desalination process to make multiple freshwater from seawater has been studied in this work. The optimization method based on process synthesis has been applied to design the RO system. The optimum design problem can be formulated as a mixed-integer non-linear programming (MINLP) problem, which minimizes the total annualized cost of the RO system. The solution of the problem includes the optimal system structure and operating conditions, and the optimal streams distribution. The design method could also be used for the optimal selection of the types of membrane elements in each stages and the optimal number of membrane elements in each pressure vessel. The effectiveness of this design methodology has been demonstrated by solving a desalination case.

scholarly journals Optimal operation of building microgrids – comparison with mixed-integer linear and continuous non-linear programming approaches

2018 ◽  
Vol 37 (2) ◽  
pp. 603-616 ◽  
Author(s):  
Vincent Reinbold ◽  
Van-Binh Dinh ◽  
Daniel Tenfen ◽  
Benoit Delinchant ◽  
Dirk Saelens
Keyword(s):  
Linear Programming ◽  
Air Quality ◽  
Energy Management ◽  
Ventilation System ◽  
Optimal Operation ◽  
Mixed Integer ◽  
Management Problem ◽  
Content Type ◽  
Non Linear Programming ◽  
Non Linear

PurposeThis paper aims to present two mathematical models to solve the Energy Management problem of a building microgrid (MG). In particular, it proposes a deterministic mixed integer linear programming (MILP) and non-linear programming (NLP) formulations. This paper focuses on the modelling process and the optimization performances for both approaches regarding optimal operation of near-zero energy buildings connected to an electric MG with a 24-h time horizon. Design/methodology/approachA general architecture of a MG is detailed, involving energy storage systems, distributed generation and a thermal reduced model of the grid-connected building. A continuous non-linear model is detailed along with linearizations for the mixed-integer liner formulation. Multi-physic, non-linear and non-convex phenomena are detailed, such as ventilation and air quality models. FindingsResults show that both approaches are relevant for solving the energy management problem of the building MG. Originality/valueIntroduction and modelling of the thermal loads within the MG. The resulting linear program handles the mutli-objective trade-off between discomfort and the cost of use taking into account air quality criterion. Linearization and modelling of the ventilation system behaviour, which is generally non-linear and non-convex equality constraints, involving air quality model, heat transfer and ventilation power. Comparison of both MILP and NLP methods on a general use case provides a solution that can be interpreted for implementation.

scholarly journals Systematic Design, Optimization, and Sustainability Assessment for Generation of Efficient Wastewater Treatment Networks

Water ◽  
2021 ◽  
Vol 13 (9) ◽  
pp. 1326
Author(s):  
Emmanuel A. Aboagye ◽  
Sean M. Burnham ◽  
James Dailey ◽  
Rohan Zia ◽  
Carley Tran ◽  
...  
Keyword(s):  
Wastewater Treatment ◽  
Systems Engineering ◽  
Sustainability Assessment ◽  
Cost Effective ◽  
Mixed Integer ◽  
Non Linear Programming ◽  
Sustainability Analysis ◽  
Sustainable Process Index ◽  
The Cost

Due to population growth and economic development, there has been an increase in global wastewater (WW) generation footprint. There are different technologies associated with the wastewater treatment (WWT) process. The challenge is to select technologies that minimize the cost of treatment, as well as meet purity requirements. Further, there is a need to integrate sustainability analysis to facilitate a holistic decision. With the application of systems engineering, sustainable and cost-effective solutions can be achieved. In this work, we apply systems engineering to generate a sustainable and cost-effective solution. A superstructure was generated by categorizing technologies into four treatment stages. After modeling all functional equations for each technology, an optimization problem was formulated to determine the best path for the treatment process. Mixed-integer non-linear programming (MINLP), which implements a 0–1 binary integer constraint for active/inactive technologies at each stage was used. Sustainability analysis was performed for each representative case study (municipal and pharmaceutical WWT) using the sustainable process index (SPI). The total cost of municipal WWT is 1.92 USD/m3, while that for the pharmaceutical WWT is 3.44 USD/m3. With the treatment of WW, there is a reduction of over 90% ecological burden based on the SPI metric.

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