Minimum Utility Cost Research Articles

Process Modeling and Evaluation of Plasma-Assisted Ethylene Production from Methane

The electrification of the petrochemical industry, imposed by the urgent need for decarbonization and driven by the incessant growth of renewable electricity share, necessitates electricity-driven technologies for efficient conversion of fossil fuels to chemicals. Non-thermal plasma reactor systems that successfully perform in lab scale are investigated for this purpose. However, the feasibility of such electrified processes at industrial scale is still questionable. In this context, two process alternatives for ethylene production via plasma-assisted non-oxidative methane coupling have conceptually been designed based on previous work of our group namely, a direct plasma-assisted methane-to-ethylene process (one-step process) and a hybrid plasma-catalytic methane-to-ethylene process (two-step process). Both processes are simulated in the Aspen Plus V10 process simulator and also consider the technical limitations of a real industrial environment. The economically favorable operating window (range of operating conditions at which the target product purity is met at minimum utility cost) is defined via sensitivity analysis. Preliminary results reveal that the hybrid plasma-catalytic process requires 21% less electricity than the direct one, while the electric power consumed for the plasma-assisted reaction is the major cost driver in both processes, accounting for ~75% of the total electric power demand. Finally, plasma-assisted processes are not economically viable at present. However, future decrease in electricity prices due to renewable electricity production increase can radically affect process economics. Given that a break-even electricity price of 35 USD/MWh (without considering the capital cost) is calculated for the two-step plasma process and that current electricity prices for some energy intensive industries in certain countries can be as low as 50 USD/MWh, the plasma-assisted processes may become economically viable in the future.

Aging-aware predictive control of PV-battery assets in buildings

This paper presents an aging-aware model predictive control (MPC) approach for operation of sustainable buildings with on-site photovoltaic (PV) and battery systems. On-site batteries can be used to collect excess PV power during low demand hours and to discharge when PV generation is not enough to meet loads. To further increase the value of the PV-battery assets, batteries can be proactively charged/discharged to shed peak demands for utility cost reduction. The battery life span is highly dependent on the operation strategy and aggressive charge/discharge actions lead to faster battery capacity degradation and higher overall operation cost due to more frequent replacement. The control strategy developed in this study incorporates a convex battery capacity loss model, derived from a physically-based degradation model, to capture the battery aging cost in the control optimization. The degradation model used in the control optimization consists of a set of convex and piece-wise linear sub-models to approximate the battery degradation effect at different time instances. A convex MPC problem is solved in the proposed control strategy to seek the optimal balance between the building utility cost and the battery life-cycle cost. Whole month simulation tests were carried out for a typical office building with on-site PV and battery assets. To quantify the benefits of the proposed control approach, three baseline strategies were also simulated that represent the best current practices. Test results showed that conventional battery control strategies seeking minimum utility cost could double the battery degradation rate and lead to a significant increase in the battery life-cycle cost. The proposed strategy could foresee the tradeoff between the utility cost and battery aging cost and make decisions accordingly. It was demonstrated that the proposed control solution could reduce the utility cost by 9% with moderate battery degradation increase, leading to overall building operation cost reduction up to 4%.

Synthesis of ternary distillation process structures featuring minimum utility cost using the IDEAS approach

A synthesis method for ternary distillation process structures is proposed on the basis of the infinite‐dimensional state‐space (IDEAS) approach. The proposed synthesis procedure consists of two steps. At the first step, the utility cost is minimized. The result of the first step contains many tiny flows among the modules because the number of flows is not included in the objective function. Then, at the second step, an evolutionary procedure for process simplification is executed. In this step, the weighted sum of flow rates is minimized recursively while updating the weights at each iteration. The practical process structure is finally determined from the result of the second simplification step. The developed synthesis procedure was applied to the separation problem of a ternary mixture consisting of benzene, toluene, and o‐xylene. It demonstrated that the proposed procedure provides a process whose liquid composition profile is quite similar to that of a Petlyuk column. © 2017 American Institute of Chemical Engineers AIChE J, 64: 1285–1294, 2018

Optimal synthesis of a heat‐integrated petroleum refinery configuration

The conceptual design of a petroleum refinery that satisfies multiple economics and operating constraints is a highly complex task. Coupled with the ever‐rising cost of designing and constructing a new refinery and the increasing demand for energy and fuels, there is incentive to optimize the energy recovery and energy efficiency of such a facility. This work addresses the flowsheet optimization of the synthesis of a petroleum refinery to attain an optimal heat‐integrated configuration or topology. A sequential two‐step strategy is employed that first performs simultaneous flowsheet optimization and heat integration to obtain an optimal refinery topology with minimum utility cost. Subsequently, the fixed optimal topology with minimum utility loads is optimized to arrive at a configuration with the fewest heat exchanger units. A mixed‐integer linear program (MILP) is formulated based on a superstructure representation that considers many alternative feasible refinery topologies. The computational results show meaningful reduction in the total annualized capital and operating costs as compared to a non‐heat‐integrated configuration.

Heat exchanger network design of large-scale industrial site with layout inspired constraints

This paper presents a systematic approach for the synthesis of the heat recovery network in total site using a Mixed Integer Linear Programming model. This model returns a near-to-optimal network configuration with minimum utility cost while allows to select geographically closest matches. The Heat Load Distribution is the subproblem of the network design and has been reported to be quite expensive to solve for large-scale problems. The computational complexity of HLD resides in the number of streams and the feasible networks. An additional challenge, raising particularly in industrial problems, has been the intermediate heat transfer network which aggravates the combinatorial complexity. The presented methodology deals with those difficulties by priority consideration based on the location of process units. It helps significantly reducing the computational time and also comes with a realistic network sketch with respect to the plant layout. Several examples are discussed along with a real industrial case study.

Modification of an Industrial Ethane Recovery Plant Using Mixed Integer Optimization and Shuffled Frog Leaping Algorithm

A currently in operation ethane recovery plant was simulated and compared with the real one. The objective of this process is to separate C1–C2 and \({{\rm C}_{3}^{+}}\) at the minimum utility cost. Then, optimal operating parameters were determined, in which the objective function is based on the plant profit. Shuffled frog leaping algorithm was applied for the optimization of this plant. The algorithm parameters were adjusted for improving the performance of the algorithm through optimization of the problem. The results show that at the optimum point the profit increased by 2.4% and utility costs decreased by 5%. In the next part, the potential of the plant for modification of the process configuration was considered. The analysis showed that it is possible to improve the process and refrigeration cycle configurations to the more efficient one. In the optimum point the profit increased by 8% towards the base case and operating cost decreased by 12.8%.

IDEAS approach to process network synthesis: minimum utility cost for complex distillation networks

This work aims at quantifying the minimum utility cost necessary to complete a given separation task using vapor–liquid equilibrium (distillation) operations. The Infinite DimEnsionAl State-space (IDEAS) process is introduced as a new paradigm for this process synthesis activity. The IDEAS conceptual framework includes all possible process configurations, and yields mathematical programs that are convex (linear), thereby guaranteeing the global optimality of the obtained solution. A case study, on nitrogen/oxygen mixture separation, is employed to illustrate the power of the proposed approach. The obtained IDEAS designs are compared with the corresponding McCabe–Thiele (conventional) minimum utility designs, and are shown to be as much as 50% more thermodynamically and economically efficient.

IDEAS approach to process network synthesis: Application to multicomponent MEN

AbstractA novel method for the globally optimal solution of the general process network synthesis problem is first presented and then applied to the solution of the minimum utility cost (MUC) problem for mass exchange networks (MEN) with multicomponent targets (MT). Previous approaches that address the MUC MEN MT synthesis problem are discussed, and the novel conceptual framework, Infinite DimEnsionAl State‐space (IDEAS), is then introduced. IDEAS allows the formulation of general process network synthesis problems as infinite convex (linear) programs whose local solutions are guaranteed to be globally optimal. In addition, an MUC MEN MT problem where conventional methods fail is probed. Then, the optimal network generated using IDEAS is discussed, together with the wide‐ranging potential impact and flexibility of IDEAS.

Pinch locations at heat capacity flow-rate disturbances of streams for minimum utility cost heat exchanger networks

The work deals with heat exchanger network (HEN) targeting under heat capacity flow-rates of streams disturbances. In particular, the aim is to calculate all pinches that can exist in a HEN with utilities of minimum cost when stream heat capacity flow-rates ( CPs) are allowed to change within given ranges. It is assumed that the disturbances are stochastic. The knowledge of pinches at certain as well uncertain data is of great importance in designing HENs. For instance, Pinch Technology is based on pinch phenomenon and its influence on HEN operation and design. In case of parameter disturbances, this is even more important since additional application in HEN’s control (see e.g. [1,2]). It is worthnoting that in case of disturbances, pinches behave in very complex manner as it was shown in [1–5]. A rigorous approach has been developed for calculating all feasible locations of pinches that can occur in minimum utility cost of HENs operating at varying heat capacity flow-rates of process streams. The method is based on recursive solution of mixed-integer linear programming (MILP) optimisation model that requires quite moderate number of binary variables. Examples of method application and analysis of results are presented in the work.

Minimum hot-cold and electric utility cost for a finite-capacity reservoir system

This paper quantifies the minimum hot-cold-electric utility cost for a finite-capacity reservoir system. A non-convex, nonlinear optimization problem formulation is presented whose global optimum is identified in analytic form. The optimum electric, hot, and cold utility usage is also explicitly identified. A case study on distillation is employed to illustrate the method.

Improvements for mass-exchange networks design

This paper addresses minimum utility cost mass-exchange network design by considering the special case of water minimisation. Two different situations are considered, re-use and regeneration re-use for single contaminants. For re-use, three different methods of targeting are presented, one of them being simultaneously a design method. This novel design method has the advantage of considering flowrate constraints only in the final stage of design. The concept of multiple pinches is introduced to prevent designing networks that do not lead to minimum cost distributed effluent treatment systems. For regeneration re-use, this paper presents the first known algorithm for targeting minimum water consumption in all possible situations. The targeted flowrate is then used to design the mass-exchange network, that almost always features splitting of operations.

Minimum utility cost for a multicomponent mass exchange operation

The minimum utility cost problem is investigated for a single mass exchanger which is required to meet composition targets in multiple components. The problem is formulated as a nonlinear program. Properties for this nonlinear program are then established. These lead to a combinatorial global solution methodology whose complexity grows as the square of the number of components considered. The minimum utility cost is shown to not necessarily be the maximum of the single component minimum utility costs. The solution procedure is illustrated with two example applications.

On the state space approach to mass/heat exchanger network design

In this paper, the conceptual framework and applications of the State Space Approach to Process Synthesis are presented. It is shown that the State Space Approach contains the concept of a Network Superstructure as a special case. Additionally, through various operators, it is shown to provide increased flexibility in formulating process network synthesis problems. As an example, it is demonstrated that an Assignment Operator can be used to facilitate the solution of large-scale problems. Pinch Operators are also employed in solving combined heat and mass exchange network synthesis problems. To demonstrate the usefulness of this new approach, two important problems are discussed. First, a one-step procedure is developed that minimizes the total annualized cost (TAC) of heat/mass exchange networks. Next, a novel problem, namely the pinch-based calculation of Minimum Utility Cost for a separable heat and mass exchange network, is solved.

Minimum utility cost of mass exchange networks with variable single component supplies and targets

Mass exchange network (MEN) synthesis is considered, with streams whose supply and target compositions are allowed to vary between upper and lower bounds. The design task is to determine the minimum mass separating agent (utility) cost needed for the transfer of a component from the rich to the lean streams. The mathematical formulation of this synthesis problem leads to a mixed integer nonlinear program (MINLP). This program is shown to possess certain properties which, in turn, are used to develop a solution procedure. This procedure is guaranteed to converge to the global optimum. Two examples, illustrating that utility cost savings can be achieved over the fixed composition MEN synthesis problem, are discussed

Heat exchanger network synthesis without decomposition

Most of the grassroot heat exchanger network (HEN) synthesis approaches decompose the synthesis problem into a series of three major tasks: (a) minimum utility cost calculation; (b) selection of the fewest number of matches; and (c) determination of a minimum investment cost HEN. This paper departs fro these approaches by posing the HEN synthesis problem as a single optimization problem, whose solution provides simultaneously the optimal utility consumption level, matches and network configuration. This approach alleviates the need for either estimating the optimal utility levels via targetting schemes, or for performing several optimization loops to determine the optimal utility consumption level and process stream matches. The approach can be applied to both pseudo-pinch and strict-pinch design problems. The proposed approach compares favorably with: (a) decomposition techniques; (b) with the simulated annealing approach; and (c) with other simultaneous approaches. The method is illustrated with three example problem

Automatic synthesis of mass-exchange networks with single-component targets

This paper addresses the problem of automatically synthesizing mass-exchange networks in which the mass of a single (key) component is exchanged between a set of rich streams and a set of lean streams. In the first part of this paper we present a two-stage synthesis procedure that employs one minimum allowable composition difference for all possible rich-lean stream pairs. In the first stage, a linear programming problem is solved to determine the minimum cost of mass-separating agents and to locate thermodynamic bottlenecks (pinch points) which restrict the exchange of mass between the rich and the lean streams. This formulation can also preclude (preassign) any specified forbidden (compulsory) matches between streams. In the second stage, a mixed-integer linear program is solved to yield minimum-utility cost networks in which the number of mass-exchanger units is minimized. In the second part of this paper we present a more general, yet computationally intensive, procedure that employs one minimum allowable composition difference for each possible rich-lean stream pair. These degrees of freedom are then used to minimize the annualized total cost of the network. An additional merit of the latter methodology is its potential as an improved approach for the synthesis of optimal heat-exchange networks. Several examples with industrial relevance are solved to demonstrate the usefulness of the notion of synthesizing mass-exchange networks and to illustrate the computational effectiveness of the proposed synthesis strategy.

Automatic synthesis of optimum heat exchanger network configurations

AbstractThis paper addresses the problem of automatically generating heat exchanger network configurations that feature minimum investment cost subject to minimum utility cost and fewest number of units. Based on the linear programming and the mixed‐integer linear programming (MILP) transshipment models for heat integration, a superstructure that has embedded many alternative configurations is proposed. This superstructure, which has as units the matches predicted by the MILP transshipment model, includes options for series and parallel matching, as well as stream splitting, mixing, and bypassing. Many of the implied stream connections in the superstructure are reduced to zero flow with a nonlinear programming formulation that leads to realistic and practical designs. Theoretical properties as well as the implementation aspects of the proposed procedure for the automatic generation of networks are presented. The method is illustrated with three example problems.

Synthesis of flexible heat exchanger networks for multiperiod operation

This paper addresses the problem of synthesizing heat exchanger networks that have the flexibility of coping with prespecified changes in flow rates, inlet temperatures and outlet temperatures in a finite sequence of time periods. A multiperiod version of the mixed integer linear programming (MILP) trans-shipment model is presented which accounts for the changes in pinch points and utility requirement at each time period. With use of this model as a basis, a systematic procedure is proposed for synthesizing network configurations that require minimum utility cost for each period of operation and involve the fewest number of units. Application of this synthesis procedure is illustrated with two example problems.

A structural optimization approach in process synthesis—II

Several formulations of the transshipment model from Operations Research are proposed for the optimal synthesis of heat exchanger networks. The linear programming versions are used for predicting the minimum utility cost, and can handle restricted matches and multiple utilities. The mixed-integer programming version yields minimum utility cost networks in which the number of units is minimized, while allowing stream splitting and selection of most preferred matches. It is shown that the transshipment models can also be incorporated easily within a mixed-integer programming approach for synthesizing chemical processing systems. Several numerical examples are presented which show that the proposed models are computationally very efficient.

Minimum utility usage in heat exchanger network synthesis A transportation problem

This paper formulates the minimum utility calculation for a heat exchanger network synthesis as a “transportation problem” from linear programming, allowing one to develop an effective interactive computing aid for this problem. The approach is to linearize cooling/heating curves and partition the only at potential pinch points. In this formulation user imposed constraints are readily included, the latter permitting selected stream/stream matches disallowed in total or in part. By altering the formulation of the objective function, the paper also shows how to solve a minimum utility cost problem, where each utility is available at a single temperature level. A procedure is included to handle a utility which passes through a temperature change when being used. Extending the partitioning procedure permits the formulation to accommodate match dependent approach temperatures, an extension which is useful when heat transfer through a third fluid only is allowed for some matches.