Heat Integrated Water Regeneration Network Synthesis via Graph-Theoretic Sequential Method

Batch processes are relevant to a wide variety of industries in chemical processes. In batch operations, water sources are almost not directly reused/recycled in process sinks without considering time constraints and storage tanks. However, storage tanks are usually expensive and thus a cost-effective water system has to be synthesized. Rescheduling the water network can contribute to reducing the cost of storage tanks by reducing their number and capacity. In the current research work, a goal programming is used to reschedule the water network in batch processes considering the time and storage tanks. A Mixed Integer Non-Linear Program model is introduced using the Lingo optimization program. This model is used to optimize multiple objectives, which are freshwater usage, wastewater discharge, the number and capacity of tanks, the degree of shifting streams, and the total cost of the water network. Three case studies are presented in this study to demonstrate the effectiveness of the proposed procedure, considering both single and multi-contaminants problems. The results of the first case study show a reduction in the network cost and the freshwater flowrate by 26.4% and 42%, respectively. Regarding the rescheduled water network results of the second case study, the cost is reduced by 24.6% and the freshwater flowrate is decreased by 21.8% with no requirement of storage tanks. The third case study highlights the model’s applicability to multi-contaminants problem, revealing a 15.1% cost reduction and a 25.7% decrease in freshwater flow.

The synthesis problems of non-isothermal water networks, combining heat exchanger network and water network (WN), usually consist of a significant number of constraints and variables, namely, flow rates, contaminant concentrations, temperatures and a large number of non-linear terms. In most cases, solving medium and large-scale synthesis problems is computationally too expensive and challenging. In order to circumvent that problem, we propose a compact superstructure and mixed-integer non-linear programming model for the simultaneous synthesis of non-isothermal WNs. The proposed superstructure includes heat integration stages enabling direct and indirect heat exchanges with a manageable number of hot and cold streams. This reduces the models size enabling easier solutions of the synthesis problems using local solvers. In addition, a superstructure reduction strategy is proposed making the superstructure flexible and adaptable for different types of problems, namely, pinched and threshold, and providing additional reduction of connections within the proposed superstructure. The proposed model is solved using a two-step solution strategy including initialisation and design steps. The model is applied to the examples of different complexities including single and multiple contaminant problems, and water-using and wastewater treatment units. Using the proposed iterative strategy, the improved locally optimal solutions are identified for most examples, minimising the total annual cost of the overall network.

A monetary network cost problem involving a homogeneous multi-level tree of processors and links is discussed. The monetary network cost of processing a divisible load, which is linearly dependent on the amount of divisible workload, is basically composed of a communication cost and a computing cost. A monetary network analysis is performed by aggregating the network speed parameters and network cost parameters. This allows one to obtain a closed form solution for the total monetary network cost with maintaining a minimum total parallel processing finish time. Through a mathematical derivation of the ratio of total computing time variation to total network cost variation against changes in network size, insights on trends of network performance against network cost are achieved.

With the widespread deployment of advanced heterogeneous technologies and growing complexity in our modern society, there is an increasing demand for risk‐aware management and joint operation of interconnected infrastructures and lifeline networks. The coordination between Power and Water Networks (PWNs) is urgently needed as water networks are one of the most energyintensive critical infrastructures. This paper proposes a framework for day‐ahead operation optimization and coordination of the interconnected Joint Power and Water Networks (JPWNs). Unlike the state‐of‐the‐art where PWNs are individually operated in their respective domains, we present an integrated framework for PWNs that conjoins the Optimal Power Flow (OPF) mechanisms in power grids with innovative operation models of the water networks. Piece‐wise linearization is applied to the nonlinear hydraulic operating constraints to convert the proposed optimization model into a mixed‐integer linear programming (MILP) formulation. The suggested framework is applied to a 15‐node water network jointly operated with the IEEE 9‐bus and IEEE 57‐bus test power systems. The simulation results show the effectiveness of the proposed framework, resulting in cost reduction and energy‐saving when both systems’ operation is jointly optimized. The results show that the proposed methodology is scalable and computationally‐efficient when applied to larger‐scale systems.

Organic-waste-derived butyric acid-to-biodiesel supply-chain network: Strategic planning design using a deterministic snapshot model

Capital and total cost targets for mass exchange networks: Part 1: Simple capital cost models

Optimal design of inter-plant hydrogen networks with intermediate headers of purity and pressure

Virtual network functions (VNFs) are placed across the network to complete the required network performance of virtual network slice (vNS), and the placement of VNFs is flexible and problematic. Besides, a VNF can be decomposed into multiple sub-functions, and the same type of sub-function can be re-used by multiple VNFs. Therefore, the resources of subfunctions in different vNS requests can be shared and the cost of the substrate network is reduced. So, function decomposition makes the VNF placement problem more flexible and challenging. In this paper, we study the VNF placement problem with function decomposition for vNS, and formulate it as an integer linear programming (ILP) aiming to minimize the total cost of the substrate network. Then, an approach named Placement algorithm based on Function Decomposition (P-FD) is proposed to get a near-optimal solution of this problem. Finally, simulation results show that P-FD can achieve less total cost compared with algorithms in existing.

We propose a comprehensive scalable algorithm simultaneously assessing the routing, scheduling and virtualization in Time-Domain Wavelength Interleaved Network (TWIN). TWIN is an energy-efficient optical burst switching technology for metropolitan area and data center intra- and interconnections, with destinations using separate allocated sets of wavelengths for the reception. Given the costs of the optical transponders and the wavelength use per km of fiber length, the proposed algorithm solves the routing and wavelength assignment problem, and in the same time allocates the time slots to traffic flows (performs the slot scheduling), so that the total network cost is minimized. The algorithm also enables the construction of overlayed virtual networking domains at minimum cost, which share the transponders and network links, and can employ different scheduling policies. The performance of the algorithm is compared with the pre-existing optimal dimensioning solution for single virtualization domain based on Integer Linear Programing, for different scenarios. The obtained results show that the network cost is within 27% of the optimal.

In integration of IP and WDM networks, there are two main approaches. One is joint planning approach; the other is joint operation approach. Joint planning typically addresses an optimality problem on total network cost given a certain data traffic pattern and some physical constraints at the network planning stage; while through reconfiguration or real-time setup of lightpaths, joint operation focuses on optimizing network performance or guaranteeing it to a defined level under current network configuration and dynamic data traffic pattern at the network operational stage. On contrary to the (semi-) static virtual topology in joint planning, the joint operation approach maintains a dynamic virtual topology. We propose an integration network model with separated control plane and data plane. Formulations have been studied in building the model, and the initial findings may help in designing the routing and signaling protocols.

This paper deals with the minimization of the total system cost in the PCS network using CDMA cellular system standard. The total system cost includes the installation costs of base stations (BS), base station controllers (BSC) and PCS exchanges (PCX), the weighted-distance connection costs between BS and BSC and between BSC and PCX and the hard handoff cost. Our objective is to keep each of these costs at a minimum with guaranteed service performance. However, there exists a tradeoff property between these costs. Therefore, we use an efficient and effective searching technique, hierarchical genetic algorithms (HGA), which has the ability to handle multiobjective functions and various constraints and find multiple different solutions for decision making.

Robust multimodal hub network design for hazmat considering a detour strategy

Optimal design of the second and third generation biofuel supply network by a multi-objective model

Recently, a lot of renewable energy sources have been integrated into the distribution network. In consideration of economy and construction feasibility, some renewable energy sources are required to be installed in specific areas. In this paper, a bi-layer distribution network planning optimization model that considers the geographical restrictions of the installation locations of the substation, pumped storage plant, photovoltaic (PV) and wind power, as well as the impact of operation on planning, is proposed. In the planning optimization layer, the optimal distribution network topology with minimal total cost is obtained. The locations of the renewable energy sources and the substation are determined by the particle swarm optimization (PSO), and then all the components are interconnected using the dynamic minimum spanning tree (DMST) method. In the operation optimization layer, the economic operation strategy of the hybrid energy system with uncertainty is obtained by the scenario-based stochastic optimal power flow (OPF). The forecast error of the uncertain variable is represented by the probability distribution function, and the roulette wheel mechanism (RWM) is used to generate the stochastic scenarios. A modified 103-bus system is used to test the effectiveness of the proposed method, and the simulation results show that the proposed method can effectively reduce the total cost of the distribution network.

Vehicular Networking is of immense importance and continuous research is going on in this field for building the Intelligent Transportation System (ITS). Vehicular ad hoc networks (VANET) are distributed, self-organizing communication networks which progressed from traveling vehicles. Therefore VANET's are characterized by very high speed of vehicles and limited degree of freedom in vehicles movement pattern. VANETs are infrastructure less which allows communication between vehicles without any type of configuration and any worthy cellular networks. Mobility Management for VANET is a challenging task because of the fast mobility of the vehicles. The main goal of VANET is to improve road traffic safety and to efficiently achieve intelligent intervehicle communications. In this paper, the scalability and efficiency of mobility management protocol MMIP6 has been further enhanced to accommodate more number of vehicles with reduction in total cost of the entire network. Numerical analysis has been carried out for comparing the total communication cost of enhanced MMIP6 with Network Mobility protocol (NEMO) of VANET.