An Application of the Harmony-Search Multi-Objective (HSMO) Optimization Algorithm for the Solution of Pump Scheduling Problem☆

Abstract In hydraulic systems, water is often pumped to reach higher elevations, so as to ensure the minimum required pressure and guarantee adequate service level. However, pumps cannot be instantly activated and people do not consume the resource in uniform mode throughout the day. To avoid direct pumping, water can be stored in tanks at a higher elevation, so that it can be supplied whenever there is a higher demand. Because of the significant costs required for pumping, energy-saving in water supply systems is one of the most challenging issues to ensure optimal management of water systems. Careful scheduling of pumping operations may lead not only to energy savings, but alsoto prevent damages, as consequence of reduction of operation times and switches. By means of computer simulation, an optimal schedule of pumps can be achieved using optimization algorithms. In this paper, a harmony-search multi-objective (HSMO) optimization approach is adapted to the pump scheduling problem. The model interfaces with the popular hydraulic solver, EPANET 2.0, to check the hydraulic constraints and to evaluate the performances of the selected schedules. Penalties are introduced in the objective function in case of violation of the hydraulic constraints. The model is applied to a case study, showing that the results are comparable with those of competitive meta-heuristic algorithms (e.g. Genetic Algorithms) and pointing out the suitability of the HSMO algorithm for pumping optimization

Multi-objective optimization of an industrial styrene reactor using Harmony Search Algorithm

Multi-objective optimization of industrial styrene reactor is done using Harmony Search algorithm. Harmony search algorithm is a recently developed meta-heuristic algorithm which is inspired by musical improvisation process aimed towards obtaining the best harmony. Three objective functions – productivity, selectivity and yield are optimized to get best combination of decision variables for styrene reactor. All possible cases of single and multi-objective optimization have been considered. Pareto optimal sets are obtained as a result of the optimization study. Results reveal that optimized solution using harmony search algorithm gives better operating conditions than industrial practice

Simulation-based coyote optimization algorithm to determine gains of PI controller for enhancing the performance of solar PV water-pumping system

In this study, a simulation-based coyote optimization algorithm (COA) to identify the gains of PI to ameliorate the water-pumping system performance fed from the photovoltaic system is presented. The aim is to develop a stand-alone water-pumping system powered by solar energy, i.e., without the need of electric power from the utility grid. The voltage of the DC bus was adopted as a good candidate to guarantee the extraction of the maximum power under partial shading conditions. In such a system, two proportional-integral (PI) controllers, at least, are necessary. The adjustment of (Proportional-Integral) controllers are always carried out by classical and tiresome trials and errors techniques which becomes a hard task and time-consuming. In order to overcome this problem, an optimization problem was reformulated and modeled under functional time-domain constraints, aiming at tuning these decision variables. For achieving the desired operational characteristics of the PV water-pumping system for both rotor speed and DC-link voltage, simultaneously, the proposed COA algorithm is adopted. It is carried out through resolving a multiobjective optimization problem employing the weighted-sum technique. Inspired on theCanis latransspecies, the COA algorithm is successfully investigated to resolve such a problem by taking into account some constraints in terms of time-domain performance as well as producing the maximum power from the photovoltaic generation system. To assess the efficiency of the suggested COA method, the classical Ziegler-Nichols and trial-error tuning methods for the DC-link voltage and rotor speed dynamics, were compared. The main outcomes ensured the effectiveness and superiority of the COA algorithm. Compared to the other reported techniques, it is superior in terms of convergence rapidity and solution qualities

Energy Optimization Using a Pump Scheduling Tool in Water Distribution Systems

Water distribution management system is a costly practice and with the growth of population, the needs for creating more cost-effective solutions are vital. This paper presents a tool for optimization of pump operation in water systems. The pump scheduling tool (PST) is a fully dynamic tool that can handle four different types of fixed speed pump schedule representations (on and off, time control, time-length control, and simple control [water levels in tanks]). The PST has been developed using Visual Basic programming language and has a linkage between the EPANET hydraulic solver with the GANetXL optimization algorithm. It has a user-friendly interface which allows the simulation of water systems based on (1) a hydraulic model (EPANET) input file, (2) an interactive interface which can be modified by the user, and (3) a pump operation schedule generated by the optimization algorithm. It also has the interface of dynamic results which automatically visualizes generated solutions. The capabilities of the PST have been demonstrated by application to two real case studies, Anytown water distribution system (WDS) and Richmond WDS as a real one in the United Kingdom. The results show that PST is able to generate high-quality practical solutions

Comparison Of HSRNAFold and RNAFold Algorithms for RNA Secondary Structure Prediction.

Ribonucleic Acid (RNA) has important structural and functional roles in the cell and plays roles in many stages of protein synthesis. The structure of RNA largely determines its function

Novel Light Coupling Systems Devised Using a Harmony Search Algorithm Approach

We report a critical assessment of the use of an Inverse Design (ID) approach steamed by an improved Harmony Search (IHS) algorithm for enhancing light coupling to densely integrated photonic integratic circuits (PICs) using novel grating structures. Grating couplers, performing as a very attractive vertical coupling scheme for standard silicon nano waveguides are nowadays a custom component in almost every PIC. Nevertheless, their efficiency can be highly enhanced by using our ID methodology that can deal simultaneously with many physical and geometrical parameters. Moreover, this method paves the way for designing more sophisticated non-uniform gratings, which not only match the coupling efficiency of conventional periodic corrugated waveguides, but also allow to devise more complex components such as wavelength or polarization splitters, just to cite some

Pump Scheduling for Optimised Energy Cost and Water Quality in Water Distribution Networks

Delivering water to customers in sufficient quantity and quality and at low cost is the main driver for many water utilities around the world. One way of working toward this goal is to optimize the operation of a water distribution system. This means scheduling the operation of pumps in a way that results in minimal cost of energy used. It is not an easy process due to nonlinearity of hydraulic system response to different schedules and complexity of water networks in general. This thesis reviewed over 250 papers about pump scheduling published in the last 5 decades. The review revealed that, despite a lot of good work done in the past, the existing pump scheduling methods have several drawbacks revolving mainly around the ability to find globally optimal pump schedules and in a computationally efficient manner whilst dealing with water quality and other complexities of large pipe networks. A new pump scheduling method, entitled iterative Extended Lexicographic Goal Programming (iELGP) method, is developed and presented in this thesis with aim to overcome above drawbacks. The pump scheduling problem is formulated and solved as an optimisation problem with objectives being the electricity cost and the water age (used as a surrogate for water quality). The developed pump scheduling method is general and can be applied to any water distribution network configuration. Moreover, the new method can optimize the operation of fixed and variable speed pumps. The new method was tested on three different case studies. Each case study has different topography, demand patterns, number of pumps and number of tanks. The objective in the first and second case studies is to minimise energy cost only, whereas in the third case study, energy cost and water age are minimized simultaneously. The results obtained by using the new method are compared with results obtained from other pump scheduling methods that were applied to the same case studies. The results obtained demonstrate that the iELGP method is capable of determining optimal, low cost pump schedules whilst trading-off energy costs and water quality. The optimal schedules can be generated in a computationally very efficient manner. Given this, the iELGP method has potential to be applied in real-time scheduling of pumps in larger water distribution networks and without the need to simplify the respective hydraulic models or replace these with surrogate models

Lost in optimisation of water distribution systems? A literature review of system operation

This is the author accepted manuscript. The final version is available from Elsevier via the DOI in this record.Optimisation of the operation of water distribution systems has been an active research field for almost half a century. It has focused mainly on optimal pump operation to minimise pumping costs and optimal water quality management to ensure that standards at customer nodes are met. This paper provides a systematic review by bringing together over two hundred publications from the past three decades, which are relevant to operational optimisation of water distribution systems, particularly optimal pump operation, valve control and system operation for water quality purposes of both urban drinking and regional multiquality water distribution systems. Uniquely, it also contains substantial and thorough information for over one hundred publications in a tabular form, which lists optimisation models inclusive of objectives, constraints, decision variables, solution methodologies used and other details. Research challenges in terms of simulation models, optimisation model formulation, selection of optimisation method and postprocessing needs have also been identified

Probabilistic Reliability Analysis of the Water-energy Nexus Using Monte Carlo Simulation

Nowadays, with the development of science and technologies, our modern society is more and more dependent on the reliable performance of the critical infrastructures. Both water systems and power systems are national critical infrastructure supporting our daily life and the development of economic growth. These two types of systems are highly interconnected and complex networks, which consist of various system elements. Similarly, the core function of water and power system is to deliver satisfactory quality water and power to consumers, and at the same time it should satisfy all the demands at all load points. The reliable performance of these critical infrastructure is becoming more and more important. Therefore, it is very urgent to develop a comprehensive reliability evaluation algorithm to quantify the reliability of these critical systems. When it comes to quantitatively assessing reliability of the facility infrastructure, there is a need to develop a comprehensive method to consider a comprehensive set of variables and uncertainties such as the random failures of mechanical components, the amount of water demands, the power supply reliability, maintenance scheduling, and so forth. The rapidly growing urban population is also a great challenge to the aging drinking water distribution networks. The water facilities are aging and in need of expensive repairs. Therefore, this thesis will aid in making informed decisions on infrastructure repair, maintenance, and staffing planning when the available budgets are limited. This thesis proposes a probabilistic reliability evaluation methodology for water distribution systems considering the impact of power supply reliability based on the sequential Monte Carlo simulation (MCS), which can guide cost-effective preventative measures before system failures. A previously developed C++ software tool is used to help perform the simulation. The probabilistic reliability assessment algorithm can be appropriately applied for both the electric power systems and water distribution system is due to the similar stochastic system nature and modeling manner of the system elements. First, the reliability characteristic of each system component in electric power system can be modeled by a two-state model (i.e., up state and down state). Then, the probability of failure for each component can be calculated and a chronological operating sequence can be further determined based on the sequential Monte Carlo Simulation. Likewise, the reliability models for the water distribution system components can be represented using this method. All these similarities result in the similar reliability assessment procedure. The commonly used deterministic criteria in industrial circles lacked the ability to model and quantify the stochastic nature of system behaviors such as the mechanical failure of system elements. Besides the uncertainties come from water distribution system itself, power supply may also affect the performance of the water distribution network and system reliability. Therefore, the two systems are interactive and physically connected. The purpose of this study is to develop a suitable algorithm to evaluate the water sector and power system as an integrated Water-Energy Nexus (WEN) system. This thesis proposes an integrated, probabilistic reliability evaluation method for the WEN model based on the sequential Monte Carlo Simulation. In the proposed evaluation procedure, both mechanical failures and hydraulic analysis are taken into consideration. Case studies are performed base on a representative water-energy nexus system to demonstrate the effectiveness of the proposed algorithm. The simulation results demonstrate that the proposed probabilistic methodology is appropriate to integrated quantitative reliability modeling and assessment of coupled critical infrastructures (i.e., electrical power networks and water distribution networks) by incorporating the emerging smart grid technologies such as electrical microgrids