Watershed Spatial Integration and System Optimisation Based on the Overall Development Model of Landscape System

Urban green space (UGS) is important in urban systems, as it benefits economic development, ecological conservation, and living conditions. Many studies have evaluated the economic, ecological, and social value of UGS worldwide, and spatial optimization for UGS has been carried out to maximize its value. However, few studies have simultaneously examined these three values of UGS in one optimization system. To fill this gap, this study evaluated the economic value of UGS in terms of promoting housing prices, its ecological value through the relief of high land surface temperature (LST), and its social value through the provision of recreation spaces for residents within a 255 m distance. Subsequently, these three values were set as objectives in a genetic algorithm (GA)-based multi-objective optimization (MOP) system. Shenzhen was taken as the case study area. The results showed that the influencing distance of UGS in Shenzhen for house prices was 345 m, and the influencing distance of UGS for LST was 135 m. Using MOP, the Pareto solutions for increasing UGS were identified and presented. The results indicate that MOP can simultaneously optimize UGS’s economic, ecological, and social value.

There is still lack of effective modelling, simulation and optimisation methods for complex electromechanical system. In this paper, the dynamics model of the PMSM-precision reducer system is established using Lagrange-Maxwell equation. The simulation model and optimisation model of this system are set up with Modelica language. The simulation and optimisation of the system are realised in Dymola and JModelica.org platforms respectively. Simulation results show that the dynamics model of the system is correct. Optimisation results show that the system can quickly respond to the given speed and loads. The proposed modelling, simulation and optimisation method based on Modelica may be commonly applied to other complex electromechanical systems.

Study of Optimization Method for Electromechanical Integration Design

Consideration of the social values people assign to relatively undisturbed native ecosystems is critical for the success of science-based conservation plans. We used an interview process to identify and map social values assigned to 31 ecosystem services provided by natural areas in an agricultural landscape in southern Australia. We then modeled the spatial distribution of 12 components of ecological value commonly used in setting spatial conservation priorities. We used the analytical hierarchy process to weight these components and used multiattribute utility theory to combine them into a single spatial layer of ecological value. Social values assigned to natural areas were negatively correlated with ecological values overall, but were positively correlated with some components of ecological value. In terms of the spatial distribution of values, people valued protected areas, whereas those natural areas underrepresented in the reserve system were of higher ecological value. The habitats of threatened animal species were assigned both high ecological value and high social value. Only small areas were assigned both high ecological value and high social value in the study area, whereas large areas of high ecological value were of low social value, and vice versa. We used the assigned ecological and social values to identify different conservation strategies (e.g., information sharing, community engagement, incentive payments) that may be effective for specific areas. We suggest that consideration of both ecological and social values in selection of conservation strategies can enhance the success of science-based conservation planning.

With the new challenges brought by the high penetration of Renewable Energy Resources (RESs) into the modern grid, developing new solutions and concepts are necessary. Microgrid (MG) is one of the new concepts introduced to overcome upcoming issues in the modern electricity grids. MGs and Multi-Microgrids (MMGs) are defined as the building blocks of smart grids. MGs are the small units, where power generation and consumption happen at the same location and MG makes the decisions by itself. MGs can operate grid-connected or island mode depending on the functionality of the MG. Energy Management System (EMS) is the decision making centre of the MG. The data from the devices is received by the EMS and after processing, the commands are sent to the controllable components. Management of voltage, active and reactive power, neutral current, unit commitment and economic dispatch are of the tasks of EMS. In this PhD thesis, an optimal EMS for MGs and MMGs is developed. The main objective of this project by developing the EMS is to optimize the energy flow in the MGs and MMGs to obtain peak load shaving in a cost beneficial system. In order to achieve an efficient EMS, communication system, forecasting system, scheduling system, and optimization system are modelled and developed. Different types of EMS operation, centralized, decentralized and distributed, are investigated in this work to achieve the best combination for MMG EMS operation. The communication system is mainly utilizing Modbus TCP/IP protocol for data transmission at local level and Internet of Things (IoT) protocols (MQTT) for the global communication level. A communication operation algorithm is proposed to manage the MMG EMS under different communication operation modes and communication failure conditions. Furthermore, a monitoring system is developed to collect the data from different devices in the MG. The data is processed in the MG EMS and the commands are sent to components through the communication infrastructure. The link between MGs and MMGs is through the proposed two-level communication system, where the expansion of MGs to a MMG is investigated. In the MMG, MGs are functioning as a unit while having different priorities and operating under different policies. Each MG has its own MG EMS and the EMSs transfer information through the communication system between each other in either centralized, decentralized, distributed, or no communication modes under the MMG EMS. The forecasting system is required in the EMS to predict the future MG characteristics such as power generation and consumption. The forecasted data is the input to the optimization and scheduling system of EMS. Employing the forecasting system in the EMS would increase the accuracy of the optimization and scheduling systems. In this thesis, the timeseries-based forecasting algorithms are employed to predict next day’s active power using the load data, generation data, weather data and temperature data as the inputs. The heart of EMS is the scheduling and optimization system. The purpose of the scheduling system is to define the amount and the time of energy flow in the MG for different generation sources and consumption loads. Furthermore, scheduling system is responsible for peak load shaving and valley filling. On the other hand, the optimization system has the task of minimizing the operation costs of the MGs. The role of market in the scheduling and optimization is important. Time of Use (ToU) tariff is the pricing system, which determines the peak and off peak hours for energy usage pricing. In order to apply the optimization system, a model of the system, an objective function and systems constraints are defined, where aging of battery energy storage system (BESS), operational cost of components and MG cost benefits are considered. To operate the EMS scheduling and optimization system, IBM CPLEX Optimization Studio solver conducts the optimization while for the scheduling system, objective function and constraints are defined in MATLAB. In this thesis, a rule-based, MILP and MIQP optimization system for commercial MGs including electric vehicles (EVs) are proposed to investigate performance of MG EMS for different case studies. In this thesis, the literature for different scheduling and forecasting systems is investigated and different optimization algorithms are analysed. The communication protocols utilized in this research are described and compared to other protocols in the literature. In different chapters of this thesis, the modelling of MGs and MMG EMS, different modules of EMS, forecasting, optimization, scheduling and communication systems are described and analysed. A novel communication system for MMG EMS operation is proposed for commercial buildings. The performance of MG EMS and MMG EMS is examined for power and neutral current sharing, operation cost optimization, and demand peak shaving applications and results are compared to investigate the performance of proposed algorithms.

The shortage of data is one of the most important problems in system modeling and optimization in industrial applications. Typical modeling techniques are unable to properly model a system with a limited dataset. In this paper, a modeling method for optimization of these systems is proposed. The proposed method has two main steps. In the first step, the model is employed to generate data using neural network. This model determines the correspondence input of each output. In the second step, optimization of the generated model is performed using genetic algorithm. Inputs leading to the specified output can be estimated using the proposed system. Optimality of the system can be explained by an evaluation function. The proposed method was evaluated in two different experiments on a time series and a real data. Results of the experiments were analyzed using mean square error. The experimental results show the capability of the proposed method in system modeling and optimization.

Purpose Opportunistic maintenance (OM) policy is a prospective maintenance approach that instigates for a more effective and optimized system. The purpose of this paper is to provide the steps and methods used in model development processes for the application of the OM policy. Design/methodology/approach Dubbed as opportunistic principle toward optimal maintenance system (OPTOMS) for OM policy toward optimal maintenance system, the model is devised as a decision support system model and contains five phases. The motivation and focus of the model resolve around the need for a practical framework or model of maintenance policy for the application in an industry. In this paper, the OPTOMS model was verified and validated to ensure that the model is applicable in the industry and robust as a support system in decision making for the optimal maintenance system. Findings From the verification steps conducted in a case study company, it was found that the developed model incorporated simple but practical tools like check sheet, failure mode and effect analysis (FMEA), control chart that has been commonly used in the industry. Practical implications This paper provides the general explanations of the developed model and tools used for each phase in implementing OM to achieve an optimal maintenance system. Based on a case study conducted in a semiconductor company, the OPTOMS model can align and prepare the company in increasing machine reliability by reducing machine downtime. Originality/value The novelty of this paper is based on the in-depth discussion of all phases and steps in the model that emphasize on how the model will become practical theories in conducting an OM policy in a company. The proposed methods and tools for data collection and analysis are practical and commonly used in the industry. The framework is designed for practical application in the industry. The users would be from the Maintenance and Production Department.

System architecture could be described clearly and unambiguously by a descriptive system model during the system-level design of mechatronic products. However, for system verification, it is necessary to integrate the system modeling tools and simulation tools for analysis. Most of the existing integration methods focus on the integration in the physical architecture phase of the system model. A model integration framework that can integrate simulation into the logical architecture phase of the entire model for synchronous model verification is proposed in this paper. In the integration process, a Model-to-Text method is employed for information extraction and model transformation from the SysML model to the simulation model. The system model can be transformed by reusing and updating the generated simulation model through the framework for model verification. A framework with the Simulink model as the transformation target is constructed as an example in this paper, and the capability of this framework is verified by a design process of a quadruped robot. The result shows that this framework can realize the system design paradigm of integrating system verification for the entire logical architecture, which can improve the design efficiency and provide a reference for other system design and integration work.

Urban green spaces (UGSs) deliver vital ecological and social benefits, and their integrated management significantly contributes to ecological sustainability and public well-being. However, existing studies tend to separately examine ecological and social values of various UGS types, lacking comprehensive assessments of their interactions. In response, this study established an integrated biotope classification system based on vegetation structure and conducted extensive field surveys to map urban biotopes in Xi'an city. Ecological values were evaluated through twelve selected indicators, including biodiversity, air quality regulation, and carbon storage. Social values were assessed using the SolVES model across six dimensions: aesthetics, recreation, cultural , spiritual, biodiversity, and therapeutics. The coupling coordination degree (CCD) between ecological and social values was subsequently calculated, and key influencing factors were analyzed via Geodetector. The results reveal that: (1) Xi'an encompasses 28 distinct biotope types, with green spaces occupying the largest area (2.89 km2; 79.97%) and blue spaces the smallest (0.32 km2; 8.72%). (2) The CCD between ecological and social values is on the verge of disorder(0.467), indicating a critical need for improved coordination. (3) Open green spaces with herbaceous vegetation (G O He) exhibit the highest CCD. Conversely, closed one-layer broad-leaved forests primarily covered by hardscape (G C Ha B L-1) and closed multi-layer broad-leaved forests primarily covered by hardscape (G C Ha B L-2) present the lowest coordination levels. (4) Ecological characteristics significantly influence CCD, highlighting the importance of detailed biotope classification. The results emphasize that enhancing spatial configurations and optimizing functional arrangements within UGSs are essential strategies for improving eco-social synergies and coupling coordination. This study provides valuable insights and practical recommendations for targeted urban planning and sustainable development of urban green infrastructure in Xi'an and similar rapidly urbanizing regions.

Three approaches for assessing non-market values (direct linkage models, revealed preference and stated preference models) are reviewed with respect to their ability to capture ecological value. An alternative biophysical approach, namely energy analysis, is also considered. The review suggests that it may be possible to measure ecological value using the contingent valuation method. The role of information in preference formation and willingness to pay bids is then investigated along with a number of other issues that need to be resolved before using the contingent valuation method. The wetlands of the case study area, Moreton Bay, Australia exhibit both ecological and economic values. The wetlands contribute approximately one-third of primary productivity in the Bay, provide habitat for a wide range of dependent species (including internationally recognised migratory wader birds) and have a diverse fauna with a relatively large number of endemic species. Economic values of the wetlands include both direct and indirect use values (for example, fishing, recreation, water quality improvements and storm buffering) and non-use values. Non-use values include the value in preserving the environment for future generations (bequest value) and the existence of vulnerable animals such as turtles and dugongs, which one may never expect to see. If consumers are willing to pay to preserve these animals, this is also a valid economic value. The economic technique of contingent valuation is tested to determine if it is possible to capture ecological value by providing respondents, selected by random sample, to a survey with the relevant information. A case study is undertaken in Moreton Bay to determine respondents' willingness to pay to improve water quality and hence protect the wetlands. To test the effects of differing types information, four different versions of the survey were sent to four groups of 500 respondents. Case A provided no extra information so it could be used as a control. Case B included information about the ecological values of the wetlands of Moreton Bay. Case C provided information about the economic use values of the wetlands in the Bay including direct and indirect use. Case D provided information about the non-use values of endangered species resident in the Bay that are dependent on the wetlands. The results indicate that the provision of different types of information influences willingness to pay. However, willingness to pay when provided with ecological information is not significantly different from willingness to pay when provided with other information. As it was not possible from the research undertaken to state that the contingent valuation method can capture ecological value, an alternative approach is proposed to link ecological and economic values. It is argued that ecologists and economists need to develop common aims and scales of assessment. Further, communication between the two disciplines can be enhanced through the use of agreed indicator terms. Through an iterative approach it should then be possible to understand the linkages between changes in indicators of ecosystem values and indicators of economic value.

Evaluation of natural computation techniques in the modelling and optimization of a sequential injection flow system for colorimetric iron(III) determination

CHAPTER TEN - Optimization of seawater desalination systems

To enhance the efficiency of system modeling and optimization in the conceptual design stage of satellite parameters, a system modeling and optimization method based on System Modeling Language and Co-evolutionary Algorithm is proposed. At first, the objectives of satellite mission and optimization problems are clarified, and a design matrix of discipline structure is constructed to process the coupling relationship of design variables and constraints of the orbit, payload, power and quality disciplines. In order to solve the problem of increasing non-linearity and coupling between these disciplines while using a standard collaborative optimization algorithm, an improved genetic algorithm is proposed and applied to system-level and discipline-level models. Finally, the CO model of satellite parameters is solved through the collaborative simulation of Cameo Systems Modeler (CSM) and MATLAB. The result obtained shows that the method proposed in this paper for the conceptual design phase of satellite parameters is efficient and feasible. It can shorten the project cycle effectively and additionally provide a reference for the optimal design of other complex projects.

The optimal allocation of land resources is a reliable guarantee for sustainable land use. As one of the least developed countries in the world with rich land resources, Laos needs scientific, reasonable and efficient use of land resources to promote the comprehensive development of economy and society. Considering that the spatial distribution of land resources is extremely uneven and the land use planning experiences are limited in Laos, a multi-scale optimal allocation method system is proposed, including the multi-scale suitability evaluation method, the multi-scale quantitative structure optimization method, and the multi-scale spatial layout optimization method. Savan District in Laos was selected as the study area. Mobile mapping technology (MMT), location-based service (LBS), remote sensing (RS), and geographic information system (GIS) methods were used in combination for data acquisition and processing under the lack of information condition. Delphi, principal component analysis (PCA), and analytic hierarchy process (AHP) methods were integrated to a set of process for suitability evaluation. Linear programming (LP), multi-objective optimization, and operational research (OR) methods were pooled for quantitative structure optimization. Logistic regression model, cellular automaton (CA) method, and CLUE-S model were used together for spatial layout optimization. Results indicate that the multi-scale optimization method can make good use of the advantages of controling land use orientation at macro scale and maintaining data precision at micro scale. Land resources were allocated more efficiently and reasonably by using this method. This method may provide data reference for the “Belt and Road” initiative, and shed light on relative academic issues of land use in future studies.

An integrated accounting system of quantity, quality and value for assessing cultivated land resource assets: A case study in Xinjiang, China