An integrated reservoir operation framework for enhanced water resources planning
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ABSTRACT:
SUBMITTER: Dash S
PROVIDER: S-EPMC10709336 | biostudies-literature | 2023 Jan
REPOSITORIES: biostudies-literature
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Project description:Reservoir-operation optimisation is a crucial aspect of water-resource development and sustainable water process management. This study addresses bi-objective optimisation problems by proposing a novel crossover evolution operator, known as the hybrid simulated binary and improved arithmetic crossover (SBAX) operator, based on the simulated binary cross (SBX) and arithmetic crossover operators, and applies it to the Non-dominated Sorting Genetic Algorithms-II (NSGA-II) algorithm to improve the algorithm. In particular, the arithmetic crossover operator can obtain an optimal solution more precisely within the solution space, whereas the SBX operator can explore a broader range of potential high-quality solutions. Considering the advantages of both operators, this study introduces an improved arithmetic operator to reduce the risk of local convergence inherent in conventional arithmetic operators. Subsequently, two strategies for the SBAX operator are discussed: SBX operator + new arithmetic operator and new arithmetic operator + SBX operator. The convergence of the bi-objective Pareto solution set is evaluated based on the generation and inverted generational distances. This method is used for the collaborative optimisation of the water supply and ecological operation of the Fenhe Reservoir, where its effectiveness is demonstrated. A comparative analysis of the bi-objective optimisation schemes obtained using different crossover operators indicates the following: (1) the NSGA-II algorithm based on the SBAX operator achieves a convergence efficiency that is 14.25-41.95% higher than that of the conventional NSGA-II algorithm; (2) the reservoir operation indices of the scheduling scheme derived from the NSGA-II algorithm based on the SBAX operator significantly outperform those obtained using the conventional NSGA-II algorithm. The optimal strategy reduces the annual average water abandonment by 11.2-14.52 million m3. This study provides a novel approach for bi-objective optimisation and sustainable reservoir management.
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Project description:A novel newsvendor model-based framework for regional industrial water resources allocation that considers uncertainties in water supply and demand was proposed in this study. This framework generates optimal water allocation schemes while minimizing total costs. The total cost of water allocation consists of the allocated water cost, the opportunity loss for not meeting water demand, and the loss of the penalty for exceeding water demand. The uncertainties in water demand and supply are expressed by cumulative distribution functions. The optimal water allocation for each water use sector is determined by the water price, the unit loss of the penalty and opportunity loss, and the cumulative distribution functions. The model was then applied to monthly water allocation for domestic, industrial, and agricultural water use in two counties of Huizhou City, China, whose water supply mainly depends on Baipenzhu Reservoir. The water demand for each water use sector and the monthly reservoir inflow showed good fits with the uniform and P-III distributions, respectively. The water demand satisfied ratio for each water use sector was stable and increased for the optimal water allocation scheme from the newsvendor model-based framework, and the costs were lower compared with the actual water allocation scheme. The novel framework is characterized by less severe water shortages, lower costs, and greater similarity to actual water use compared with the traditional deterministic multi-objective analysis model, and demonstrates strong robustness in the advantages of lower released surplus water and higher water demand satisfied ratio. This novel framework yields the optimal water allocation for each water use sector by integrating the properties of the market (i.e., determining the opportunity loss for not meeting water demand) with the government (i.e., determining the water price and the loss of the penalty for exceeding water demand) under the strictest water resources management systems.
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Project description:The development of a commercial fusion power plant presents a unique set of challenges associated with the complexity of the systems, the integration of novel technologies, the likely diversity and distribution of the organizations involved, and the scale of resources required. These challenges are reviewed and compared to those for other complex engineering systems. A framework for creating a digital environment that integrates research, test, design and operational data is discussed and is based on combining the integrated nuclear digital environment (INDE), proposed recently for nuclear fission power plants, with the hierarchical pyramid of test and simulation used in the aerospace industry. The framework offers the opportunity to plan modelling strategies that allow large design domains to be explored prior to optimizing a detailed design for construction; and in this context, the relationship between measurements and predictions are explored. The use of the framework to guide the socio-technical activity associated with a distributed and collaborative design process is discussed together with its potential benefits and the technology gaps that need to be addressed in order to realize them. These benefits include shorter development times, reduced costs and improvements in credibility, operability, reliability and safety.
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Project description:BackgroundThe aim of this study was to demonstrate the application of a needs-based mental health service planning model in Tasmania, Australia to identify indicative directions for future service development that ensure the equitable provision of mental health services across the State.MethodsThe activity and capacity of Tasmania's 2018-19 mental health services were compared to estimates of required care by: (1) generating estimates of required care using the National Mental Health Service Planning Framework (NMHSPF); (2) collating administrative mental health services data; (3) aligning administrative data to the NMHSPF; and (4) comparing aligned administrative data and NMHSPF estimates to identify priority areas for service development. Findings were contextualised using information about service location, population demographics, and upcoming service development.ResultsBed-based services capacity reached 85% of the NMHSPF estimate. However, access to certain bed types was inequitable across regional areas. Access to jurisdictional clinical ambulatory team-based services was lowest in the South, while overall full-time equivalent staff capacity reached 58% of the NMHSPF estimate. Access to Primary Health Tasmania (PHT) primary care services was highest in the North West; access to Medicare services was highest in the South. Collectively, activity across primary care (PHT, headspace and Medicare) reached 43% of the NMHSPF estimate. Over half of Community Managed Mental Health Support Services were state-wide services.ConclusionsThis study demonstrates the application of a needs-based planning model for mental health services. Findings revealed service priority areas across Tasmania and highlight considerations for needs-based planning.
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