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Power-System Flexibility: A Necessary Complement to Variable Renewable Energy Optimal Capacity Configuration

ENERGIES 2023年第21期16卷 7432-7432页

作者： Juma, Denis Munda, Josiah Kabiri, Charles Univ Rwanda Coll Sci & Technol African Ctr Excellence Energy Sustainable Dev KN 67 St NyarugengePOB 3900 Kigali Rwanda Tshwane Univ Technol Dept Elect Engn X680-0001 Pretoria South Africa

Comprehending the spatiotemporal complementarity of variable renewable energy (VRE) sources and their supplemental ability to meet electricity demand is a promising move towards broadening their share in the power supply mix without sacrificing either supply security or overall cost efficiency of power system operation. Increasing VRE share into the energy mix has to be followed with measures to manage technical challenges associated with grid operations. Most sub-Saharan countries can be considered 'greenfield' due to their relatively low power generation baseline and are more likely to be advantaged in planning their future grids around the idea of integrating high VRE sources into the grid from the outset. An essential measure for achieving this objective entails exploring the possibility of integrating renewable hybrid power plants into the existing hydropower grid, leveraging on existing synergies and benefiting from the use of existing infrastructure and grid connection points. This study evaluates the potential for hybridizing existing hydropower-dominated networks to accommodate solar- and wind-energy sources. The existing synergy is quantified using correlation and energy indicators by evaluating complementarity at daily, monthly and annual intervals. The proposed metric serves as a tool to improve planning on increasing the VRE fraction into the existing systems with the aim to achieve optimal power mixes. In comparison to cases in which the same kind of resource is over-planted while expanding installed capacity, the results demonstrate that wind and solar resources hold a positive degree of complementarity, allowing a greater share of VRE sources into the grid. The study shows that Kenya bears favorable climatic conditions that allow hybrid power plant concepts to be widely explored and scaled up on a large and efficient scale. The results can be applicable in other regions and represent an important contribution to promoting the integration of VRE sourc

关键词： variable renewable energy sources complementarity compromise programming grid integration power system flexibility

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Statistical downscaling of sea levels: application of multi-criteria analysis for selection of global climate models

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ENVIRONMENTAL MONITORING AND ASSESSMENT 2022年第10期194卷 764-764页

作者： Sithara, S. Pramada, S. K. Thampi, Santosh G. Natl Inst Technol Calicut Dept Civil Engn Kozhikode 673601 Kerala India

Sea level rise is one of the serious after-maths of global warming on the hydrosphere. The scientific community often depends on global climate models (GCMs) for projection of future sea levels. Numerous GCMs are available;thus, selecting the most appropriate GCM/GCMs is a critical task to be performed prior to downscaling. In this study, multi-criteria decision-making (MCDM) techniques, namely, Preference Ranking Organisation Method of Enrichment Evaluation (PROMETHEE-II), Elimination Et Choice Translating Reality (ELECTRE-II), and compromise programming, were used to identify appropriate GCMs whose projections can be used to downscale sea level projections at Ernakulam, Kerala, India. Support vector machine was employed to statistically downscale the sea level projections from the projections of GCMs. Five statistical metrics, namely, correlation coefficient (r), normalized root mean square error, absolute normalized average bias, mean absolute relative error, and skill score, were adopted in this study as the performance criteria. The weightage of each criterion was computed using the entropy method. Six GCMs (GISS-E2-H, CanESM2, ACCES S1-0, CNRM-CM5, GFDL-CM3, and CMCC-CM) were considered for the analysis based on the availability of predictors. GISS-E2-H, CanESM2, and ACCESS 1-0 occupied the first three positions respectively in all three MCDM techniques.

关键词： compromise programming ELECTRE PROMETHEE Sea level Statistical downscaling SVM

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Assessment Of Climate Change Impacts On Cotton Yield In A Semi-Arid Region: A Case Study

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淡江理工学刊 2024年第6期27卷 2619-2632页

作者： Kandula Srikanth N V Umamahesh

Cotton cultivation in India is of vital importance to the national economy. However, the susceptibility of cotton crops to climate change poses significant challenges. Recognizing the spatial heterogeneity of climate change's influence, comprehending its potential repercussions on cotton productivity is crucial. This research examines the effects of climate change on forthcoming cotton yields by utilizing the AquaCrop crop simulation model alongside eight climate models. A sensitivity analysis using the EFAST method is conducted to identify the key parameters influencing cotton yield, revealing eight influential parameters (Kcb, CGC, CCx, CDC, CCmin, wp, HIo, and Zmax) among the 30 parameters considered. These influential parameters are further employed to calibrate the model, automating, and optimizing the calibration process using a genetic algorithm to reduce the root mean square error (RMSE) between observed and simulated values. The AquaCrop model simulations demonstrate favourable agreement with observed data, exhibiting an RMSE of 0.15 t/ha during the calibration period (2001-2010) and 0.24 t/ha during the validation period (2011-2018). Utilizing the well-calibrated model, future projections are generated under different climate scenarios (SSP126 and SSP245) until the end of the century. The results indicate median yield increases of 4.4% and 1.9% in the SSP126 and SSP245 scenarios, respectively. Conversely, under the SSP370 and SSP585 scenarios, median yields are projected to decline by approximately 1.2% and 2% by the year 2100. It is an innovative study that combines AquaCrop, sensitivity analysis, and optimization to assess climate change impact on Indian cotton yields.

关键词： Climate change scenarios AquaCrop Sensitivity Analysis EFAST Genetic Algorithm compromise programming

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A Two-Stage GIS-Based Suitability Model for Siting Biomass-to-Biofuel Plants and its Application in West Virginia, USA

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International Journal of Forest Engineering 2011年第2期22卷 28-38页

作者： Jinzhuo Wu Jingxin Wang Michael P. Strager Northeast Forestry University College of Engineering and Technology West Virginia University Division of Forestry and Natural Resources Division of Resource Management

Woody biomass has been considered of low value because the cost of removal generally exceeded market price. New, val- ued-added markets to offset removal costs are necessary for utilization to be effective. In recent years the use of biomass as feedstock for biofuel production in the United States has been on the rise. A variety of liquid fuels can be produced from woody biomass; ethanol is one of the most promising. This study presents a two-stage approach to selecting woody biomass-based bio- fuel plants using Geographical Information System (GIS) spatial analysis and the multi-criteria analysis ranking algorithm of compromise programming. Site suitability was evaluated to minimize direct cost for investors and potential negative environ- mental impacts. The first step was to create a site suitability index using a linear fuzzy logic prediction model. The model in- volved 15 variables in three factor groups: (1) general physical conditions, (2) costs, and (3) environmental factors. The weights of the cost factors were determined using pairwise comparisons in the Analytical Hierarchy Process (AHP). The value of site suitability was reclassified into three categories (non-suitable, low-suitable, and high-suitable) using different classification methods. With a feasible plant location defined as an industrial site within the most suitable area, the second stage of the analy- sis used compromise programming to compare the potential sites. The criteria used to rank the potential sites included fuzzy distance to woody biomass, highways, railways, commercial airports, communities, and available parcel size. The AHP was used to compute the relative importance of each criterion. The top ten suitable sites were determined, and sensitivity analyses were conducted to derive the most preferred sites. The approach was successful in taking a large amount of non-commensurate spatial data and integrating a site-based ranking algorithm to find the top locations for biomass plants.

关键词： multi-criteria analysis (MCA) Geographical Information System (GIS) compromise programming biofuel site selection

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A new multi-criteria framework to identify optimal detention ponds in urban drainage systems

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JOURNAL OF FLOOD RISK MANAGEMENT 2023年第2期16卷 e12890-e12890页

作者： Hosseinzadeh, Azadeh Behzadian, Kourosh Rossi, Pekka Karami, Mozhgan Ardeshir, Abdollah Torabi Haghighi, Ali Amirkabir Univ Technol Dept Civil & Environm Engn Tehran Iran Univ Oulu Water Energy & Environm Engn Res Unit Oulu Finland Univ West London Sch Comp & Engn London England Amirkabir Univ Technol Dept Civil & Environm Engn Tehran Iran

Urban development broadly impacts the hydrological cycle, leading to increased peak flow and flooding. Surface water detention ponds are among the most efficient measures for attenuating peak flow and returning it from development to pre-development conditions. However, the major challenge is identifying optimal locations and cost-effective designs for these ponds. This paper presents a new framework for identifying the best strategies for using detention ponds to control floods in urban drainage systems (UDS). The framework comprises a portfolio of simulation tools coupled with evolutionary optimisation and multi-criteria decision analysis models. Hydraulic simulation of UDS is first modelled using SWMM and GIS tools. A multi-objective optimisation model was used to find the optimal location and design for detention ponds. The compromise programming (CP) multi-criteria decision-making method was then used to prioritise potential best management solutions for detention ponds based on several sustainability criteria comprising economic, environmental, physiographic and social factors. The results identified the key features of potential detention ponds appearing in all multi-objective optimal solutions that are useful for decision-makers/designers when planning/designing for new detention ponds. The selected optimal pond strategies can significantly improve the UDS performance by decreasing flood damage between 66% and 90% at the cost of between $50,000 and $160,000.

关键词： compromise programming detention ponds flood control GIS multi-objective optimisation

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ANALYSIS OF A KARSTIC AQUIFER MANAGEMENT PROBLEM BY FUZZY COMPOSITE programming

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WATER RESOURCES BULLETIN 1992年第1期28卷 63-73页

作者： BARDOSSY, A DUCKSTEIN, L UNIV ARIZONA DEPT SYST & IND ENGNTUCSONAZ 85721

A multiple objective framework for water resources problems possessing uncertain or imprecise elements is provided using distance-based concepts, fuzzy set theory, and fuzzy arithmetic. The case of regional management of a karstic aquifer in Hungary in which six conflicting objectives and six alternatives have been identified illustrates the methodology. The objectives are classified into three groups of two objectives each, namely: (1) environmental ( aesthetics, thermal springs temperature), (2) economic (mining, tourism), and (3) water quality (nitrates, phosphates). Both environmental objectives are formulated under fuzziness, and all objectives are scaled using the extension principle. Fuzzy compromise programming (FCP-I) is then applied;here, all six objectives are entered in a single l(p) norm measuring the distance between each alternative and an ideal point. Next, fuzzy composite programming (FCP-II) is developed;here, a trade off is first made within each group of objectives, and then an upper level trade-off takes place between the three groups. The fuzzy numbers describing each alternative as a result from applying these techniques are ranked to yield an ordering of the alternatives. The results of applying FCP-I, FCP-II, and two different ordering techniques are compared. The FCP-II technique appears to provide a relatively simple approach at hierarchical or multilevel multiple objective decision-making, where uncertainty is described by fuzziness.

关键词： compromise programming FUZZY ARITHMETIC FUZZY SETS HIERARCHICAL CRITERIA KARSTIC AQUIFER LP NORMS MINING MULTIPLE OBJECTIVES THERMAL SPRINGS

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Redundancy Allocation Combined with Supplier Selection for Design of Series-parallel Systems

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INTERNATIONAL JOURNAL OF ENGINEERING 2015年第5期28卷 730-737页

作者： Soltani, R. Tofigh, A. A. Sadjadi, S. J. Islamic Azad Univ Sci & Res Branch Dept Ind Engn Tehran Iran Amirkabir Univ Technol Dept Ind Engn Tehran Iran Iran Univ Sci & Technol Dept Ind Engn Tehran Iran

Designing highly reliable and economical systems is of interest in today's competitive world. In this paper, enhancing system reliability through redundancy allocation is investigated, where the supplier selection is taken into account and redundant components are provided from appropriate suppliers with the most suitable offers such as discount on purchasing price of components, warranty length of components, things like that, so that the system reliability, profit and the warranty length proposed by suppliers are simultaneously maximized. The resulting multi-objective model is then solved with the well-known compromise programming approach and the performance of the proposed approach is investigated through a numerical example.

关键词： System Design Redundancy Allocation Supplier Selection Price Discounting Warranty Length compromise programming

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System optimal compensators placement via immune multi-objective algorithm

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WSEAS Transactions on Systems 2009年第5期8卷 604-612页

作者： Hwang, T.Y. Tsai, C.M. Huang, Tson Liang Huang, C.C. Lien, Y.N. Chung, C.M. Chang, C.H. Computer Science Department National Taipei University of Education Ho-Ping E. Rd. Taipei Taiwan Department of Electrical Engineering Chang-Gung University 259 Wen-Hwa 1st Road Kwei-Shan Tao-Yuan Taiwan Computer Science Department National Chengchi University ZhiNan Rd. Taipei Taiwan

This work proposes a two-stage immune algorithm that embeds the compromise programming to perform multi-objective optimal compensator placement. A new problem formulation model that involves fuzzy sets to reflect the imprecise nature of objectives and incorporates multiple planning requirements is presented. The proposed approach finds a set of non-inferior (Pareto) solutions rather than any single aggregated optimal solution. Additionally, this developed approach eliminates the need for any user-defined weight factor to aggregate all objectives. Comparative studies are conducted on an actual system with encouraging results, demonstrating the effectiveness of the proposed approach.

关键词： Compensator placement compromise programming Immune algorithm Non-inferior set

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Selecting the most suitable blockchain platform: A case study on the healthcare industry using a novel rough MCDM framework

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TECHNOLOGICAL FORECASTING AND SOCIAL CHANGE 2023年第PartA期186卷

作者： Erol, Ismail Oztel, Ahmet Searcy, Cory Medeni, I. Tolga Ankara Yildirim Beyazit Univ Sch Business TR-06760 Ankara Turkiye Bartin Univ Sch Business TR-06760 Bartin Turkiye Toronto Metropolitan Univ Mech & Ind Engn Toronto ON M5B 2K3 Canada

Healthcare networks are sophisticated systems, which are commonly comprised of medical and drug suppliers, insurance companies, third-party logistics (3PL) providers, and regulators. Effective healthcare systems should be capable of sustainably delivering high quality and accessible patient care services using data shared through the best available technologies. However, healthcare data are generally hard to comprehend, use, and share since they are also inaccessible, non-standardized, and disseminated throughout the network. Blockchain may be employed to alleviate the impact of these challenges. However, only a few blockchain platforms (BP) have reached the stable design and established user base needed to give a healthcare organization (HO) confidence in their implementation. Each digital transformation project employing blockchain faces the challenge of picking a BP suitable to the requirements of a HO. While some research has been conducted to choose an appropriate BP, quantitative studies on specific industries, including healthcare, are currently insufficient. This investigation provides a case addressing the selection of the most feasible BP for a healthcare group. To this end, we propose a new multi-criteria decision-making (MCDM) framework that integrates the extent analysis-based rough Analytic Hierarchy Process (RAHP-E) and rough compromise programming (RCP). The findings of this study are validated through several analyses.

关键词： Blockchain Healthcare industry Rough numbers Analytic hierarchy process compromise programming Case study

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Modeling climate change impacts on blue and green water of the Kobo-Golina River in data-scarce upper Danakil basin, Ethiopia

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JOURNAL OF HYDROLOGY-REGIONAL STUDIES 2024年 53卷

作者： Abate, Belay Z. Alaminie, Addis A. Assefa, Tewodros T. Tigabu, Tibebe B. He, Li Tianjin Univ Sch Civil Engn State Key Lab Hydraul Engn Simulat & Safety Tianjin 300350 Peoples R China Amhara Design & Supervis Works Enterprise POB 1921 Bahir Dar Ethiopia Bahir Dar Univ Bahir Dar Inst Technol Fac Civil & Water Resources Engn POB 26 Bahir Dar Ethiopia Univ Calif Davis Dept Land Air & Water Resources Hydrol Sci Grp One Shield Ave Davis CA 95616 USA

Study region: Kobo-Golina River, Upper Danakil Basin, Ethiopia. Study focuses: It is crucial to understand the spatiotemporal distribution of blue water (BW) and green water (GW) for optimal use of water resources, especially in data -scarce regions. This study aims to evaluate the extent to which future climate is changing, and its impact on blue-green water resources in the study area. Projected changes were predicted based on the latest Coupled Model Intercomparison Project Phase 6 (CMIP6) Global Climate Models (GCMs) for three future periods (2015 - 2044, 2045 - 2075, 2076 - 2100) under two shared socio-economic pathways (SSP2 - 4.5 & SSP5 - 8.5). compromise programming technique was employed to rank and select best performing GCMs. The multi -variable calibrated SWAT + model was forced with climate projections from the top -ranked CMIP6 GCMs ensemble to simulate projected blue water (BW) and green water (GW) in the study area. New hydrological insights for the region: Compared to the baseline period (1984 - 2014), blue water declined while green water exhibited an increasing trend in all future periods under two SSPs. It is also noted that the spatial distribution of BW and GW remains uneven in the study area. Precipitation significantly impacted BW than GW resources. This study provides valuable insights into the utilization of the recent CMIP6 Global Climate Model coupled with multi -variable calibrated SWAT + hydrological models for better simulation of Blue -Green water in data -scarce basins under changing climate.

关键词： Blue Water Green water Climate Change SWAT + CMIP6 compromise programming

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