Power flow tracing for transmission open access

In this paper, graph theory is used to analyze real power transfer between individual generators and loads, which is important to transmission open access. Related lemmas are proved first to present necessary conditions required by the method. Based on an AC load flow solution a novel method is suggested which can determine downstream and upstream power flow tracing paths and calculate the contribution factors of generations and loads to the line flows efficiently in the system without circulating power. When the existence of circulating power in the system is detected, by revealing the reasons which cause circulating power, the optimal power flow (OPF) approach is suggested to eliminate it and a new feasible AC load flow solution will be obtained for tracing. The computer tests yield satisfactory results. The suggested method is suitable for both active and reactive power flow tracings of real power systems.published_or_final_versio

Allocation of tie-line costs in power exchange scheduling using amulti-agent approach

After deregulations in power industries, the original boundary lines have been removed and how to support optimal cross-border electricity trade planning has become an important issue. Decentralization, or all market participants have the rights to participate in decision making, is one of the directions. In this paper a decentralized structure is suggested to solve the problem using multi-agent technology. In this structure the information centralization is prevented and each market participant behaves rationally based on local information. Although the market participants make decisions to protect its own benefits, the minimum production and transmission cost of the whole system can be finally reached. This structure is based on the method proposed in another paper by the authors and implemented on computer via a multi-agent system using Java programming language. A demonstration on a 5-area test system shows that the suggested new approach is effective and promising.published_or_final_versio

A decentralized approach for optimal wholesale cross-border trade planning using multi-agent technology

Over the past decade, power industry has been undergoing deregulations to introduce competitions among market participants. Once centralized decision making must now adapt to the new market structure. The optimal cross-border electricity trade planning is an important issue in interconnected power systems under transmission open access. In this paper a decentralized approach is suggested to solve the problem using multi-agent technology. In the new approach rational market participants make decisions based on their own benefits, in the meantime the minimum production and transmission cost of the whole system can be reached without a central coordination except necessary information exchange through media like the Internet. A relevant lemma has been proven. The approach is implemented via a multi-agent system using Java programming language. Computer tests on a 5-area test system show that the suggested new approach is effective and promising.published_or_final_versio

A multi-agent based negotiation support system for cost allocation of cross-border transmission

Regulation and protection have been the major issues to prevent the consumers from enjoying good quality of service (QoS) at reasonable prices, for example, electricity and long distance call service. Deregulation in such industries started in early 1970s and have achieved significant results in, for example, telecommunication industry. The deregulation in telecommunication was mainly focused on reducing the market power to add more competition to reduce the price and to improve QoS. Similarly, the power industry in several countries also underwent regulation. The power industry used to be protected and regulated. Consumers were forced to buy electricity from particular suppliers and suffered high prices and low QoS. After deregulation, the original boundary lines have been removed and consumers have more alternatives. How to support optimal planning of cross-border electricity trade has become an important issue since then. Decentralization, or participants have the rights to participate in decision making, is one of the directions of deregulation. In this paper a decentralized structure is suggested to solve the problem by using multi-agent technology to create autonomy for each participant. In such structure the centralization of information transmission or decision making is prevented. Each participant behaves rationally to search for best benefit or payoff through the information she or he owns or through information exchange with other participants. Although all the market participants make decisions to protect their own benefits, the optimal solution (total costs) of the whole system can be achieved finally. This structure is based on the method proposed in [5] and implementation, which a multiagent system called Multi-Agent System for Cross-Border Trade (MASCBT), was done by using Java programming language. A demonstration on a 5-area test system shows that the suggested new approach is effective and promising.published_or_final_versio

A simulation study for comparing testing statistics in response-adaptive randomization

<p>Abstract</p> <p>Background</p> <p>Response-adaptive randomizations are able to assign more patients in a comparative clinical trial to the tentatively better treatment. However, due to the adaptation in patient allocation, the samples to be compared are no longer independent. At large sample sizes, many asymptotic properties of test statistics derived for independent sample comparison are still applicable in adaptive randomization provided that the patient allocation ratio converges to an appropriate target asymptotically. However, the small sample properties of commonly used test statistics in response-adaptive randomization are not fully studied.</p> <p>Methods</p> <p>Simulations are systematically conducted to characterize the statistical properties of eight test statistics in six response-adaptive randomization methods at six allocation targets with sample sizes ranging from 20 to 200. Since adaptive randomization is usually not recommended for sample size less than 30, the present paper focuses on the case with a sample of 30 to give general recommendations with regard to test statistics for contingency tables in response-adaptive randomization at small sample sizes.</p> <p>Results</p> <p>Among all asymptotic test statistics, the Cook's correction to chi-square test (<it>T</it>_<it>MC</it>) is the best in attaining the nominal size of hypothesis test. The William's correction to log-likelihood ratio test (<it>T</it>_<it>ML</it>) gives slightly inflated type I error and higher power as compared with <it>T</it>_<it>MC</it>, but it is more robust against the unbalance in patient allocation. <it>T</it>_{<it>MC </it>}and <it>T</it>_{<it>ML </it>}are usually the two test statistics with the highest power in different simulation scenarios. When focusing on <it>T</it>_{<it>MC </it>}and <it>T</it>_<it>ML</it>, the generalized drop-the-loser urn (GDL) and sequential estimation-adjusted urn (SEU) have the best ability to attain the correct size of hypothesis test respectively. Among all sequential methods that can target different allocation ratios, GDL has the lowest variation and the highest overall power at all allocation ratios. The performance of different adaptive randomization methods and test statistics also depends on allocation targets. At the limiting allocation ratio of drop-the-loser (DL) and randomized play-the-winner (RPW) urn, DL outperforms all other methods including GDL. When comparing the power of test statistics in the same randomization method but at different allocation targets, the powers of log-likelihood-ratio, log-relative-risk, log-odds-ratio, Wald-type Z, and chi-square test statistics are maximized at their corresponding optimal allocation ratios for power. Except for the optimal allocation target for log-relative-risk, the other four optimal targets could assign more patients to the worse arm in some simulation scenarios. Another optimal allocation target, <it>R</it>_{<it>RSIHR</it>}, proposed by Rosenberger and Sriram (<it>Journal of Statistical Planning and Inference</it>, 1997) is aimed at minimizing the number of failures at fixed power using Wald-type Z test statistics. Among allocation ratios that always assign more patients to the better treatment, <it>R</it>_{<it>RSIHR </it>}usually has less variation in patient allocation, and the values of variation are consistent across all simulation scenarios. Additionally, the patient allocation at <it>R</it>_{<it>RSIHR </it>}is not too extreme. Therefore, <it>R</it>_{<it>RSIHR </it>}provides a good balance between assigning more patients to the better treatment and maintaining the overall power.</p> <p>Conclusion</p> <p>The Cook's correction to chi-square test and Williams' correction to log-likelihood-ratio test are generally recommended for hypothesis test in response-adaptive randomization, especially when sample sizes are small. The generalized drop-the-loser urn design is the recommended method for its good overall properties. Also recommended is the use of the <it>R</it>_{<it>RSIHR </it>}allocation target.</p

Use of Bayesian networks to dissect the complexity of genetic disease: application to the Genetic Analysis Workshop 17 simulated data

Complex diseases are often the downstream event of a number of risk factors, including both environmental and genetic variables. To better understand the mechanism of disease onset, it is of great interest to systematically investigate the crosstalk among various risk factors. Bayesian networks provide an intuitive graphical interface that captures not only the association but also the conditional independence and dependence structures among the variables, resulting in sparser relationships between risk factors and the disease phenotype than traditional correlation-based methods. In this paper, we apply a Bayesian network to dissect the complex regulatory relationships among disease traits and various risk factors for the Genetic Analysis Workshop 17 simulated data. We use the Bayesian network as a tool for the risk prediction of disease outcome

Entanglement distribution and quantum discord

Establishing entanglement between distant parties is one of the most important problems of quantum technology, since long-distance entanglement is an essential part of such fundamental tasks as quantum cryptography or quantum teleportation. In this lecture we review basic properties of entanglement and quantum discord, and discuss recent results on entanglement distribution and the role of quantum discord therein. We also review entanglement distribution with separable states, and discuss important problems which still remain open. One such open problem is a possible advantage of indirect entanglement distribution, when compared to direct distribution protocols.Comment: 7 pages, 2 figures, contribution to "Lectures on general quantum correlations and their applications", edited by Felipe Fanchini, Diogo Soares-Pinto, and Gerardo Adess

Water Policies and Conflict Resolution of Public Participation Decision-Making Processes Using Prioritized Ordered Weighted Averaging (OWA) Operators

[EN] There is a growing interest in environmental policies about how to implement public participation engagement in the context of water resources management. This paper presents a robust methodology, based on ordered weighted averaging (OWA) operators, to conflict resolution decision-making problems under uncertain environments due to both information and stakeholders' preferences. The methodology allows integrating heterogeneous interests of the general public and stakeholders on account of their different degree of acceptance or preference and level of influence or power regarding the measures and policies to be adopted, and also of their level of involvement (i.e., information supply, consultation and active involvement). These considerations lead to different environmental and socio-economic outcomes, and levels of stakeholders' satisfaction. The methodology establishes a prioritization relationship over the stakeholders. The individual stakeholders' preferences are aggregated through their associated weights, which depend on the satisfaction of the higher priority decision maker. The methodology ranks the optimal management strategies to maximize the stakeholders' satisfaction. It has been successfully applied to a real case study, providing greater fairness, transparency, social equity and consensus among actors. Furthermore, it provides support to environmental policies, such as the EU Water Framework Directive (WFD), improving integrated water management while covering a wide range of objectives, management alternatives and stakeholders.Llopis Albert, C.; Merigó-Lindahl, JM.; Liao, H.; Xu, Y.; Grima-Olmedo, J.; Grima-Olmedo, C. (2018). Water Policies and Conflict Resolution of Public Participation Decision-Making Processes Using Prioritized Ordered Weighted Averaging (OWA) Operators. Water Resources Management. 32(2):497-510. https://doi.org/10.1007/s11269-017-1823-2S497510322Amin GR, Sadeghi H (2010) Application of prioritized aggregation operators in preference voting. Int J Intell Syst 25(10):1027–1034Chen TY (2014) A prioritized aggregation operator-based approach to multiple criteria decision making using interval-valued intuitionistic fuzzy sets: A comparative perspective. Inf Sci 281:97–112Chen LH, Xu ZS (2014) A prioritized aggregation operator based on the OWA operator and prioritized measures. J Intell Fuzzy Syst 27:1297–1307Chen LH, Xu ZS, Yu XH (2014a) Prioritized measure-guided aggregation operators. IEEE Trans Fuzzy Syst 22:1127–1138Chen LH, Xu ZS, Yu XH (2014b) Weakly prioritized measure aggregation in prioritized multicriteria decision making. Int J Intell Syst 29:439–461CHJ (2016). Júcar river basin authority http://www.chj.es/CHS (2016). Segura river basin authority http://www.chsegura.es/Dong JY, Wan SP (2016) A new method for prioritized multi-criteria group decision making with triangular intuitionistic fuzzy numbers. J Intell Fuzzy Syst 30:1719–1733EC (2000). Directive 2000/60/EC of the European Parliament and of the Council of October 23 2000 Establishing a Framework for Community Action in the Field of Water Policy. Official Journal of the European Communities, L327/1eL327/72 22.12.2000Jackson S, Tan P-L, Nolan S (2012) Tools to enhance public participation and confidence in the development of the Howard East aquifer water plan, Northern Territory. J Hydrol 474:22–28Jin FF, Ni ZW, Chen HY (2016) Note on “Hesitant fuzzy prioritized operators and their application to multiple attribute decision making”. Knowl-Based Syst 96:115–119Kentel E, Aral MM (2007) Fuzzy Multiobjective Decision-Making Approach for Groundwater Resources Management. J Hydrol Eng 12(2):206–217. https://doi.org/10.1061/(ASCE)1084-0699(2007)12:2(206).Kirchherr J, Charles KJ, Walton MJ (2016) Multi-causal pathways of public opposition to dam project in Asia: A fuzzy set qualitative comparative analysis (fsQCA). Glob Environ Chang 41:33–45. https://doi.org/10.1016/j.gloenvcha.2016.08.001Llopis-Albert C, Pulido-Velazquez D (2015) Using MODFLOW code to approach transient hydraulic head with a sharp-interface solution. Hydrol Process 29(8):2052–2064. https://doi.org/10.1002/hyp.10354Llopis-Albert C, Palacios-Marqués D, Soto-Acosta P (2015) Decision-making and stakeholders constructive participation in environmental projects. J Bus Res 68:1641–1644. https://doi.org/10.1016/j.jbusres.2015.02.010Llopis-Albert C, Merigó JM, Xu Y, Huchang L (2017) Improving regional climate projections by prioritized aggregation via ordered weighted averaging operators. Environ Eng Sci. https://doi.org/10.1089/ees.2016.0546Maia R (2017) The WFD Implementation in the European Member States. Water Resour Manag 31(10):3043–3060. https://doi.org/10.1007/s11269-017-1723-5Malczewski J, Chapman T, Flegel C, Walters D, Shrubsole D, Healy MA (2003) GIS - multicriteria evaluation with ordered weighted averaging (OWA): case study of developing watershed management strategies. Environ Plan A 35:1769–1784. https://doi.org/10.1068/a35156Merigó JM, Casanovas M (2011) The uncertain generalized owa operator and its application to financial decision making. Int J Inf Technol Decis Mak 10(2):211–230Merigó JM, Yager RR (2013) Generalized moving averages, distance measures and OWA operators. Int J Uncertain, Fuzziness Knowl-Based Syst 21(4):533–559Merigó JM, Palacios-Marqués D, Ribeiro-Navarrete B (2015) Aggregation systems for sales forecasting. J Bus Res 68:2299–2304Mesiar R, Stupnanová A, Yager RR (2015) Generalizations of OWA Operators. IEEE Trans Fuzzy Syst 23(6):2154–2162O’Hagan M (1988) Aggregating Template Rule Antecedents in Real-time Expert Systems with Fuzzy Set Logic. In: Proceedings of 22nd annual IEEE Asilomar Conference on Signals. IEEE and Maple Press, Pacific Grove, Systems and Computers, pp 681–689Rahmani MA, Zarghami M (2013) A new approach to combine climate change projections by ordered weighting averaging operator; applications to northwestern provinces of Iran. Glob Planet Chang 102:41–50Ran LG, Wei GW (2015) Uncertain prioritized operators and their application to multiple attribute group decision making. Technol Econ Dev Econ 21:118–139Ruiz-Villaverde, A., García-Rubio, M.A. (2017). Public Participation in European Water Management: from Theory to Practice. Water Resour Manag 31(8), 2479–2495. https://doi.org/10.1007/s11269-016-1355-1Sadiq R, Tesfamariam S (2007) Probability density functions based weights for ordered weighted averaging (OWA) operators: An example of water quality indices. Eur J Oper Res 182:1350–1368Sadiq R, Rodríguez MJ, Tesfamariam S (2010) Integrating indicators for performance assessment of small water utilities using ordered weighted averaging (OWA) operators. Expert Syst Appl 37:4881–4891Verma R, Sharma B (2016) Prioritized information fusion method for triangular fuzzy information and its application to multiple attribute decision making. Int J Uncertain, Fuzziness Knowl-Based Syst 24:265–290Wang HM, Xu YJ, Merigó JM (2014) Prioritized aggregation for non-homogeneous group decision making in water resource management. Econ Comput Econ Cybern Stud Res 48(1):247–258Wei GW (2012) Hesitant fuzzy prioritized operators. Knowl-Based Syst 31:176–182Wei CP, Tang XJ (2012) Generalized prioritized aggregation operators. Int J Intell Syst 27:578–589Xu ZS (2005) An Overview of Methods for Determining OWA Weights. Int J Intell Syst 20:843–865Yager RR (1988) On ordered weighted averaging aggregation operators in multi-criteria decision making, IEEE Transactions on Systems. Man Cybern B 18(1988):183–190Yager RR (2008) Prioritized Aggregation Operators. Int J Approx Reason 48:263–274Yan H-B, Huynh V-N, Nakamori Y, Murai T (2011) On prioritized weighted aggregation in multi-criteria decision making. Expert Syst Appl 38(1):812–823Ye J (2014) Prioritized aggregation operators of trapezoidal intuitionistic fuzzy sets and their application to multicriteria decision-making. Neural Comput & Applic 25:1447–1454Yu XH, Xu ZS, Liu SS (2013) Prioritized multi-criteria decision making based on preference relations. Comput Ind Eng 66:104–115Zadeh LA (1983) A Computational Approach to Fuzzy Quantifiers in Natural Languages. Comput Math Appl 9:149–184Zarghami M, Szidarovszky F (2009) Revising the OWA operator for multi criteria decision making problems under uncertainty. Eur J Oper Res 198:259–265Zarghami M, Ardakanian R, Memariani A, Szidarovszky F (2008) Extended OWA Operator for Group Decision Making on Water Resources Projects. J Water Resour Plan Manag 134(3):266–275. https://doi.org/10.1061/(ASCE)0733-9496(2008)134:3(266)Zarghami M, Szidarovszky F, Ardakanian R (2009) Multi-attribute decision making on inter-basin water transfer projects. Transaction E. Ind Eng 16(1):73–80Zhao XF, Li QX, Wei GW (2014) Some prioritized aggregating operators with linguistic information and their application to multiple attribute group decision making. J Intell Fuzzy Syst 26:1619–1630Zhao N, Xu ZS, Ren ZL (2016) On typical hesitant fuzzy prioritized “or” operator in multi-attribute decision making. Int J Intell Syst 31:73–100Zhou LY, Lin R, Zhao XF, Wei GW (2013) Uncertain linguistic prioritized aggregation operators and their application to multiple attribute group decision making. Int J Uncertain, Fuzziness Knowl-Based Syst 21:603–627Zhou LG, Merigó JM, Chen HY, Liu JP (2016) The optimal group continuous logarithm compatibility measure for interval multiplicative preference relations based on the COWGA operator. Inf Sci 328:250–26