a multiobjective approach to vendor selection abstract purchases from vendors involve significant costs for many firms decisions related to these purchases include the selection of vendors and the determination of order quantities to be placed with the selected vendors such decisions are frequently multiobjective in nature that is they are evaluated by more than one criterion at least 23 criteria for various vendor selection problems have been identified in this article we present a multiobjective approach to systematically analyze the inherent tradeoffs involved in multicriteria vendor selection problems the approach is motivated by and demonstrated with an actual purchasing problem facing a division of a fortune 500 company

evaluating the impacts of priority dispatch in the european electricity market this paper compares the impact of the nodal pricing and european market coupling organizations on different economic agents of the power system under two main wind policies under the priority dispatch policy transmission system operators tsos must accommodate all wind energy produced which thus has the priority over energy produced by conventional plants in the no priority dispatch policy tsos can decide not to inject all potential wind power in the grid in order to limit congestion problems the effects of these two wind policies are measured by developing simple stochastic programming models that consider cases with different wind penetration levels existing capacities and endogenous investments as well as assumptions on the eu ets our computational experiments show that when there is priority dispatch nodal pricing and market coupling evolve in a similar way as long as wind penetration is not too high in contrast a significant increase of wind penetration causes the collapse of the market coupling organization while nodal pricing continues to perform well on the other hand no priority dispatch removes most of the problems resulting from market coupling which still exhibits a slightly lower efficiency than nodal pricing these outcomes do not depend on the contextual assumptions fixed capacities vs investment eu ets vs non eu ets that characterize the several cases analyzed this suggested that our policy conclusions are robust furthermore our models overestimate the flexibility of conventional plants which means that these conclusions would likely be reinforced with a more detailed model

fuzzy multiobjective linear model for supplier selection in a supply chain abstract within new strategies for purchasing and manufacturing suppliers play a key role in achieving corporate competition hence selecting the right suppliers is a vital component of these strategies in practice vagueness and imprecision of the goals constraints and parameters in this problem make the decision making complicated in spite of the importance of the problem the literature on this subject is relatively scarce in this paper a fuzzy multiobjective linear model is developed to overcome the vagueness of the information for the first time in a fuzzy supplier selection problem an asymmetric fuzzy decision making technique is applied to enable the decision maker to assign different weights to various criteria the model is explained by an illustrative example

evaluating the impacts of real time pricing on the usage of wind generation one of the impediments to large scale use of wind generation within power systems is its nondispatchability and variable and uncertain real time availability operating constraints on conventional generators such as minimum generation points forbidden zones and ramping limits as well as system constraints such as power flow limits and ancillary service requirements may force a system operator to curtail wind generation in order to ensure feasibility furthermore the pattern of wind availability and electricity demand may not allow wind generation to be fully utilized in all hours one solution to these issues which could reduce these inflexibilities is the use of real time pricing rtp tariffs which can both smooth out the diurnal load pattern in order to reduce the impact of binding unit operating and system constraints on wind utilization and allow demand to increase in response to the availability of costless wind generation we use and analyze a detailed unit commitment model of the texas power system with different estimates of demand elasticities to demonstrate the potential increases in wind generation from implementing rtp

modeling unit commitment in political context case of china s partially restructured electricity sector restructuring an electricity sector entails a complex realignment of political and economic institutions which may both delay and distort the achievement of satisfactorily competitive conditions in research and planning for policy interventions in power systems under these varied regulatory environments typical operational models may neglect important interactions between techno economic criteria and political constraints leading to poor understanding of underlying causes of inefficiency and to inappropriate recommendations we develop tractable formulations of the unit commitment problem based on integer clustering of similar units that endogenize important political factors in the northeast grid region of china we demonstrate the importance of these interactions on operations and provide a set of options for researchers to explore further pathways for china s ongoing power system reforms for example wind integration a key policy priority is inhibited by the interaction of institutions limiting short and long term sources of flexibilities in interprovincial trade

investment in electricity networks with transmission switching we consider the application of dantzig wolfe decomposition to stochastic integer programming problems arising in the capacity planning of electricity transmission networks that have some switchable transmission elements the decomposition enables a column generation algorithm to be applied which allows the solution of large problem instances the methodology is illustrated by its application to a problem of determining the optimal investment in switching equipment and transmission capacity for an existing network computational tests on ieee test networks with 73 nodes and 118 nodes confirm the efficiency of the approach

reserve requirements to efficiently manage intra zonal congestion the security constrained unit commitment problem schedules power generators to minimize cost subject to operating constraints reserve requirements ensure that reserve is available to re balance the system following a contingency but do not guarantee reliability in congested systems where reserve activation is limited by transmission constraints operators improve reserve deliverability by limiting power flows and controlling the location of reserves zones are used to address inter zonal congestion but operators lack efficient ways to handle intra zonal congestion we propose dynamically relating minimum reserve levels to transmission stress in a computationally efficient approach that complements existing reserve models from the literature analysis on the ieee rts 96 test case demonstrates the approach can mitigate intra zonal congestion more economically than traditional reserve policies

renewable energy integration in zonal markets in this paper we investigate the impact of zonal network management in the operation of power systems with significant levels of renewable energy integration our study is inspired by the current state of the european energy market and we focus on a case study of the central western european cwe system first we present a hierarchy of models that account for unit commitment the separation of energy and reserves and the simplified representation of transmission constraints in a zonal market in order to examine the impact of these factors on efficiency in a regime of large scale renewable energy integration second we simulate operations of the cwe system under the zonal market design using a detailed instance that consists of 656 thermal generators 679 nodes and 1073 lines with multiarea renewable energy production and 15 minute time resolution zonal market operations are compared against deterministic and stochastic unit commitment using high performance computing in order to tackle the scale of the resulting models we find that market design can have an influence on cost efficiency which far exceeds the benefits of stochastic unit commitment relative to deterministic unit commitment we conduct a detailed analysis of the numerical results in order to explain the relative performance of the different models

an engineering economic approach to transmission planning under market and regulatory uncertainties wecc case study we propose a stochastic programming based tool to support adaptive transmission planning under market and regulatory uncertainties we model investments in two stages differentiating between commitments that must be made now and corrective actions that can be undertaken as new information becomes available the objective is to minimize expected transmission and generation costs over the time horizon nonlinear constraints resulting from kirchhoff s voltage law are included we apply the tool to a 240 bus representation of the western electricity coordinating council and model uncertainty using three scenarios with distinct renewable electricity mandates emissions policies and fossil fuel prices we conclude that the cost of ignoring uncertainty the cost of using naive deterministic planning methods relative to explicitly modeling uncertainty is of the same order of magnitude as the cost of first stage transmission investments furthermore we conclude that heuristic rules for constructing transmission plans based on scenario planning can be as suboptimal as deterministic plans

market clearing with stochastic security part ii case studies this paper analyzes the market clearing formulation with stochastic security developed in its companion paper through two case studies solved using mixed integer linear programming techniques the generation and reserve schedules as well as the nodal prices of energy and security are assessed under various conditions such as a line flow limits b when nonspinning reserve is excluded from the formulation c demand side valuation of energy not served d generator ramping limits and e the set of pre selected contingencies

on the informational content of spot and forward exchange rates abstract in foreign exchange markets efficiency tests have typically been applied to the forward rate on the argument that the forward rate should be a good proxy for the unobservable market expectations of future spot rates the present study offers innovations in two directions first we utilize a data set which consists of daily observations on spot and forward exchange rates this allows us to match the forward contract with the exact settlement date and to create a large number of non overlapping data sets second and more importantly we show that in general the current spot rate is a better predictor of the future spot rate than is the current forward rate of appropriate maturity

further tests on the forward exchange rate unbiasedness hypothesis in this paper we reexamine the evidence on the forward rate unbiasedness hypothesis for the main currencies vis a vis the u s dollar exchange rate using the phillips and hansen 1990 estimation and inference procedure

optimal transmission switching sensitivity analysis and extensions in this paper we continue to analyze optimal dispatch of generation and transmission topology to meet load as a mixed integer program mip with binary variables representing the state of the transmission element line or transformer previous research showed a 25 savings by dispatching the ieee 118 bus test case this paper is an extension of that work it presents how changing the topology affects nodal prices load payment generation revenues cost and rents congestion rents and flowgate prices results indicate that changing the topology to cut costs typically results in lower load payments and higher generation rents for this network computational issues are also discussed

renewable electric energy integration quantifying the value of design of markets for international transmission capacity abstract integrating large quantities of variable renewable electricity generation remains a political and operational challenge one of the main obstacles in europe to installing at least 200 gws of power from variable renewable sources is how to deal with the insufficient network capacity and the congestion that will result from new flow patterns we model the current methodology for controlling congestion at international borders and compare its results under varying penetrations of wind power with models that simulate an integrated european network using nodal localised marginal pricing the nodal pricing simulations illustrate that congestion and price patterns vary considerably between wind scenarios and within countries and that a nodal price regime could make better use of existing network capacity introducing substantial operational cost savings and reducing marginal power prices in the majority of european countries

integrated fuzzy multi criteria decision making method and multi objective programming approach for supplier selection and order allocation in a green supply chain abstract an organization s environmental performance is affected by its suppliers environmental performance and selecting green suppliers is a strategic decision in order to be more competitive in today s global market the supplier selection problem involves several quantitative and qualitative criteria in the supplier selection process if suppliers have limited capacity or other constraints it is necessary to determine the best supplier and order quantity of each supplier in this paper we present an integrated approach of fuzzy multi attribute utility theory and multi objective programming for rating and selecting the best green suppliers according to economic and environmental criteria and then allocating the optimum order quantities among them at first the fuzzy analytic hierarchy process and fuzzy technique for order preference by similarity to ideal solution is applied in order to analyze the importance of multiple criteria by incorporating experts opinion and to determine the best green suppliers next multi objective linear programming is used to consider and to formulate various constraints such as quality control capacity and other objectives the objective of the mathematical model is simultaneously to maximize the total value of purchasing and to minimize the total cost of purchasing to handle the subjectivity of decision makers preferences fuzzy logic has been applied the efficiency and application of the proposed approach has been illustrated with a case study in an automobile manufacturing company the obtained results help firms establish a systematic approach for tackling green supplier selection and order allocation problems in a realistic situation finally managerial implications conclusions and directions for additional research are introduced

multi objective models for lot sizing with supplier selection abstract in this paper two multi objective mixed integer non linear models are developed for multi period lot sizing problems involving multiple products and multiple suppliers each model is constructed on the basis of three objective functions cost quality and service level and a set of constraints the total costs consist of purchasing ordering holding and backordering and transportation costs ordering cost is seen as an ordering frequency dependent function whereas total quality and service level are seen as time dependent functions the first model represents this problem in situations where shortage is not allowed while in the second model all the demand during the stock out period is backordered considering the complexity of these models on the one hand and the ability of genetic algorithms to obtain a set of pareto optimal solutions we apply a genetic algorithm in an innovative approach to solve the models comparison results indicate that in a backordering situation buyers are better able to optimize their objectives compared to situations where there is no shortage if we take ordering frequency into account the total costs are reduced significantly

a single settlement energy only electric power market for unpredictable and intermittent participants we discuss a stochastic programming based method for scheduling electric power generation subject to uncertainty such uncertainty may arise from either imperfect forecasting or moment to moment fluctuations and on either the supply or the demand side the method gives a system of locational marginal prices that reflect the uncertainty and these may be used in a market settlement scheme in which payment is for energy only we show that this scheme is revenue adequate in expectation

transmission investment problems in europe going beyond standard solutions the european transmission grid is facing an investment challenge there is a strong call for more transmission capacity at the same time the investment climate is fierce and troubled by public opposition a complex regulatory framework etc many transmission capacity expansion projects are delayed or canceled in this paper different technology options suitable for increasing transmission capacity are discussed the aim is to provide policy makers with information on technologies without going too much into technical details the focus is on opportunities and limitations to implement various technological alternatives in practice including technical solutions that go beyond constructing new connection lines the criteria used in this technology assessment are based on the obstacles reported in the european priority interconnection plan this ensures a realistic approach based on problems encountered in real projects although ac overhead lines ohl will remain the standard solution for grid expansion it is argued that different technology options can overcome many obstacles that ohl face additionally it is illustrated that the higher investment costs for some solutions can be offset with an increased benefit e g by accomplishing investments with smaller delays due to fewer obstacles encountered

covariance matrix estimators and tests of market efficiency abstract this paper carries out multi currency multi horizon and combined tests of simple market efficiency using alternative covariance matrix estimators whose finite sample performances have been examined elsewhere in the literature the data utilized are properly aligned weekly exchange rates from june 1973 to december 1994 on bid spot 1 month 3 month and 6 month ask forward rates for several currencies the results demonstrate that tests of market efficiency are sensitive to the information set specified the prediction horizon considered and the covariance matrix estimator employed in most but not all cases rejections of market efficiency are overturned using a prewhitened heteroskedasticity and autocorrelation consistent covariance matrix estimator with optimal asymptotic properties and better finite sample performance

the total cost of logistics in supplier selection under conditions of multiple sourcing multiple criteria and capacity constraint abstract little attention is given in the literature to decisions on the appropriate selection of suppliers and on assigning order quantities to these suppliers in the case of multiple sourcing with multiple criteria and with suppliers capacity constraints only a few mathematical programming models to analyse such decisions have been published to date and these have tended to consider only net price as the cost of purchasing although the costs of transportation ordering and storage may be significantly important to the decision in this paper a mixed integer non linear programming model is presented to solve the multiple sourcing problem which takes into account the total cost of logistics including net price storage transportation and ordering costs buyer limitations on budget quality service etc can also be considered in the model an algorithm is proposed to solve the model and the model is illustrated using a numerical example

tractable transmission topology control using sensitivity analysis the standard economic generation dispatch ed minimizes generation costs subject to transmission constraints where the status of each line i e open or closed is fixed recent research shows that by optimally dispatching the network topology along with generation resources significant congestion costs may be avoided optimal topology control i e appropriate changes of transmission line status for real sized power networks requires the solution of a computationally intractable mixed integer linear program however it appears that much of the cost savings may be attained by changing the status of just a few lines this paper proposes tractable transmission topology control policies which employ sensitivity information readily available from the ed to select candidate lines to change status while maintaining system connectivity implementation on the ieee 118 bus test system found that our best performing policy captured an average of 96 of the potential cost savings moreover the limited computational effort required suggests that these policies could be employed in real system operations

market failures of market coupling and counter trading in europe an illustrative model based discussion the horizontal integration of the energy market and the organization of transmission services remain two open issues in the restructured european electricity sector the coupling of the french belgian and dutch electricity markets the trilateral market in november 2006 was a real success the extension of the system to germany in november 2010 also proceeded smoothly and the intent is to continue with the same market architecture but market coupling is based on a zonal system which has often failed in meshed grids this may cast doubts on what will happen in the future when electricity demand picks up again and wind develops the nodal system has generally been more successful than zonal architectures but its implementation is not currently foreseen in the eu this paper analyzes versions of market coupling that differ by the organization of counter trading while underplayed in current discussions counter trading could become a key element of market coupling as its geographic coverage expands and wind penetrates we simplify matters by assuming away strategic behavior between the energy and counter trading markets and conduct the analysis on a stylized six node example taken from the literature we simulate market coupling for different assumptions of zonal decomposition and coordination of transmission system operators tsos we show that these assumptions matter even in the absence of strategic behavior market coupling can be quite vulnerable to the particular situation on hand countertrading can work well or completely fail and it is not clear beforehand what will prevail our analysis relies on standard economic notions such as social welfare and generalized nash equilibrium but the use of these notions is probably novel the nodal organization is the reference first best scenario different zonal decompositions and degrees of coordination are then studied with respect to this first best solution

stochastic optimization of sub hourly economic dispatch with wind energy we present a stochastic programming framework for a multiple timescale economic dispatch problem to address integration of renewable energy resources into power systems this framework allows certain slow response energy resources to be controlled at an hourly timescale while fast response resources including renewable resources and related network decisions can be controlled at a sub hourly timescale to this end we study two models motivated by actual scheduling practices of system operators using an external simulator as driver for sub hourly wind generation we optimize these economic dispatch models using stochastic decomposition a sample based approach for stochastic programming computational experiments conducted on the ieee rts96 system and the illinois system reveal that optimization with sub hourly dispatch not only results in lower expected operational costs but also predicts these costs with far greater accuracy than with models allowing only hourly dispatch our results also demonstrate that when compared with standard approaches using the extensive formulation of stochastic programming the sequential sampling approach of stochastic decomposition provides better predictions with much less computational time

cointegration and unit roots this paper provides an updated survey of a burgeoning literature on testing estimation and model specification in the presence of integrated variables integrated variables are a specific class of non stationary variables which seem to characterise faithfully the properties of many macroeconomic time series the analysis of cointegration develops out of the existence of unit roots and offers a generic route to test the validity of the equilibrium predictions of economic theories special emphasis is put on the empirical researcher s point of view

impact of the regulatory framework for transmission investments on the cost of renewable energy in the eu abstract under the current regulatory frame in the eu transmission planning is done at the national level to maximize national welfare rather than european welfare in this paper we develop a competitive equilibrium model that calculates the impact of this imperfect regulatory framework on the cost of renewable energy we apply the model to a power system with two interconnected zones and find that the impact is case specific but significant we also find that the negative impact of national transmission planning on the cost of renewable energy is more significant in a state of the world in which member states trade renewable energy but that this negative effect is much smaller than the positive effect of renewable energy trade between member states we conclude that the imperfect regulatory framework for transmission investment is a significant cost for renewable energy in the eu but that it should not stop member states from trading renewable energy

economic valuation of reserves in power systems with high penetration of wind power this paper proposes a methodology to determine the required level of spinning and nonspinning reserves in a power system with a high penetration of wind power the computation of the required reserve levels and their costs is achieved through a stochastic programming market clearing model spanning a daily time horizon this model considers the network constraints and takes into account the cost of both the load shedding and the wind spillage the methodology proposed is illustrated using an example and a realistic case study some conclusions are finally drawn

the impacts of transmission topology control on the european electricity network the european union is targeting a 20 share of energy from renewable resources by 2020 and this increase is in turn expected to lead to operational challenges that will require various congestion management actions by system operators in this paper we deal with topology control of the transmission network as a congestion management resource and evaluate the impacts of topology control on the european electricity network to do this we co optimize unit commitment and transmission switching over 24 h and we use a decomposition scheme to tackle the resulting large scale problem our analysis is conducted on different scenarios of load and renewable power generation we find that topology control results in significant cost savings within europe which tend to be inversely related to net load the robustness of our results is supported by an extensive sensitivity analysis

hybrid pricing in a coupled european power market with more wind power abstract in the european electricity market the promotion of wind power leads to more network congestion zonal pricing market coupling which does not take the physical characteristics of transmission into account is the most commonly used method to relieve network congestion in europe however zonal pricing fails to provide adequate locational price signals regarding scarcity of energy and thus creates a large amount of unscheduled cross border flows originating from wind generated power in this paper we investigate the effects of applying a hybrid congestion management model i e a nodal pricing model for one country embedded in a zonal pricing system for the rest of the market we find that compared to full nodal pricing hybrid pricing fails to fully utilize all the resources in the network and some wrong price signals might be given however hybrid pricing still outperforms zonal pricing the results from the study cases show that within the area applying nodal pricing better price signals are given the need for re dispatching is reduced more congestion rent is collected domestically and the unit cost of power is reduced

incorporating post zonal reserve deployment transmission constraints into energy and ancillary service co optimization this paper presents a new approach implemented in miso day ahead and real time energy and ancillary service market clearing processes to address the reserve deliverability issue in this approach miso enhanced the co optimization process to incorporate post zonal reserve deployment transmission constraints reserves are procured within the co optimization to meet both market wide reserve requirements and ensure their deliverability on a zonal basis as a result zonal market clearing prices mcps for reserves can properly reflect the effects of zonal reserve deployment on transmission constraints under consideration

a weighted max min model for fuzzy multi objective supplier selection in a supply chain abstract supplier selection is one of the most important activities of purchasing departments this importance is increased even more by new strategies in a supply chain supplier selection is a multi criteria decision making problem in which criteria have different relative importance in practice for supplier selection problems many input information are not known precisely the fuzzy set theories can be employed due to the presence of vagueness and imprecision of information a weighted max min fuzzy model is developed to handle effectively the vagueness of input data and different weights of criteria in this problem due to this model the achievement level of objective functions matches the relative importance of the objective functions in this paper an analytic hierarchy process ahp is used to determine the weights of criteria the proposed model can help the decision maker dm to find out the appropriate order to each supplier and allows the purchasing manager s to manage supply chain performance on cost quality and service the model is explained by an illustrative example