Showing papers on "Power system simulation published in 2005"

Fuel consumption minimization of a microgrid

Abstract: A cost optimization scheme for a microgrid is presented. Prior to the optimization of the microgrid itself, several schemes for sharing power between two generators are compared. The minimization of fuel use in a microgrid with a variety of power sources is then discussed. The optimization of a small power system has important differences from the case of a large system and its traditional economic dispatch problem. Among the most important differences is the presence of a local heat demand which adds another dimension to the optimization problem. The microgrid considered in this paper consists of two reciprocating gas engines, a combined heat and power plant, a photovoltaic array and a wind generator. The optimization is aimed at reducing the fuel consumption rate of the system while constraining it to fulfil the local energy demand (both electrical and thermal) and provide a certain minimum reserve power. A penalty is applied for any heat produced in excess of demand. The solution of the optimization problem strongly supports the idea of having a communication infrastructure operating between the power sources.

Probabilistic load-flow computation using point estimate method

Abstract: A new probabilistic load-flow solution algorithm based on an efficient point estimate method is proposed in this paper. It is assumed that the uncertainties of bus injections and line parameters can be estimated or measured. This paper shows how to estimate the corresponding uncertainty in the load-flow solution. The proposed method can be used directly with any existing deterministic load-flow program. For a system with m uncertain parameters, it uses 2m calculations of load flow to calculate the statistical moments of load-flow solution distributions by weighting the value of the solution evaluated at 2m locations. The moments are then used in the probability distribution fitting. Performance of the proposed method is verified and compared with those obtained from Monte Carlo simulation technique and combined simulation and analytical method using several IEEE test systems.

Market-clearing with stochastic security-part I: formulation

Abstract: The first of this two-paper series formulates a stochastic security-constrained multi-period electricity market-clearing problem with unit commitment. The stochastic security criterion accounts for a pre-selected set of random generator and line outages with known historical failure rates and involuntary load shedding as optimization variables. Unlike the classical deterministic reserve-constrained unit commitment, here the reserve services are determined by economically penalizing the operation of the market by the expected load not served. The proposed formulation is a stochastic programming problem that optimizes, concurrently with the pre-contingency social welfare, the expected operating costs associated with the deployment of the reserves following the contingencies. This stochastic programming formulation is solved in the second companion paper using mixed-integer linear programming methods. Two cases are presented: a small transmission-constrained three-bus network scheduled over a horizon of four hours and the IEEE Reliability Test System scheduled over 24 h. The impact on the resulting generation and reserve schedules of transmission constraints and generation ramp limits, of demand-side reserve, of the value of load not served, and of the constitution of the pre-selected set of contingencies are assessed.

Corrective switching algorithm for relieving overloads and voltage violations

Abstract: It is widely known that corrective switching, including transmission line switching, bus-bar switching, and shunt element switching, may change the states of the power systems, and consequently, affect the distribution of power flows, transmission losses, short circuit currents, voltage profiles as well as transient stability of power systems. In this paper, a new algorithm is developed to find the best line and bus-bar switching action for relieving overloads and voltage violations caused by system contingencies based on a sparse inverse technique and fast decoupled power flow with limited iteration count. A general model of bus-bar switching action is also presented such that the new algorithm can simulate any kind of complicated bus-bar switching action. Furthermore, on the basis of a newly proposed voltage distribution factor by multiple iterations in power flow calculation, a novel algorithm for corrective voltage control by shunt switching is developed. These two algorithms are then integrated into a corrective switching algorithm. Simulation results on the WECC 179-bus system indicate that the new corrective switching algorithm proposed in this paper can effectively solve certain problems of line overloads and voltage violations. The computation time required is also satisfactory.

Electromagnetic transients simulation models for accurate representation of switching losses and thermal performance in power electronic systems

Abstract: This work presents an electrothermal model of an insulated-gate bipolar transistor (IGBT) switch suitable for the simulation of switching and conduction losses in a large class of voltage-sourced converter (VSC)-based flexible ac transmission systems (FACTS) devices. The model is obtained by mathematical derivation of loss equations from the known submicrosecond device switching characteristics, and through the selection of appropriate differential equation parameters for representing the thermal performance. The model is useful in determining the device's heat generation, its junction temperature, as well as the cooling performance of the connected heat sinks. The model provides accurate results without recourse to an unreasonably small time step.

Benders decomposition: applying Benders decomposition to power systems

Abstract: It is apparent that power system restructuring provides a major forum for the application of decomposition techniques - including the Benders decomposition algorithm - to coordinate the optimization of various objectives among self-interested entities. It is used for solving large-scale, mixed-integer programming (MIP) problems. Benders decomposition has been successfully applied to take advantage of underlying problem structures for various optimization problems, such as restructured power systems operation and planning. This paper shows how Benders decomposition works in the power system.

Integrating Large Wind Farms into Weak Power Grids with Long Transmission Lines

Abstract: This paper addresses some of the most significant challenges for wind generation facilities, including voltage control, reactive power management, dynamic power-swing stability, and behavior following disturbances in the power grid. It also describes wind farm control functions, including performance for controlling grid voltage in quasi-steady-state and dynamic conditions. Low-voltage ride-through characteristics, including performance following severe system disturbances. Dynamic power control functions within wind turbine-generators, including transient and dynamic performance from power swings. The dynamic performance of GE wind turbine-generators with LVRT and WFMS technology is described. The information presented includes dynamic simulation results from existing power systems with large wind farm interconnections, and actual field measurements from operating systems

Solving the unit commitment problem of hydropower plants via Lagrangian Relaxation and Sequential Quadratic Programming

Abstract: We consider the optimal scheduling of hydropower plants in a hydrothermal interconnected system. This problem, of outmost importance for large-scale power systems with a high proportion of hydraulic generation, requires a detailed description of the so-called hydro unit production function. In our model, we relate the amount of generated hydropower to nonlinear tailrace levels; we also take into account hydraulic losses, turbine-generator efficiencies, as well as multiple 0-1 states associated with forbidden operation zones. Forbidden zones are crucial to avoid nasty phenomena such as mechanical vibrations in the turbine, cavitation, and low efficiency levels. The minimization of operating costs subject to such detailed constraints results in a large-scale mixed-integer nonlinear programming problem. By means of Lagrangian Relaxation, the original problem is split into a sequence of smaller and easy-to-solve subproblems, coordinated by a dual master program. In order to deal better with the combinatorial aspect introduced by the forbidden zones, we derive three different decomposition strategies, applicable to various configurations of hydro plants (with few or many units, which can be identical or different). We use a Sequential Quadratic Programming algorithm to solve nonlinear subproblems. We assess our approach on a real-life hydroelectric configuration extracted from the south sub region of the Brazilian hydrothermal power system.

Algorithms for the accounting of multiple switching events in digital simulation of power-electronic systems

Abstract: Digital simulation of power systems containing power electronics apparatus is challenging due to the need to account multiple switching events within one simulation time-step. This paper describes a family of algorithms, with varying levels of computational complexity, for accounting such switching events in digital simulations. The proposed algorithms are applicable for both off-line and real-time simulations. A comparative study on their performance such as harmonic content, errors in fundamental component and simulation time requirement is presented. A Pulse Width Modulated (PWM) Voltage Source Converter (VSC) based D-STATCOM system is used as a case study for simulations. Simulation results indicate excellent performance (accuracy and efficiency) in comparison with a fixed time-step algorithm using a small step-size.

A parallel transient stability simulation for power systems

Abstract: As power systems continue to develop, online dynamic security analysis and real-time simulation using parallel computing are becoming increasingly important. This paper presents a novel multilevel partition scheme for parallel computing based on power network regional characteristics and describes the design and implementation of a hierarchical block bordered diagonal form (BBDF) algorithm for power network computation. Some optimization schemes are further proposed to reduce the computation and communication time and to improve the scalability of the program. The simulation results show that, for a large network with 2115 nodes, 2614 branches, 248 generators, and 544 loads, the proposed algorithms and schemes run ten times faster on a cluster system with eight CPUs than on a single CPU. Thus, they satisfy the real-time simulation requirement for large-scale power grids.

A Stochastic Integer Programming Model for Incorporating Day-Ahead Trading of Electricity into Hydro-Thermal Unit Commitment

Abstract: We develop a two-stage stochastic integer programming model for the simultaneous optimization of power production and day-ahead power trading in a hydro-thermal system. The model rests on mixed-integer linear formulations for the unit commitment problem and for the price clearing mechanism at the power exchange. Foreign bids enter as random components into the model. We solve the stochastic integer program by a decomposition method combining Lagrangian relaxation of nonanticipativity with branch-and-bound in the spirit of global optimization. Finally, we report some first computational experiences.

Price-based optimal control of electrical power systems

Abstract: During the past decade, electrical power systems have been going through some major restructuring processes. From monopolistic, highly regulated and one utility controlled operation, a system is being restructured to include many parties competing for energy production and consumption, and for provision of many of the ancillary services necessary for system operation. With the emergence of competitive markets as central operational mechanisms, the prime operational objective has shifted from a centralized, utility cost minimization objective to decentralized, profit maximization objectives of competing parties. The market-based (price-based) operation is shown to be practically the only approach that is capable to simultaneously provide incentives to hold the prices at marginal costs and to minimize the costs. As a result, such an operational structure inherently tends to maximize the social welfare of the system during its operation, and to accelerate developments and applications of new technologies. Another major change that is taking place in today’s power systems is an increasing integration of small-scale distributed generation (DG) units. Since in future power systems, a large amounts of DG will be based on renewable, intermittent energy sources, e.g. wind and sun, these systems will be characterized by significantly larger uncertainties than those of the present power systems. Power markets significantly deviate from standard economics since the demand side is largely disconnected from the market, i.e. it is not price responsive, and it exhibits uncertain, stochastic behavior. Furthermore, since electrical energy cannot be efficiently stored in large quantities, production has to meet these rapidly changing demands in real-time. In future power systems, efficient real-time power balancing schemes will become crucial and even more challenging due to the significant increase of uncertainties by large-scale integration of renewable sources. Physical and security limits on the maximal power flows in the lines of power transmission networks represent crucial system constraints, which must be satisfied to protect the integrity of the system. Creating an efficient congestion management scheme for dealing with these constraints is one of the toughest problems in the electricity market design, as the line power flows are characterized by complex dependencies on nodal power injections. Efficient congestion control has to account for those limits by adequately transforming them into market signals, i.e. into electricity prices. One of the main contributions of this thesis is the development of a novel dynamic, distributed feedback control scheme for optimal real-time update of electricity prices. The developed controller (which is called the KKT controller in the thesis) reacts on the network frequency deviation as a measure of power imbalance in the system and on measured violations of line flow limits in a transmission network. The output of the controller is a vector of nodal prices. Each producer/consumer in the system is allowed to autonomously react on the announced price by adjusting its production/consumption level to maximize its own benefit. Under the hypothesis of global asymptotic stability of the closed-loop system, the developed control scheme is proven to continuously balance the system by driving it towards the equilibrium where the transmission power flow constraints are satisfied, and where the total social welfare of the system is maximized. One of the advantageous features of the developed control scheme is that, to achieve this goal, it requires no knowledge of marginal cost/benefit functions of producers/consumers in the system (neither is it based on the estimates of those functions). The only system parameters that are explicitly included in the control law are the transmission network parameters, i.e. network topology and line impedances. Furthermore, the developed control law can be implemented in a distributed fashion. More precisely, it can be implemented through a set of nodal controllers, where one nodal controller (NC) is assigned to each node in the network. Each NC acts only on locally available information, i.e. on the measurements from the corresponding node and on the information obtained from NC’s of the adjacent nodes. The communication network graph among NC’s is therefore the same as the graph of the underlying physical network. Any change is the network topology requires only simple adjustments in NC’s that are local to the location of the change. To impose the hard constraints on the level to which the transmission network lines are overloaded during the transient periods following relatively large power imbalances in the system, a novel price-based hybrid model predictive control (MPC) scheme has been developed. The MPC control action adds corrective signals to the output of the KKT controller, i.e. to the nodal prices, and acts only when the predictions indicate that the imposed hard constraint will be violated. In any other case, output of the MPC controller is zero and only the KKT controller is active. Under certain hypothesis, recursive feasibility and asymptotic stability of the closed-loop system with the hybrid MPC controller are proven. Next contribution of this thesis is formulation of the autonomous power networks concept as a multilayered operational structure of future power systems, which allows for efficient large-scale integration of DG and smallscale consumers into power and ancillary service markets, i.e. markets for different classes of reserve capacities. An autonomous power network (AN) is an aggregation of networked producers and consumers, whose operation is coordinated/controlled with one central unit (AN market agent). By performing optimal dispatching and unit commitment services, the main goals of an AN market agent is to efficiently deploy the AN’s internal resources by its active involvement in power and ancillary service markets, and to optimally account for the local reliability needs. An autonomous power network is further defined as a major building block of power system operation, which is capable of keeping track of its contribution to the uncertainty in the overall system, and is capable of bearing the responsibility for it. With the introduction of such entities, the conditions are created that allow for the emergence of novel, competitive ancillary service market structures. More precisely, in ANs based power systems, each AN can be both producer and consumer of ancillary services, and ancillary service markets are characterized by double-sided competition, what is in contrast to today’s single-sided ancillary service markets. One of the main implications of this novel operational structure in that, by facilitating competition, it creates the strong incentive for ANs to reduce the uncertainties and to increase reliability of the system. On a more technical side, the AN concept is seen as decentralization and modularization approach for dealing with the future, large scale, complex power systems. As additional contribution of this thesis, motivated by the KKT controller for price-based real-time power balancing and congestion management, the general KKT control paradigm is presented in some detail. The developed control design procedure presents a solution to the problem of regulating a general linear time-invariant dynamical system to a time-varying economically optimal operating point. The system is characterized with a set of exogenous inputs as an abstraction of time-varying loads and disturbances. Economic optimality is defined through a constrained convex optimization problem with a set of system states as decision variables, and with the values of exogenous inputs as parameters in the optimization problem. A KKT controller belongs to a class of dynamic complementarity systems, which has been recently introduced and which has, due to its wide applicability and specific structural properties, gained a significant attention in systems and control community. The results of this thesis add to the list of applications of complementarity systems in control.

Wind power simulation model for reliability evaluation

Abstract: The rapidly increasing contribution of wind power to electric power generation around the world has motivated a need to develop more widely applicable methodologies for evaluating the actual benefits of adding wind turbines to traditional power generating systems. Reliability and cost evaluation of wind generation systems requires simulation of long-term chronological wind speed data for specified geographical wind farm sites. The main steps to construct the wind speed simulation model are presented in this paper. It is important that the developed models maintain the main statistical characteristics of the wind farm locations. Wind speed data from two wind sites are used to illustrate the model. The results of wind data simulation, power output profile, and power system risk evaluation are presented and compared using different types of wind models at different wind farm sites. The objective is to derive a general and appropriate model for reliability evaluation of power systems containing wind sources

Consideration of wind farm wake effect in power system dynamic simulation

Abstract: This paper deals with the modelling of the wake effect in wind farms for use in dynamic power system simulation software. First, basic relationships describing the leeside wind speed as a function of the incoming wind speed under ideal conditions are put together. Through aerodynamic efficiency considerations the ideal power-coefficient of the turbine is then related to the actual power coefficient provided by the turbine manufacturer. Finally, mathematical expressions are formulated for the wake wind speed in relation to location within the park and the wind direction. The model thus obtained is implemented on a power system simulation package as an additional feature. Together with the full range of capabilities of the package for steady state as well as dynamic analysis, the model enables an in-depth study of the wake effect and its impact on the farm in terms of output power and its interactions with the network. Some results illustrating the impact of the wake effect on steady state system operation have been presented.

Electric ship power system integration analyses through modeling and simulation

Abstract: The Center for Electromechanics (CEM) at the University of Texas is engaged in the development of a comprehensive power system model in order to address several challenging issues facing the development of a viable and effective integrated power system architecture for future naval platforms. The power system under consideration reflects the notional DD power system architecture and is developed in the Matlab/Simulink environment. System components such as motors and generators are modeled using parameters based on actual machine design and analysis work performed at CEM. Simulation results of models including permanent-magnet propulsion motors and generators with simple reconfiguration scenarios simulating loss and recovery of power to propulsion and vital loads are presented.

Latency techniques for time-domain power system transients simulation

Abstract: This work presents the techniques derived for an efficient and accurate latency exploitation of electric networks using time-domain transients simulation software, such as the "electromagnetic transients program" (EMTP). Latency exploitation is related to the capability of numerically solving the differential equations governing the behavior of electric networks with different integration steps. With this approach, the limitations of a single fixed size integration step, as required by EMTP-type programs, can be overcome, resulting in a decreased number of numerical operations for a given total simulation time. Using a network partitioning and recombination technique, latency exploitation is achieved using noniterative solutions. Results are shown for networks consisting exclusively of lumped elements and networks with transmission lines and are compared with those obtained from conventional EMTP simulations.

Capacitor placement in three-phase distribution systems with nonlinear and unbalanced loads

Abstract: The problem of choosing optimal locations and sizes for shunt capacitors in distribution systems is addressed. The objective of the capacitor placement procedure is not only to minimise the power losses along distribution feeders, but also to make sure that these capacitors will have the minimum possible impact on the harmonic distortion of bus voltages in the system. Furthermore, the fact that distribution systems can operate under unbalanced loading conditions, means that the optimisation will have to account for any unbalances in the system. An optimisation program, which successfully solves the problem is developed and tested. Results obtained by simulation of a distribution test system under various operating conditions, are presented to validate the proposed solution methods.

Integral planning of primary-secondary distribution systems using mixed integer linear programming

Abstract: Summary form only given. Important research effort has been devoted to the topic of optimal planning of distribution systems. However, in general it has been mostly referred to the design of the primary network, with very modest considerations to the effect of the secondary network in the planning and future operation of the complete grid. Relatively little attention has been paid to the optimization of the secondary grid and to its effect on the optimality of the design of the complete electrical system, although the investment and operation costs of the secondary grid represent an important portion of the total costs. Appropriate design procedures have been proposed separately for both the primary and the secondary grid, however in general both planning problems have been presented and treated as different, almost isolated problems, setting aside with this approximation some important factors that couple both problems, such as the fact that they may share the right of way, use the same poles, etc., among other factors that strongly affect the calculation of the investment costs. The main purpose of this work is the development and initial testing of a model for the optimal planning of a distribution system that includes both the primary and the secondary grids, so that a single optimization problem is stated for the design of the integral primary-secondary distribution system that overcomes these simplifications. The mathematical model incorporates the variables that define both the primary as well as the secondary planning problems and consists of a mixed integer-linear programming problem that may be solved by means of any suitable algorithm. Results are presented of the application of the proposed integral design procedure using conventional mixed integer-linear programming techniques to a real case of a residential primary-secondary distribution system consisting of 75 electrical nodes.

Damping power system oscillations using a fuzzy logic based unified power flow controller

Abstract: This paper presents a new control method based on fuzzy logic technique to control a unified power flow controller (UPFC) installed in a single-machine infinite-bus power system. The objective of the fuzzy logic based UPFC controller is to damp power system oscillations. Phillips-Herffron model of a single-machine power system equipped with a UPFC is used to model the system. The fuzzy logic based UPFC controller is designed by selecting appropriate controller parameters based on the knowledge of the power system performance. Simple fuzzy logic controller using mamdani-type inference system is used. The effectiveness of the new controller is demonstrated through time-domain simulation studies. The results of these studies show that the designed controller has an excellent capability in damping power system oscillations

Method of Combined Static and Dynamic Analysis of Voltage Collapse in Voltage Stability Assessment

Abstract: Different analysis methods have been used for voltage stability assessment. In comparison with static analysis methods, little work has been done on dynamic analysis of large interconnected power systems. Voltage instability can be studied effectively with a combination of static approaches and time simulations. This paper discusses voltage stability assessment using mixed static and dynamic techniques. Using static methods, a voltage stability based ranking is carried out to specify faint buses, generators and links in power system. The system is analyzed for most severe conditions. Then, time domain simulation is performed for the conditions determined by voltage instability ranking. The mixed approach benefits from advantages of both static and dynamic analyses. The New England (IEEE 39 bus) system was used as a test system

Analysis and Comparison on Several Kinds of Models of Cascading Failure in Power System

Abstract: Highly interconnected power grid is developing more and more complex. Cascading failure in such complex power grid, which can be triggered by some disturbances, will have global catastrophic effects over the entire networks. So the research on cascading failure of complex power grid is of significant concern. The foundation of such research is the modeling. In this paper, the mechanism of cascading failure in power grid is firstly explained. Then respectively from the point of view in artificial power system and complex network, several existing models are introduced and commented. And some feasible methods, which should be paid more attention to in the future, in order to prevent and control cascading failure are also analyzed and discussed

Probabilistic small signal analysis using Monte Carlo simulation

Abstract: This paper presents a Monte Carlo approach for probabilistic small signal stability (PSSS) analysis in electric power systems with uncertainties. The uncertainties considered include both generation and demand in power systems, though others, such as parameter changes of network components, can be added as well. Probabilistic models of these uncertainties are constructed considering their characteristics. Subsequently, probabilistic small signal stability assessment of the power system is carried out based on eigenvalue analysis via Monte Carlo Simulation. The proposed method is tested by analysing the eigenvalues of two benchmark systems, where stable, unstable and oscillation modes are identified in the probabilistic context. In addition, local and inter-area modes of electro-mechanical oscillation are classified. Relevant discussion of stability enhancement using the proposed approach has been presented as well. The proposed method aims at providing a comprehensive characterization of system stability which can be very helpful in applications, such as system operation and expansion planning in the deregulation with many uncertainties.

Modeling the sequential switching shunt series regulator

Abstract: This letter characterizes, in terms of the bandwidth and limit cycle frequency of its constituent subsystems, the sequential switching shunt series regulator -S/sup 4/R, a high-efficiency, low-mass and volume power cell devised to power the next generation of regulated power buses in telecommunication spacecrafts. Transconductance power source modeling is used to obtain linear and nonlinear models. These are used to establish a design control strategy which involves the dynamic response in large load requirements or at the end of the satellite life. Simulations and experimental results are also given to demonstrate the validity of the model.

Reactive power and voltage control of the Nigerian grid system using micro-genetic algorithm

Abstract: In this paper, a micro-genetic based approach to the optimization of reactive power and voltage profiles improvement and real power loss minimization is presented. The reactive power control devices such as generators, tap positions of on-load tap changer of transformers, shunt reactors are used to correct voltage limits violations while simultaneously reducing the system real power losses. Genetic algorithms (GAs) are well-known global search techniques anchored on the mechanisms of natural selection and genetics. Because of the time intensive nature of the conventional GA, the micro-GA is proposed as a more time efficient alternative. The feasibility and effectiveness of the developed algorithm is tested and verified on the Nigerian grid power system for three case studies scenarios preset in the power world simulator. The far-reaching simulation results that validate the effectiveness of the developed tool are presented and discussed in depth.

Optimal metering systems for monitoring power networks under multiple topological scenarios

Abstract: This work presents a methodology for designing optimal metering systems for real-time power system monitoring, taking into account different topologies that the network may experiment Genetic algorithms are employed to achieve a trade-off between investment costs and reliability of the state estimation process under many different topology scenarios This is done by formulating a fitness function where the cost of the metering system is minimized, while no critical measurements and/or critical sets are allowed in the optimal solution An efficient algorithm for the identification of critical measurements and sets (irrespective of state estimation runs) is employed during the evaluation of the fitness function Simulation results illustrate the performance of the proposed method

Neural networks approach to online identification of multiple failures of protection systems

Abstract: In complex emergency situations, failed protection relays and circuit breakers (CBs) have to be identified in order to begin the restoration process of a power system. This paper proposes a novel neural-network approach to identify multiple failures of protection relays and/or CBs. The approach uses information received from protection systems in the form of alarms and is able to deal with incomplete and distorted data. All possible emergencies are simulated and analyzed separately for each section of a power system. Taking into consideration supervisory control and data-acquisition system malfunctions, the corrupted patterns are used to train neural networks. The preliminary classification of emergencies into two different classes is applied to improve the system's performance. The evaluation of results shows that the overall error rate does not exceed 5%. The developed system was tested on a real power system.

Stochastic unit commitment in hydro-thermal power production planning

Abstract: Economic needs and the ongoing liberalization of European electricity markets stimulate the interest of power utilities in developing models and optimization techniques for the generation and trading of electric power under uncertainty. Utilities participating in deregulated markets observe increasing uncertainty in load (i.e., demand for electric power) and prices for fuel and electricity on spot and contract markets. The mismatched power between actual and predicted demand may be supplied by the power system or by trading activities. The competitive environment forces the utilities to rate alternatives within a few minutes. In this chapter, we describe a mathematical model for optimal short term operation and trading of a hydro-thermal based electric utility, which is usually called unit commitment problem because of the important role of the commitment or on/off decisions. Furthermore, we present a methodology for modelling the stochastic data process in form of a scenario tree and report on a Lagrangian-based decomposition strategy for solving the optimization model. We also provide some numerical experience obtained from test runs on realistic data from the German utility Vereinigte Energiewerke AG (VEAG). The optimization model has emerged from a collaboration with engineers of VEAG. For our tests we use a configuration of the VEAG system consisting of 25 (coal-fired, gas-burning) thermal units and seven pumped storage hydro units. Its total capacity is about 13,000 megawatts (MW), including a hydro capacity of 1,700 MW; the peak loads of the system are about 8,600 MW. In contrast to other hydro-thermal based utilities the amount of installed pumped storage capacity enables the inclusion of pumped storage plants into the optimization. It is an additional feature of the VEAG system that, for a weekly planning period, inflows to reservoirs are negligible. There is a growing number of contributions to stochastic power system optimization with emphasis on modelling aspects and solution methods. For stochastic models including commitment decisions see Bacaud et al. (2001), Bogensperger (1999), Caroe and Schultz (1998), Carpentier et al. (1996), Conejo et al. (1999), Dentcheva and Romisch (1998), Growe∗Institute of Mathematics, Humboldt-University Berlin, 10099 Berlin, Germany (nicole@mathematik.huberlin.de, romisch@mathematik.hu-berlin.de).

Multiple harmonic source detection and equipment identification with cascade correlation network

Abstract: This paper presents the design of a harmonic source detection system with a cascade correlation network (CCN). Current-injection-based harmonic power flow was used to calculate bus voltages and total harmonic distortion (THD). THD of voltages is used as indices for meter placement in the power network. At metering buses, it shows that the harmonic components of voltages under various loads would form particular patterns in the frequency domain, and can be used to create training examples for CCN. Good meter planning is helpful to reduce the number of meters and training examples. With an IEEE 14-bus power system, computer simulations were conducted to show the effectiveness of the proposed system.