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This paper presents a new non-deterministic approach for multiyear distribution network reinforcement planning (DNRP) considering the uncertainty sources pertaining to loads, electricity prices, investment costs, and operation costs. Accordingly, the underlying idea of the information-gap decision theory (IGDT) is used to obtain a robust solution protected against different realizations of each uncertain variable lying in its robust region. The proposed model is capable of adjusting the robustness of the optimal solution in terms of a specific parameter designated as the budget of uncertainty. As the uncertain loads, investment and operation costs competitively tend to maximize their robust regions for a particular value of the budget of uncertainty, the normalized normal constraint (NNC) method as a proficient multi-objective optimization method is exploited in this paper to solve the proposed multiobjective IGDT-based DNRP (IGDT-DNRP) model. Mainly, the NNC method presents a set of Pareto optimal solutions rather than a single optimal solution. Accordingly, a posteriori out-of-sample analysis is introduced in this paper to find the best solution among the set of Pareto optimal solutions. The proposed IGDT-DNRP model is implemented on the IEEE 33-bus distribution network under different circumstances. Simulation results illustrate the effectiveness of the proposed nondeterministic approach. [ABSTRACT FROM AUTHOR]

Recent years have witnessed significant interest in convex relaxations of the power flows, with several papers showing that the second-order cone relaxation is tight for tree networks under various conditions on loads or voltages. This paper shows that ac-feasibility, i.e., to find whether some generator dispatch can satisfy a given demand, is NP-hard for tree networks. [ABSTRACT FROM AUTHOR]

Risk of blackouts is more than expected and must be considered in the power system studies. The interest of this paper is to minimize the blackouts risk during minimizing the costs in probabilistic transmission expansion planning (TEP). In this paper, a long-term reliability analysis, which was developed by self-organized criticality theory, is used in a multi-objective optimization to include risk of blackouts in TEP. The objective functions are costs and expected energy not supplied. Also, a new formulation for calculating transmission operating cost as a part of cost function is proposed. The problem is solved by a multi-objective particle swarm optimization to find an optimal Pareto set from which the decision-maker can choose the most desirable one, regarding existing budget. The proposed method is applied to the IEEE 118-bus test system to investigate its applicability and scalability. The results are compared with security-constrained TEP, which uses famous deterministic criterion known as N-1. The proposed approach produces more efficient plans for suppressing cascading blackouts with less network investment. Moreover, the results provide motivation for considering the risk of cascading blackouts in TEP, which afford substantial saving to society. [ABSTRACT FROM AUTHOR]

The Endesa Company is the main power utility in Spain. One of the main concerns of power distribution companies is energy loss, both technical and non-technical. A non-technical loss (NTL) in power utilities is defined as any consumed energy or service that is not billed by some type of anomaly. The NTL reduction in Endesa is based on the detection and inspection of the customers that have null consumption during a certain period. The problem with this methodology is the low rate of success of these inspections. This paper presents a framework and methodology, developed as two coordinated modules, that improves this type of inspection. The first module is based on a customer filtering based on text mining and a complementary artificial neural network. The second module, developed from a data mining process, contains a Classification & Regression tree and a Self-Organizing Map neural network. With these modules, the success of the inspections is multiplied by 3. The proposed framework was developed as part of a collaboration project with Endesa. [ABSTRACT FROM PUBLISHER]

This paper presents a methodology for integrated planning of real-life medium-voltage networks based on the utility planning concepts. The research is motivated by the need to develop a methodology that would line-up with utility day-to-day businesses and could be applied in real-life. Its core is a two-stage optimization process, where the first stage solves the static investment optimization and the second stage considers operational problem. A probabilistic decision tree approach is proposed for the solution of the entire problem to consider uncertainties in the planning period. The overall formulation is given first, which is followed by details of the investment model and outlines of the proposed operation planning. The novelty of the investment problem, which determines optimal network reinforcements, is explicit modeling of network security constraints of radially operated networks, whilst considering different operating regimes. Additional novel features include modeling of real-life supply restoration rules through network reconfiguration and optimal placement of new switching devices, as well as consideration of “customer flows” on the network. Connection of new distributed generation and demand centers and construction of circuits on new corridors are also included. Two investment models are formulated as mixed-integer nonlinear optimization problems, tested on several MV networks and compared with established methods. The proposed operational problem is solved in two stages, quality-of-supply and operation cost optimization. Computational aspects are also presented. [ABSTRACT FROM PUBLISHER]

Distributed renewable energy resources have attracted significant attention in recent years due to the falling cost of the renewable energy technology, extensive federal and state incentives, and the application in improving load-point reliability. This growing proliferation, however, is changing the traditional consumption load curves by adding considerable levels of variability and further challenging the electricity supply–demand balance. In this paper, the application of microgrids in effectively capturing the distribution network net load variability, caused primarily by the prosumers, is investigated. Microgrids provide a viable and localized solution to this challenge, while removing the need for costly investments by the electric utility on reinforcing the existing electricity infrastructure. A flexibility-oriented microgrid optimal scheduling model is proposed and developed to coordinate the microgrid net load with the aggregated consumers/prosumers net load in the distribution network with a focus on ramping issues. The proposed coordination is performed to capture both inter- and intra-hour net load variabilities. Numerical simulations on a test distribution feeder with one microgrid and several consumers and prosumers exhibit the effectiveness of the proposed model. [ABSTRACT FROM PUBLISHER]

The requirements concerning reliability in power supply are high. This paper treats the issue of system adequacy, i.e., there should be enough installed capacity to meet the load with an acceptable reliability. The challenge in a liberalized market is that the utilization time of rarely used peak units is so low that they require extremely high prices in order to be profitable. This has led to different methods, including the creation of capacity markets. The aim of this paper is to analyze the connection between peak prices, system reliability, required amount of subsidized capacity, i.e., the volume of the capacity market. In the studied market setup, only some selected units, so-called "reserve plants", receive a capacity payment. The paper also provides an example concerning change of capacity market volume in presence of wind power. [ABSTRACT FROM AUTHOR]

This paper addresses the problem of a multiyear security constrained hybrid generation-transmission expansion planning. It is assumed that the overall generation requirements of a network are known along the planning horizon, but their allocations are unknown. Moreover the fuel cost throughout the net- work is not uniform. By allocating the overall generation capacity among the grid nodes, and determining the new transmission element additions along the planning horizon, the overall cost of the system is minimized. The problem is formulated as a mixed integer nonlinear programming problem, which for a large-scale system is very difficult to solve. In this paper a new constructive heuristic approach is proposed, so that the problem can be readily solved. To assess the capabilities of the proposed approach, two networks are studied: the Garver test grid as a small grid and the Iranian power grid as a large-scale grid. [ABSTRACT FROM AUTHOR]

This paper investigates the reliability effects on a composite generation and transmission system associated with the addition of large-scale wind energy conversion systems (WECS) using the state sampling Monte Carlo simulation technique. Three types of composite system were developed to represent the general conditions that exist in practical systems and used to conduct the studies presented in this paper. Load point and system indices for the three types of test systems are presented to illustrate the impact of adding wind farms in various system locations and the effect of varying the degree of wind speed correlation. The contributions of large-scale wind farms considering different degrees of wind speed correlation to the reliability performance of an electric power system are quantified in this paper. [ABSTRACT FROM AUTHOR]

The paper applies the well-known red-green-blue (RGB) coloring method to visualize traveling waves initiated by switching events or faults occurring in power systems. The three-phase voltage profile along a given transmission line is obtained first. This profile is then converted into a colored picture by assigning different colors to phase signals according to their intensity. An interesting outcome of repeating this process for each time step is the emergence of the Bewley diagram [1] which is commonly used to illustrate the behavior of traveling waves in space-time. The main contribution of the paper is to show that RGB coloring of phase signals reveals essentially the same profile as the one obtained by using the aerial mode of the signals transformed into the modal domain. Furthermore, it discusses how this result can possibly be useful in applications such as fault location. [ABSTRACT FROM AUTHOR]

This paper studies the minimum load cutting problem existing in the process of transmission network expansion planning when load is uncertain and expressed in interval number. The interval most minimum load cutting model is established and can be solved to get the maximum value of the minimum load cutting number when load is interval uncertain. The solution can be used to evaluate the safety of the planning schemes under interval uncertainty and guide the new plans' making under interval load. The load values in the optimal solution of this problem have been proved to be at their lower or upper limits. Two different algorithms are proposed to solve this model. One is better in being capable of getting global optimal solution, while the other is better in calculation speed. Both of them are compared with two traditional methods that are generally used to evaluate the system's safety under uncertainty in aspects of precision and speed. This evaluation method is applied to the greedy randomized adaptive search procedure algorithm to solve the transmission expansion planning problem under interval load. The case results show the rightness and validity of the model and algorithms proposed in this paper. [ABSTRACT FROM AUTHOR]

Asset management is an important activity in present day distribution system planning and operation. Utilities are constantly striving to optimize the use of resources available for maintenance while ensuring system reliability is within satisfactory limits. This paper proposes a method to allocate maintenance resources to various distribution system assets. To determine the effects of maintenance, a predictive reliability assessment tool is developed. This paper describes the model on which this tool is based. The results obtained from reliability assessment can be used along with an optimizer to allocate resources to various maintenance tasks in a distribution system. [ABSTRACT FROM AUTHOR]

Conventional measurement and verification for non-interval metered, direct load control (DLC) programs bidding into wholesale electricity markets usually requires a PURPA-compliant load research study. This requirement con- tributes to high operating costs and has been a factor in recent reductions in the amount of emergency demand response available to regional transmission system operators. This paper describes. a collaborative effort by PJM members to determine whether regional modeling using pooled historical data could satisfy DLC measurement and verification (M&V) requirements without sacrificing estimation accuracy. This paper also describes how PJM incorporated the regional "deemed savings estimates" into its Load Data Systems Manual. This paper concludes that regional approaches to MଦV could yield large cost savings for DLC resource providers around the country. [ABSTRACT FROM AUTHOR]

This paper is the first of a two-part paper on optimal distribution system planning. The horizon distribution planning problem and optimal distribution system model formulation are described. The horizon planning mission is to minimize future costs by determining optimal design parameters given assumptions about the future. Prior work addressed short-range and expansion planning of subsets or combinations of design parameters. The many distribution requirements and associated constraints inhibited an all-inclusive evaluation of total horizon design requirements for the 20+ year period. The proposed model and optimization formulation provides a generalized horizon planning approach and introduce a fully functioning comprehensive horizon planning model using a perspective that encompasses all necessary parameters and constraints. Parameters include: substation and distribution transformer capacities; number, size, and lengths of distribution feeders and secondary conductors; and primary voltage class. Optimal design voltage drops and reliability indices are determined. The horizon planning optimization application is described and solved in the second companion paper using continuous constrained nonlinear programming methods. The application is demonstrated with Snohomish PUD case studies. [ABSTRACT FROM AUTHOR]

This paper evaluates the usefulness of publicly available electricity market information in forecasting the hourly Ontario energy price (HOEP). In order to do so, relevant data from Ontario and its neighboring electricity markets, namely, New York, New England, and PJM electricity markets, are investigated, and a final set of explanatory variable candidates that are available before real-time are selected. Multivariate transfer function and dynamic regression models are employed to relate HOEP behavior to the selected explanatory variable candidates. Univariate ARIMA models are also developed for the HOEP. The HOEP models are developed on the basis of two forecasting horizons, i.e., 3 h and 24 h, and forecasting performance of the multivariate models is compared with that of the univariate models. The outcomes show that the market information publicly available before real-time can be used to improve HOEP forecast accuracy to some extent; however, unusually high or low prices remain unpredictable, and hence, the available data cannot lead to significantly more accurate forecasts. Nevertheless, the generated forecasts in this paper are significantly more accurate than currently available HOEP forecasts. To analyze the relatively low accuracy of the HOEP forecasts, comparisons are made with respect to ARIMA models developed for locational marginal prices (LMPs) of Ontario's three neighboring markets, and price volatility analyses are presented. [ABSTRACT FROM AUTHOR]

This paper presents a new approach to the fuzzy unit commitment problem using the absolutely stochastic simulated annealing method. In every iteration, a solution is taken with a certain probability. Typically in the simulated annealing minimization method, a higher cost feasible solution is accepted with temperature-dependent probability, but other solutions are accepted deterministically. However, in this paper, all the solutions, both higher and lower cost, are associated with acceptance probabilities, e.g., the minimum membership degree of all the fuzzy variables. Be- sides, the number of bits flipping is decided by the linguistic fuzzy control. Excess units with system-dependent distribution handle constraints efficiently and reduce overlooking the optimal solution. To reduce the economic load dispatch calculations, a sign bit vector is introduced with imprecise calculation of the fuzzy model as well. The proposed method is tested using the reported problem data sets. Simulation results are compared to previous reported results. Numerical results show an improvement in solution cost and time compared to the results obtained from powerful algorithms. [ABSTRACT FROM AUTHOR]

In this paper, an effective ac corrective/preventive contingency dispatch over a 24-h period is proposed based on security-constrained unit commitment (SCUC) model. The SCUC model includes unit commitment, ac security-constrained optimal power flow (SCOPF), and load shedding (LS) for steady state and contingencies. The objective of this SCUC model is to obtain the minimum bid-based system operating cost while maintaining the system security. The prevailing generation constraints, such as hourly power demand, system reserves, fuel and emission limits, ramp up/down limits, and minimum up/down time limits, are included in this model. In addition, system constraints such as time-limited emergency controls for a given contingency and ac network security limits are taken into account. The proposed ac solution for the hourly scheduling of generating units is based on Benders decomposition. Case studies with the six-bus system, the IEEE 118-bus test system, and 1168-bus system are presented in detail in this paper. [ABSTRACT FROM AUTHOR]

In a competitive electricity market, the oligopoly structure of the market and the network constraints may produce results far from the perfect competition. This paper presents a comprehensive approach to evaluate the performances of the electricity markets with network representation in presence of bidding behavior of the producers in a pool system. A supply function strategic bidding model for the producers is introduced, and then different scenarios in terms of bidding behavior and network constraints are studied and compared on the basis of a set of microeconomic metrics. The aim of the paper is to assess, throughout a set of proper indices, the level of competition in a network-constrained market considering strategic behavior of the producers. The approach proposed gives the possibility to assess the different weight of strategic behavior of the producers and of the network constraints in distorting the market performances from its perfect competition equilibrium. From such an analysis, the worsening of the market efficiency and performances, due to the joint effects of the nonperfect competition and the network constraints, may be assessed and quantified, providing information on the adequacy of the grid considered for accommodating a competitive market. The exploitation of the proposed metrics for the market analysis is shown with reference to the IEEE 30-bus test system with demand elasticity explicitly represented. [ABSTRACT FROM AUTHOR]

In a restructured power market, the independent system operator (ISO) executes the security-constrained unit commitment (SCUC) program to plan a secure and economical hourly generation schedule for the day-ahead market. This paper introduces an efficient SCUC approach with ac constraints that obtains the minimum system operating cost while maintaining the security of power systems. The proposed approach applies the Benders decomposition for separating the unit commitment (UC) in the master problem from the network security check in sub- problems. The master problem applies the augmented Lagrangian relaxation (LR) method and dynamic programming (LW) to solve UC. The subproblem checks ac network security constraints for the UC solution to determine whether a converged and secure ac power flow can be obtained. If any network violations arise, corresponding Benders cuts will be formed and added to the master problem for solving the next iteration of UC. The iterative process will continue until ac violations are eliminated and a converged optimal solution is found. In this paper, a six-bus system and the IEEE 118-bus system with 54 units are analyzed to exhibit the effectiveness of the proposed approach. [ABSTRACT FROM AUTHOR]

This paper deals with power system restoration and discusses the connection of pumped storage loads to restoration paths. This new strategy allows avoiding any disturbance to customers during field tests of restoration paths and improves as well the reliability of restoration plans. The first application of the new strategy concerned the field test of a new path in central Italy. This paper reports the test and analyzes the main novel features of the considered path: complete separation from subtransmission and distribution networks and use of pumped storage loads during its energization. These aspects and their consequences are discussed with reference to both field testing of restoration paths and effectiveness of system restoration. [ABSTRACT FROM AUTHOR]

In this paper, we address the issue of quantifying effects of model uncertainty on transmission security in a power market. The paper addresses two types of uncertainties: 1) structural (e.g., branch outages), which are modeled by contingency scenarios, and 2) perturbations of model parameters (e.g., branch impedance), which are described by sensitivity analysis. The paper embeds these considerations in an optimization procedure that checks if transmission security is maintained and, when necessary, generates minimal corrections in existing contractual transactions that ensure security. Given our interest in real-time applications, we consider problem formulations guaranteeing solution existence and global optimality. A detailed sensitivity analysis based on approximate matrix inversion and linear programming perturbation theory is performed. The paper proposes a linearized ac power flow model to describe the transmission network. The model is studied on a benchmark example of the New England/New York interconnection with 68 nodes. [ABSTRACT FROM AUTHOR]

This paper presents a simulation study about the co- ordination and interaction of advanced power electronic devices working in close electrical proximity. In particular, three major power quality devices (PQDs)--an advanced static VAR compensator, a dynamic voltage restorer, and a high-speed transfer switch as well as their combined performance--are modeled and studied in detail using ATP-EMTP. The paper addresses potential problems related to the PQD's combined operation, in addition to coordination issues. Comparison between simulation results and field measurements of individual PQD's are also presented. [ABSTRACT FROM AUTHOR]

In a restructured power market, the independent system operator (ISO) executes the security-constrained unit commitment (SCUC) program to plan a secure and economical hourly generation schedule for the day-ahead market. This paper introduces an efficient SCUC approach with ac constraints that obtains the minimum system operating cost while maintaining the security of power systems. The proposed approach applies the Benders decomposition for separating the unit commitment (UC) in the master problem from the network security check in sub- problems. The master problem applies the augmented Lagrangian relaxation (LR) method and dynamic programming (DP) to solve UC. The sub-problem checks ac network security constraints for the UC solution to determine whether a converged and secure ac power flow can be obtained. If any network violations arise, corresponding Benders cuts will be formed and added to the master problem for solving the next iteration of UC. The iterative process will continue until ac violations are eliminated and a converged optimal solution is found. In this paper, a six-bus system and the IEEE 118-bus system with 54 units are analyzed to exhibit the effectiveness of the proposed approach. [ABSTRACT FROM AUTHOR]

Traditional methods for regulating electricity distribution grids have several weaknesses hi terms of incentives, risk allocation, consumer preferences, and the value of reliability. Rate of Return and Performance Based Regulation do not provide incentives for both cost efficiency and quality of service. These regulatory structures also allocate the risk of outages almost entirely to consumers and fail to Incorporate consumer preferences for reliability/service quality Additionally, investments in system reliability are not explicitly valued. This paper proposes an insurance scheme for reliability as a possible solution. Reliability Insurance provides economically efficient investment incentives and alleviates consumers' reliability risk. Consumers provide economic signals to the distribution provider for their desired quality of service through insurance contracts. The value of reliability to consumers is thereby made transparent, allowing Distribution Companies (DisCo's) to make efficient investment decisions. Insurance also allocates outage risk to the DisCo (which controls the system), instead of consumers (who have little or no control over reliability). Reliability insurance effectively unbundles delivery and reliability services and enables consumers to receive differentiated reliability based upon their value for this service. This paper describes the potential for reliability insurance to improve both efficiency and risk allocation compared to conventional regulatory structures. [ABSTRACT FROM AUTHOR]

Many problems have appeared with the practical implementation of restructured electrical business in the U.S. and European Union such as lack of generation, network constraints, etc. A good example of these problems is the scarce participation of the demand in the electricity markets-energy, reserve, and other ancillary services-problems that could be solved through new demand responsive programs, aimed to replace the traditional demand side management programs into voluntary demand participation programs. A methodology for the generation of demand side bids and offers in large customer facilities and a real application to a university customer is presented in this paper. The methodology is based on the knowledge of the physical processes involved in the electricity consumption and on the flexibility of the required supply. The result of the methodology proposed is a set of demand packages that can be used to participate in different electricity markets, whose possibilities-in the market arena-will be explored in a consequent paper. [ABSTRACT FROM AUTHOR]

A method is proposed in this paper to select the input signals for both single and multiple flexible ac transmission system (FACTS) devices in small and large power systems. Different input- output controllability analyses are used to assess the most appropriate input signals (stabilizing signal) for the static var compensator (SVC), the static synchronous compensator (SSSC), and the unified power-flow controller (UPFC) for achieving good damping of interarea oscillations. The study presented in this paper is carried out on one small system with one FACTS device at a time; and one large system equipped with the SVC, the SSSC, and the UPFC. [ABSTRACT FROM AUTHOR]

This paper addresses the allocation of electrical losses in distribution networks with embedded generation, in a liberalized environment. The nonlinear nature of the issue, the loss changes due to voltage variation and, specially, the contribution of embedded generation to loss variation are considered. The proposed method is based on tracing the real and imaginary parts of the currents and has two steps. First, the loses in the distribution network, in the absence of embedded generation, are allocated to the consumers (or their providers). Second, the variations in the losses that result from the influence of embedded generation are allocated to the generators. These variations are a measure of the avoided or added costs related to losses. In the allocation process, made in a branch basis, both real and reactive powers ate considered. The methodology presented in this paper can be used to evaluate embedded, generation incentives or to design tariffs for the use of the distribution network. [ABSTRACT FROM AUTHOR]

A detailed AC OPF-based formulation for procuring, pricing, and settling energy and ancillay service in simultaneous auctions by integrated market systems is presented. The paper provides clear definitions of locational marginal prices for energy and ancillary service marginal prices in terms of Lagrange multipliers. The characteristics of the prices are analyzed especially when economic substitution among ancillary services is required. The paper also evaluates the conditions under which opportunity costs are incurred to units that provide ancillary services. It is particularly shown that the intuitive belief that the provision of regulation down service does not incur opportunity cost to the provider, in general, is not true. [ABSTRACT FROM AUTHOR]

This paper proposes a novel approach to energy exchange between electric vehicle (EV) load and wind generation utilities participating in the day-ahead energy, balancing, and regulation markets. An optimal bidding/offering strategy model is developed to mitigate wind energy and EV imbalance threats, and optimize EV charging profiles. A new strategy model is based on optimizing decision making of a wind generating company (WGenCO) in selecting the best option among the use of the balancing or regulation services, the use of the energy storage system (ESS) and the use of all of them to compensate wind power deviation. Energy imbalance is discussed using conventional systems, ESS, and EV-Wind coordination; results are compared and analyzed. Stochastic intra-hour optimization is solved by mixed-integer linear programming (MILP). Uncertainties associated with wind forecasting, energy price, and behavior of EV owners based on their driving patterns, are considered in the proposed stochastic method and validated through several case studies. [ABSTRACT FROM PUBLISHER]

In this paper, a new optimization framework is proposed to coordinate the operation of large, price-maker, and geographically dispersed energy storage/battery systems in a nodal transmission-constrained energy market. The energy storage units are assumed to be investor-owned and independently-operated, seeking to maximize their total profit. Various design factors are taken into consideration such as the location, size, efficiency, and charge and discharge rates of the energy storage units as well as the joint impact of the energy storage operations on the locational marginal prices. While the formulated optimization problem is originally nonlinear and hard to solve, nonlinearities are tackled both in the objective function and in the constraints and the problem is transformed into a tractable mixed-integer linear program, for which the global optimal solutions are found for the charge and discharge schedules of each energy storage unit. Both deterministic and stochastic design scenarios are addressed. Various case studies are presented. It is observed that transmission line congestion is often, but not always, desirable for the coordinated storage systems. Locational diversity, practice of arbitrage, robust design, self-scheduling versus economic bidding, and the overall power system performance are also investigated. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Existing population-based Stochastic Search Algorithms (SSAs) are too time-consuming to solve dynamic optimal power flow (OPF). The solution proposed in this paper is to accelerate SSAs with memory. Two memory schemes, the similarity retrieval scheme and the mean-based immigrants scheme, are proposed and applied together to the Differential Evolution and Particle Swarm Optimizer, which are two representatives of SSAs. Experiments are conducted on modified IEEE 30-bus and IEEE 118-bus systems with changing load buses and the objective of minimizing real power transmission loss. The results show that the proposed schemes significantly improve the performance of the two existing algorithms, and that SSAs could be practical for tracking optima of dynamic OPF. [ABSTRACT FROM AUTHOR]

Distribution systems are naturally unbalanced as a consequence of unbalanced loads and the electrical network itself, where the use of single-phase or two-phase sections is not uncommon. In addition, a detailed representation of a typical distribution system can have tens of thousands of nodes, depending on the area selected for study and whether a three-phase representation is employed. This contrasts with Transmission systems, where typical sizes in terms of number of nodes are much smaller and where a balanced (single-phase) representation is sufficient in most situations. Thus, Transmission and Distribution systems have traditionally been studied separately, but this approach is becoming increasingly inadequate for various reasons. This paper then proposes a methodology that integrates Transmission and Distribution systems into a common electrical model. At the core of the methodology there are 1) single- and three-phase models for each component (branches, transformers, loads, etc.) and 2) interchangeable balanced and unbalanced network equivalents that allow for analyzing specific areas of a given complete network. Potential gains brought about by the proposed methodology are illustrated through its application in a real-world electric system. [ABSTRACT FROM AUTHOR]

This paper presents a novel particle filter based dynamic state estimation scheme for power systems where the states of all the generators are estimated. The proposed estimation scheme is decentralized in that each estimation module is independent from others and only uses local measurements. The particle filter implementation makes the proposed scheme numerically simple to implement. What makes this method superior to the previous methods which are mainly based on the Kalman filtering technique is that the estimation can still remain smooth and accurate in the presence of noise with unknown changes in covariance values. Moreover, this scheme can be applied to dynamic systems and noise with both Gaussian and non-Gaussian distributions. [ABSTRACT FROM AUTHOR]

Stability is an important constraint in power system operation and the transient stability constrained optimal power flow (OPF) has always received considerable attention in recent years. In this paper, the defects of the existing models and algorithms around this topic are firstly analyzed, on the basis of which, a multi-objective optimization method is proposed. The basic idea of the proposed method is to model transient stability as an objective function rather than an inequality constraint and consider classic transient stability constrained OPF (TSCOPF) as a tradeoff procedure using Pareto ideology. Second, a master-slave parallel elitist non-dominated sorting genetic algorithm II is used to solve the proposed multi-objective optimization problem, the parallel algorithm shows an excellent acceleration effect and provides a set of Pareto optimal solutions for decision makers to select. An innovative weight assigning technique based on fuzzy membership variance is also introduced for a more scientific and objective optimal solution decision. Case study results demonstrate the proposed multi-objective method has many advantages, compared with traditional TSCOPF methods. [ABSTRACT FROM PUBLISHER]

Common information model (CIM) in vogue represents transmission and distribution components, and market operations in the perspective of electrical system, as unified modeling language (UML) objects. UML is object centric. CIM can offer interoperability and facilitate model exchange for large systems and is being adopted by many utilities. However, dealing effectively with multiple business processes is the backbone of the restructured power systems. Since CIM lacks chronological process sense, this has to be superimposed on CIM models, which is not easy due to inherent limitations of UML. To overcome this, this paper proposes to utilize business process modeling notation (BPMN) standards as a kind of pre-processor. BPMN is used to represent process centric interoperability requirements as business objects. UML object representation in CIM model is derived subsequently from it. The proposal is illustrated with an application use case—deriving CIM model of day-ahead market (DAM) transaction of distribution company, from its business process representation. Semantic model of DAM transaction using CIM IEC 62325 (Markets) and extensions required are presented with a sample Indian system. DAM models in BPMN and CIM can be utilized to build an efficient software application. [ABSTRACT FROM PUBLISHER]

Fast and accurate unveiling of power-line outages is of paramount importance not only for preventing faults that may lead to blackouts, but also for routine monitoring and control tasks of the smart grid, including state estimation and optimal power flow. Existing approaches are either challenged by the combinatorial complexity issues involved and are thus limited to identifying single and double line-outages or they invoke less pragmatic assumptions such as conditionally independent phasor angle measurements available across the grid. Using only a subset of voltage phasor angle data, the present paper develops a near real-time algorithm for identifying multiple line outages at the affordable complexity of solving a sparse signal reconstruction problem via either greedy steps or coordinate descent iterations. Recognizing that the number of line outages is a small fraction of the total number of lines, the novel approach relies on reformulating the DC linear power flow model as a sparse overcomplete expansion and leveraging contemporary advances in compressive sampling and variable selection. This sparse representation can also be extended to incorporate available information on the internal system and more general line-parameter faults. Analysis and simulated tests on 118-, 300-, and 2383-bus systems confirm the effectiveness of identifying sparse power line outages. [ABSTRACT FROM PUBLISHER]

This paper describes a simple probabilistic method for assessing the criticality of sections of a distribution feeder. The proposed method accounts for a number of factors such as the feeder configuration, reliability performance of each section of the feeder, number of load points of the feeder, and the number of customers at each load points. The various sections of the feeder can be ranked using any one of feeder performance indices. The list of feeder section ranking will enable distribution planners and asset managers to identify the feeder sections that have the most dominant impacts on the overall feeder performance, and therefore, investment decisions can be made effectively towards those sections. An assessment procedure illustrating how the results of the feeder section criticality are used by distribution asset managers is described. The proposed method is illustrated using one of Hydro One's long distribution feeders. [ABSTRACT FROM PUBLISHER]

In this paper, an integrated simulation—optimization approach is proposed for annual planning of power restoration workforce related to an electricity distribution company in a province of Canada. Internal and external workforces are employed to perform maintenance actions and restore power after interruptions throughout the province. According to the electricity distribution network, the province is divided into a number of work locations (WL), each having local crews to perform maintenance actions and fix power interruptions. However, determining the size of the crew in each WL over the year is challenging because of high fluctuation in interruption frequency and consequently in projected demand during the year. The frequency of interruptions is affected by various factors such as geographical location, time calendar, and particularly weather conditions. The objective is to determine the optimal combination of internal and external workforce over the year to cover the interruptions across the province with minimum cost and minimum customer interruption duration. [ABSTRACT FROM PUBLISHER]

In a competitive electricity market, consumers seek strategies to procure their energy needs from different resources (pool, bilateral contracts, and their own generation facilities) at minimum cost while controlling the risk. In this paper, a novel method is proposed to address the electricity procurement problem of large consumers using the concept of information gap decision theory. The method can be used as a tool for assessing the risk levels, considering whether a large consumer is risk-taking or risk-averse regarding its midterm procurement strategies. In the proposed method, procurement decisions are evaluated by means of two criteria. The first criterion is the robustness of the decision against experiencing high procurement costs, and the second one is the opportunity of taking advantage of low procurement costs. The pool price is considered an uncertain variable, and it is assumed that the large consumer has an estimate of the prices. In this study, two models of uncertainty are addressed for the pool price based on the concept of weighted mean squared error using a variance-covariance matrix, and the expected procurement cost is modeled using a joint normal probability distribution function. A case study illustrates the working of the proposed technique. [ABSTRACT FROM PUBLISHER]

When the wind-turbine generator system (WTGS) is connected to a radial distribution system, it can improve reliability of system by achieving the appropriate voltage regulation via its suitable control action. In this case, protective relay coordination and voltage stability issues become important factors in determining the optimal size of the WTGS, and moreover in evaluating its maximum capacity. In this paper, the proposed algorithm for selecting the optimal size of WTGS is applied based on a power flow analysis by treating the WTGS as a regulated voltage source, which is added to the related utility substation. Also, it considers the coordination time interval (CTI) of existing relays to maintain their present settings, and therefore provides an efficient solution in power system restructuring process by connecting the WTGS with its optimal size. The case study is carried out to verify that the proposed method can effectively determine the optimal size of WTGS under tightly constrained conditions resulting from voltage regulation and required protective relay coordination problems. [ABSTRACT FROM PUBLISHER]

Plug-in electric vehicles (PEVs) present environmental and energy security advantages versus conventional gasoline vehicles. In the near future, the number of plug-in electric vehicles will likely grow significantly in the world. Despite the aforementioned advantages, the connection of PEV to the power grid poses a series of new challenges for electric utilities. This paper proposes a comprehensive approach for evaluating the impact of different levels of PEV penetration on distribution network investment and incremental energy losses. The proposed approach is based on the use of a large-scale distribution planning model which is used to analyze two real distribution areas. Obtained results show that depending on the charging strategies, investment costs can increase up to 15% of total actual distribution network investment costs, and energy losses can increase up to 40% in off-peak hours for a scenario with 60% of total vehicles being PEV. [ABSTRACT FROM AUTHOR]

This paper proposes a novel schematic approach for coordinating the selection of distributed generation unit investment proposals submitted by multiple, competing, private investors to achieve maximum investor participation while complying with the technical operational limits of the local distribution company. The concept of domains and commons has been used to identify the largest transgressors to system function, and forms the basis for revisions to the investor proposals. [ABSTRACT FROM AUTHOR]

This paper proposes a methodology to achieve integrated planning and projects for secondary distribution circuits. The planning model is formulated as a mixed integer nonlinear programming problem (MINLP). In order to resolve this problem, a tabu search (TS) algorithm is used, with a neighborhood structure developed to explore the physical characteristics of specific geographies included in the planning and expansion of secondary networks, thus obtaining effective solutions as well as low operating costs and investments. The project stage of secondary circuits consists of calculating the mechanical efforts to determine the support structures of the primary and secondary distribution systems and determining the types of structures that should be used in the system according to topological and electrical parameters of the network and, therefore, accurately assessing the costs involved in the construction and/or reform of secondary systems. A constructive heuristic based on information of the electrical and topological conditions between the medium voltage and low voltage systems is used to connect the primary systems and secondary circuits. The results obtained from planning and design simulations of a real secondary system of electric energy distribution are presented. [ABSTRACT FROM AUTHOR]

This paper presents an original and effective application of support vector clustering (SVC) to electrical load pattern classification. The proposed SVC-based approach combines the calculation of the support vectors, carried out by using a classical procedure adopting a Gaussian kernel, with a specifically developed deterministic algorithm to form the clusters. This algorithm exploits the meaningful location of the bounded support vectors (BSVs) to define the outliers, identifying the clusters in function of the distance of the non-BSVs to the BSVs. Its implementation is less computationally intensive than other existing approaches and the cluster formation is driven by a single user-defined threshold. Extended comparison to other clustering methods is included to show the effectiveness of the proposed approach in grouping multidimensional load pattern data into non-overlapping clusters. This effectiveness is confirmed by the calculation of various cluster validity indicators. In particular, the most successful tasks are the identification of the outliers and the more effective formation of small numbers of clusters with respect to other methods. [ABSTRACT FROM AUTHOR]

Multistage Benders decomposition (MSBD), also known as dual dynamic programming, is a well-established technique to solve hydrothermal scheduling problems, especially for predominantly hydro systems. The MSBD methodology solves the problem by iterative forward and backward recursions, approximating the cost-to-go function for each stage by Benders cuts, as opposed to traditional dynamic programming approaches that discretize the state space at each time-step. The classical definition of the stages in the MSBD approach is to assign a stage for each time period. In this paper, we propose a new strategy to decompose the problem, where each stage comprises all variables and constraints of several time periods. Numerical results of the application of this strategy to the short- term hydrothermal scheduling problem confirm the advantages of this strategy in terms of CPU time, as compared to the classical stage definition approach. We show that there is an "optimal aggregation factor," which best balances the trade-off between solving a "larger number of shorter subproblems" and solving a "smaller number of larger subproblems." The primal and dual solutions related to different aggregation factors are also compared, and the stability of the results is confirmed. Extensions of the proposed strategy to stochastic problems are discussed. [ABSTRACT FROM AUTHOR]

Increase in power consumption can cause serious stability problems in electric power systems if there are no on- going or impending construction projects of new power plants or transmission lines. Additionally, such increase can result in large power losses of the system. In costly and environmentally effective manner to avoid constructing the new infrastructures such as power plants, transmission lines, etc., the distributed generation (DG) has been paid great attention so far as a potential solution for these problems. The beneficial effects of DG mainly depend on its location and size. Therefore, selection of optimal location and size of the DG is a necessary process to maintain the stability and reliability of existing system effectively before it is connected to a power grid. However, the systematic and cardinal rule for this issue is still an open question. In this paper, a method to determine the optimal locations of multiple DGs is proposed by considering power loss. Also, their optimal sizes are determined by using the Kalman filter algorithm. [ABSTRACT FROM AUTHOR]

This paper presents a model for the simulation of the optimal medium-term operation of a hydrothermal system. System stochastic parameters are modeled by Monte Carlo scenarios, which are solved on distributed processors. For each scenario a yearly hydrothermal scheduling (HTS) problem with hourly time resolution is formulated and solved as a large mixed integer linear program (MILP). HTS modeling includes unit commitment, start-up costs and minimum up/down time constraints. The model is applied to the Greek Power System, comprising 29 thermal units and 13 hydroplants; 100 simulation scenarios are generated and solved on 18 distributed processors. Test results include both medium-term objectives, such as reservoir water management, and short-term decisions such thermal unit start-up decisions. [ABSTRACT FROM AUTHOR]

It is widely agreed that an increased participation of the demand side in the electricity markets would produce benefits not only for the individual consumers but also for the market as a whole. This paper proposes a method for quantifying rigorously the effect that such an increase would have on the various categories of market participants. A new centralized complex-bid market-clearing mechanism has been devised to take into consideration the load shifting behavior of consumers who do submit price-sensitive bids. The effects of the proportion of demand response on the market are illustrated using a test system with ten generating units scheduled over 24 periods. [ABSTRACT FROM AUTHOR]

Optimal power flow (OPF) belongs to the nonlinear optimization problem with discrete variables. The interior point cutting plane method (IPCPM), which possesses the advantages of both the interior point method and the cutting plane method, becomes a very promising approach to the large-scale OPF. It employs a successive linearization process and iteratively solves the mixed integer linear programming problem. However, case studies have shown that: if the problem has multiple solutions, the optimal solutions will converge to the interior of the optimal face, and the cutting planes cannot be generated due to the failure to identify the optimal base. This paper presents a new general optimal base identification method for solving the problem. The new approach significantly improves the robustness and efficiency of IPCPM. Simulation results on IEEE test systems indicate that the algorithm proposed can not only properly deal with various types of optimal solutions but also greatly enlarge the application area of IPCPM. [ABSTRACT FROM AUTHOR]