Search

In this paper, the sensitivity of look-ahead economic dispatch in real-time power markets with respect to data perturbation is studied. In the look-ahead dispatch optimization problem, a small change in the data that are used for setting the interspatial and temporal equality/inequality constraints and the objective function may negatively affect normal operations, such as the calculation of real-time wholesale electricity prices and operating costs. This could lead to more distorted prices and larger operating costs with the look-ahead dispatch than with a static dispatch that use data for a single future time. We perturb Karush–Kuhn–Tucker conditions of the look-ahead dispatch optimization formulation and then, using them, derive a linear sensitivity matrix that assesses the impact of data corruption on look-ahead dispatch. This matrix illustrates the changing optimal solution of look-ahead dispatch subject to potential corruption in various types of spatial and temporal data—generator's bidding cost coefficients, capacity limits for generators and transmission lines, ramp rates and the estimate of initial generation output with ramp constraints, and multiple-time series of the forecast load for the look-ahead horizon. The results of the simulation are illustrated with numerical examples in the IEEE 14-bus system. [ABSTRACT FROM AUTHOR]

This paper proposes a flow-based approach for the transmission tariff allocation problem based on the notions of long-run marginal cost (LRMC) and nodal exchange factors (NEFs). A worst-case power flow, expressed in terms of NEFs, is formulated to characterize the system state. Additionally, the NEFs optimal values are determined considering a specific criterion to compute tariffs. The resulting problem is formulated as a bilevel program. The upper level is a worst-case power flow that maximizes line flows taking into account the transmission tariffs computed in the lower level. The criterion considered in the lower level aims to minimize the variation range of transmission tariffs, which is particularly desirable to provide incentives for renewable sources installed far away from load centers. The resulting bilevel problem may have multiple solutions. Here, the uniqueness in tariffs is preserved by solving an alternative problem once both the generation dispatch and the variation range of transmission tariffs are known. Numerical results are provided for a 6-bus system and the IEEE 118-bus system. [ABSTRACT FROM AUTHOR]

The deep interdependence between electrical and gas systems entails a potential threat to the security (or reliability) of both systems. It is imperative to investigate the impacts of massive uncertainties on the overall secure and economical operation of both systems. In this paper, a probabilistic energy flow framework of integrated electrical and gas systems is initially proposed considering correlated varying energy demands and wind power. Three aspects of couplings between electrical and gas systems are considered: gas-fired generators, electric-driven compressors, and energy hubs integrated with power to gas (P2G) units. Furthermore, a multilinear method is specially designed to produce a deterministic energy flow solution for each sample generated by Monte Carlo simulation (MCS). Finally, test results have verified that the proposed multilinear MCS method prevails over the nonlinear MCS. In addition, P2G effectively benefits the operation of both electrical and gas networks. [ABSTRACT FROM AUTHOR]

This paper proposes a necessary condition for power flow insolvability in power distribution systems with distributed generators (DGs). We show that the proposed necessary condition indicates the impending singularity of the Jacobian matrix and the onset of voltage instability. We consider different operation modes of DG inverters, e.g., constant-power and constant-current operations, in the proposed method. A new index based on the presented necessary condition is developed to indicate the distance between the current operating point and the power flow solvability boundary. Compared to existing methods, the operating condition-dependent critical loading factor provided by the proposed condition is less conservative and is closer to the actual power flow solution space boundary. The proposed method only requires the present snapshots of voltage phasors to monitor the power flow insolvability and voltage stability. Hence, it is computationally efficient and suitable to be applied to a power distribution system with volatile DG outputs. The accuracy of the proposed necessary condition and the index is validated by simulations on a distribution test system with different DG penetration levels. [ABSTRACT FROM AUTHOR]

In some rural and sub-urban areas, the hosting capacity (HC) of low voltage networks is restricted by voltage limits. With local voltage control, photovoltaic generators can mitigate the voltage rise partly and, therefore, increase the HC. This paper investigates the effectiveness and general performance of different reactive and active power control concepts. It presents the findings of an extensive simulation-based investigation into the effectiveness of voltage rise mitigation, additional reactive power flows, network losses, and power curtailment. The two most common implementations of reactive power control have a similar effectiveness. The voltage rise can be compensated for by up to 25% and more than 60% for typical cable and overhead (OH) feeders, respectively. By additionally using active power curtailment of up to 3% of the annual yield, the HC can be increased by about 50% and 90% for the considered cable and OH feeder, respectively (purely rural feeders). [ABSTRACT FROM AUTHOR]

The dynamic tariff (DT) method is designed for the distribution system operator (DSO) to alleviate congestions that might occur in a distribution network with high penetration of distributed energy resources (DERs). Uncertainty management is required for the decentralized DT method because the DT is determined based on optimal day-ahead energy planning with forecasted parameters such as day-ahead energy prices and energy needs which might be different from the parameters used by aggregators. The uncertainty management is to quantify and mitigate the risk of the congestion when employing the DT method, which is achieved by firstly formulating the problem as a chance constrained two-level optimization and then solving the problem through an iterative procedure. Two case studies were conducted to demonstrate the efficacy of the uncertainty management of DT method. [ABSTRACT FROM PUBLISHER]

Utilizing battery storage systems (BSSs) can reduce the intermittent output of PV generation systems (PVGSs) and make them dispatchable. The aim of this paper is to design an optimal charging/discharging scheduling for BSSs such that the line loss of distribution systems interconnected with sizeable PVGSs can be minimized. A mathematical model for BSSs which can be used to simulate the charging procedures such as the commonly-used constant current to constant voltage (CC-CV) charging method, the discharging procedures and the state of charge (SOC) is proposed first. The minimum line loss problem considering the intermittent output of PVGSs and the scheduling of BSSs is then formulated based on the BSS mathematical model. The optimal charging/discharging scheduling of BSSs can then be obtained by a genetic algorithm (GA) based method. Test results demonstrate the validity of the proposed mathematical model and optimal charging/discharging scheduling for BSSs. [ABSTRACT FROM PUBLISHER]

Analysis of power systems is typically made using the method of either phase coordinates or symmetrical components depending on the type of network (un/symmetrical). The use of the symmetrical components method, a three-phase specific application of the Fortescue transformation, has been limited to pure three-phase symmetrical networks. Therefore phase coordinates has been the method used most for the analysis of distribution networks. This paper is extending the use of the symmetrical components method to distribution networks combining one-phase, two-phase, and three-phase symmetrical network parts. This paper derives a new integrated approach for the description of such networks based on Fortescue transformation. This approach is demonstrated using the forward-backward sweeping algorithm (FBS). [ABSTRACT FROM PUBLISHER]

This paper proposes a method to evaluate the worth of installing renewable distributed generation (DG) in distribution networks. Moreover, the work optimally allocates these DG units in the distribution network to maximize the worth of the connection to the local distribution company (LDC), as well as the customers connected to the system. The proposed methodology helps the LDC to better assess the benefits of the renewable DG units' proposed connections and to identify the optimal buses on which to connect these DG units. The benefits considered in this paper are deferral of upgrade investments, reduction of the cost of energy losses, and reliability improvement, which is represented by the interruption cost reduction. The proposed methodology takes into consideration the uncertainty and variability associated with the output power of renewable DG as well as the load variability. The planning problem of determining the optimal location and sizes of DG units is defined as multi-objective mixed integer programming. [ABSTRACT FROM PUBLISHER]

This paper proposes a novel model to estimate the electric energy consumption of light duty fleet of plug-in electric vehicles (PEVs). This model can be used to evaluate the impacts of plugging such loads in distribution networks. Both vehicles users' habits and diversity of usage are considered in the presented model, as well as different electric ranges and ambient temperature effect. Moreover, the paper proposes a method to optimally allocate distributed generation (DG) units in the distribution network to mitigate the impacts of high penetration of PEVs. The proposed model shall help the local distribution companies (LDC) to better assess the expected effects of PEVs on their networks and evaluate the required upgrades. Furthermore, the proposed DG allocation methodology helps to identify the optimal buses on which to connect these DG units in the presence of high PEVs penetration. A genetic based approach is utilized for the planning problem of determining the optimal locations and sizes of DG units, which is defined as a multi-objective mixed integer programming. [ABSTRACT FROM PUBLISHER]

Wind generator (WG) output is a function of wind speed and three-phase terminal voltage. Distribution systems are predominantly unbalanced. A WG model that is purely a function of wind speed is simple to use with unbalanced three-phase power flow analysis but the solution is inaccurate. These errors add up and become pronounced when a single three-phase feeder connects several WGs. Complete nonlinear three-phase WG models are accurate but are slow and unsuitable for power flow applications. This paper proposes artificial neural network (ANN) models to represent type-3 doubly-fed induction generator and type-4 permanent magnet synchronous generator. The proposed approach can be readily applied to any other type of WGs. The main advantages of these ANN models are their mathematical simplicity, high accuracy with unbalanced systems and computational speed. These models were tested with the IEEE 37-bus test system. The results show that the ANN WG models are computationally ten times faster than nonlinear accurate models. In addition, simplicity of the proposed ANN WG models allow easy integration into commercial software packages such as PSS®E and PSS®SINCAL and implementations are also shown in this paper. [ABSTRACT FROM PUBLISHER]

Society's increased concern over green house gas emission and the reduced cost of electric vehicle technologies has increased the number of electric vehicles (EV) and plug-in hybrid vehicles on the road. Previous studies into the effects of electric vehicles on the electric system have focused on transmission, generation, and the loss of life of distribution transformers. This paper focuses specifically on identifying distribution transformers that are most susceptible to excessive loading due to the implementation of electric vehicles. The authors use a binomial probability model to calculate the probability that a specific distribution transformer will experience excessive loading. Variables to the function include the existing peak transformer demand, number of customers connected to the transformer, and the most common EV charger demand. Also included in the paper is an optimization approach that utilizes the results from the binomial function to determine the optimal replacement strategy to minimize replacement costs. An extension of the approach is also utilized to explore the effectiveness of EV targeted demand side management programs. The authors apply the described algorithms to 75 000 distributions transformers within a distribution system located in Denver, Colorado, USA. [ABSTRACT FROM PUBLISHER]

In this paper, an ultra-fast algorithm for the computation of multiphase short-circuit currents at all buses is proposed by addressing the concept of selected inversion. The short circuit summary is achieved through the computation of multiphase Thevenin equivalent at each bus by using the augmented nodal matrix. This typically requires the sequential solution of linear system of equations, i.e., direct inversion which can be demanding in terms of CPU time. In this paper, it is shown that dramatic gains in computational time can be obtained when the selected inversion (SelInv) technique is performed where only a subset of entries of the inverse of augmented nodal matrix is computed. These entries include the phase domain Thevenin impedances seen from network buses which are used in the computation of short-circuit currents with the predefined boundary conditions specific to the fault type. The performance of the method is demonstrated with very large scale and realistic distribution systems. [ABSTRACT FROM PUBLISHER]

Estimating technical losses is fundamental to the planning and economics of electric power networks. This paper surveys the evolution of the ideas behind energy loss estimation and focuses on the development of the concepts of the loss factor and equivalent hours. The paper next identifies difficulties in using maximum demands and the loss factor to estimate energy losses. Based on this analysis, this study proposes an alternative loss estimation approach that relies on the “loss coefficient” as the fundamental parameter for describing load variations in loss estimation. A large load-curve data bank from Brazilian utilities is used to characterize load-curve parameters and provide perspective on the old and new concepts. Practical applications put the proposed ideas into perspective, showing how the use of average demands and loss coefficient can help to make better cable choices, increase accuracy in loss estimation for distribution transformers, and enhance the quality of information in loss estimation analysis. [ABSTRACT FROM PUBLISHER]

For the operation of distribution systems, loading balance of distribution feeders is important for reducing power loss and mitigating power flow overloading. In this paper, a loop power controller (LPC) is applied for the control of real power and reactive power flows by adjusting voltage ratio and phase shift so that the loading balance of distribution feeders can be obtained. To incorporate photovoltaic (PV) power generation in feeder loading balance, a Taipower distribution feeder with large PV installation is selected for computer simulation. Daily loading unbalance is determined by analyzing PV power generation recorded by the SCADA system and by constructing daily power load profiles based on distribution automation system (DAS) data. The load transfer required to achieve loading balance and the line impedance of distribution feeders are used to derive the voltage ratio and phase shift of the LPC. Computer simulations indicated that loading balance can be achieved in distribution feeders with large PV system installation by using loop power controllers according to the variation of solar energy and power loading of study feeders. The system power loss reduction resulting from feeder loading balance by LPC is also investigated in this paper. [ABSTRACT FROM PUBLISHER]

This paper proposes an effective approach based on the particle swarm optimization with integer coded to determine the switch operation schemes for feeder reconfiguration. The proposed approach, enhanced integer coded particle swarm optimization (EICPSO), is able to improve the search efficiency for feeder reconfiguration problems by considering the historical local optimal solutions when generating new particles. The local optimal solutions found during the evolution process are used when new particle are generated. Three different distribution systems are used in this paper to verify and validate the effectiveness of the proposed method. Simulation results show that the proposed method can find the solutions for feeder reconfiguration problems faster than other approaches such as discrete particle swarm optimization, modified binary particle swarm optimization, and genetic algorithm. [ABSTRACT FROM PUBLISHER]

A Reference Network Model (RNM) is a large-scale distribution planning tool that can help regulators to estimate efficient costs in the context of incentive regulation applied to distribution companies. This paper presents the main features of an RNM developed for planning distribution networks from scratch, greenfield planning, or incrementally from an existing grid. Two properties of the model are highlighted: the simultaneous planning of high-, medium-, and low-voltage networks by using simultaneity factors; and the layout of cables in urban areas, taking into consideration the street map, which is automatically generated by the model. A case study evaluates the impact of these features on the results. [ABSTRACT FROM AUTHOR]

This paper proposes a method to evaluate the ATC by considering dynamic constraints. The paper adopts equilibrium equations to describe steady-state constraints of pre and postdisturbance. Dot product is used as a criterion for rotor angle stability. An algorithm based on control variable parameterization (CVP) is implemented to solve the formulated dynamic-constrained optimization (DCO) problem. A nine-bus three-machine system is used to illustrate the proposed model and algorithm. [ABSTRACT FROM AUTHOR]

Power flow tracing has been suggested as an approach for evaluating 1) transmission system usage (TSU) cost and 2) loss (MW) cost for generator and load entities in the system. Recently, optimal power flow tracing methods have been proposed to "explicitly" model fairness constraints in the tracing framework. This paper, further, strengthens the tracing-compliant min-max fair cost allocation approach. The min-max model proposed in this paper is robust. It addresses concerns like scalability, numerical stability and termination in a finite number of steps while searching the optimal solution. We also propose a methodology to model DISCOMs and GENCOs as coalition within min-max framework. Case studies on an all India network of 1699 nodes and comparison with average participation and marginal participation methods bring out the better conflict resolution feature of the proposed approach. A method to model HVDC lines within the marginal participation scheme is also proposed. Quantitative and qualitative comparison of various TSU cost allocation methods on such a large system is another noteworthy contribution of the paper. [ABSTRACT FROM AUTHOR]

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 provides new insights into the electricity tracing methodology, by representing the inverted tracing upstream and downstream distribution matrices in the form of matrix power series and by applying linear algebra analysis. The nth matrix power represents the contribution of each node to power flows in the other nodes through paths of length exactly n in the digraph of flows. Such a representation proves the link between graph-based and linear equation-based approaches for electricity tracing. It also makes it possible to explain an earlier observation that circulating flows, which result in a cyclic directed graph of flows, can be detected by appearance of elements greater than one on the leading diagonal of the inverted tracing distribution matrices. Most importantly, for the first time a rigorous mathematical proof of the invertibility of the tracing distribution matrices is given, along with a proof of convergence for the matrix power series used in the paper; these proofs also allow an analysis of the conditioning of the tracing distribution matrices. Theoretical results are illustrated throughout using simple network examples. [ABSTRACT FROM AUTHOR]

Currently, there is a national push for a smarter electric grid, one that is more controllable and flexible. The full control of transmission assets are not currently built into electric network optimization models. Optimal transmission switching is a straightforward way to leverage grid controllability: to make better use of the existing system and meet growing demand with existing infrastructure. Previous papers have shown that optimizing the network topology improves the dispatch of electrical networks. Such optimal topology dispatch can be categorized as a smart grid application where there is a co-optimization of both generators and transmission topology. In this paper we present a co-optimization formulation of the generation unit commitment and transmission switching problem while ensuring N-1 reliability. We show that the optimal topology of the network can vary from hour to hour. We also show that optimizing the topology can change the optimal unit commitment schedule. This problem is large and computationally complex even for medium sized systems. We present decomposition and computational approaches to solving this problem. Results are presented for the IEEE RTS 96 test case. [ABSTRACT FROM AUTHOR]

The deregulation of electric power systems in many parts of the world has changed the mechanism of electricity pricing. Unlike the fixed price in conventional power systems, electricity price varies with time and location in the new deregulated environment. Electricity prices in a restructured power system can be highly volatile due to the random nature of system failures and demands. It is therefore very difficult for the independent system operator (ISO) to control the price and associated risk. The high prices beyond control have resulted in significant impacts on customers as well as on system operation. This paper proposes a penalty scheme for reducing electricity price volatility caused by failures in generation companies (Gencos) or transmission companies (Transcos). In this scheme, Gencos and Transcos will be penalized if their equipment failures result in unexpected price changes. The price decomposition technique is used to evaluate the price components caused by random failures. The penalty can be calculated based on the difference of electricity price components between the normal state and the contingency states. Moreover, a simplified schema which is based on profit analysis is also proposed in this paper. The proposed penalty scheme not only gives the Gencos and Transcos an incentive to improve their reliabilities but also provides a flexible tool for the ISO to control the system price risk. The possible shortcomings of the proposed schema are also specified in the paper. The IEEE RTS is analyzed to illustrate the technique. [ABSTRACT FROM AUTHOR]

This paper focuses on representing the state space model of a microgrid in which power regulated (PQ ) and voltage/frequency regulated (Vf) generation units share a distribution system. The generation units considered in this paper are inverter interfaced. This introduces some interesting modeling problems which are treated in the paper, such as the decoupled cascaded control schemes or the non-negligible grid dynamics. A modeling approach is proposed based on four defined complex vectors. These vectors allow for complex-valued system matrices to be formed in a quite automated way. Moreover, a convenient partition of the system matrices is proposed, which in turn allows fast and easy modifications. Additionally, a multivariable methodology is proposed to simultaneously find the control system gains in an optimal sense. A 69-bus radial system, supplied by 20 generation units, is used to demonstrate how the proposal is of easy implementation to conduct small-signal stability analyses. [ABSTRACT FROM AUTHOR]

This paper presents a new paradigm for distribution system operation in the presence of distributed generation (DG) sources taking into consideration the goodness factor of the DG units. The proposed concept of goodness factor of DG units is based on the computation of the incremental contribution of a DG unit to distribution system losses. The incremental contributions of a DG unit to active and reactive power losses in the distribution system are termed as the active/reactive incremental loss indices (ILI). The goodness factors are integrated directly into the distribution system operations model, which is based on an optimal power flow (OPF) framework. This model seeks to minimize the distribution company's (disco's) energy costs in the short term taking into account the contribution (goodness factor) of each DG unit. Two scenarios are considered in the paper: the first scenario considers the disco to be the owner of the DG units and hence is responsible for their scheduling and dispatch, and the second scenario considers the DG units to be investor-owned. The analysis was carried out considering an 18-bus distribution network extracted from the well-known IEEE 30-bus system and a 69-bus distribution system. [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]

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]

Forward contracts play an important role for market power mitigation and risk hedging in electricity markets. In this paper, a two-settlement electricity market including a forward market and a spot market is formulated as a two-stage game. The linear supply function equilibrium (LSFE) model and Cournot model are used to model strategic bidding for the spot market, while the forward market is modeled by Cournot model. A co-evolutionary genetic algorithm (CGA) is employed to determine the market equilibrium. The paper then examines the question whether generation companies (GenCos) would voluntarily enter forward markets due to economic inspiration and studies theoretically and numerically the factors which can affect the bidding behaviors of GenCos. The effectiveness of CGA in determining the market equilibrium is investigated and demonstrated based on two test examples. The studies show that GenCos' decisions on the participation in forward markets depend significantly on the type of competition that they have in the spot market. Moreover, GenCos' bidding behaviors in the forward market can be affected by their cost parameters and the slope of system demand function significantly. [ABSTRACT FROM AUTHOR]

The positive feedback-based anti-islanding scheme has become a common anti-islanding protection technique for inverter-based distributed generators (DGs). This paper investigates the scheme's impact on the small-signal stability of multiple inverter-based DGs installed in power distribution systems during grid-connected operation. The interactions among multiple-DGs due to the anti-islanding scheme are also addressed. An index is proposed to quantify the destabilizing effect of the aggregated positive feedback activities of multiple DGs. This paper further introduces a DG power transfer limit versus islanding detection time curve to reveal the conflicting requirements of anti-islanding protection speed and the maximum power transfer of multi-DG systems. [ABSTRACT FROM AUTHOR]

In order to be able to successfully apply interline power flow controllers (IPFCs) for power-system transient-stability improvement and for the damping of oscillations, proper control strategies should be applied to these devices. The basis for the implementation of such a strategy that is proposed in this paper is to know the energy function of a power system that includes IPFCs. Already-known energy functions that proved to be suitable for an electric-power system do not include such a device. There- fore, in this paper an energy function that considers the IPFC's action in the form of a supplement to the already-known structure-preserving energy functions was constructed. Furthermore, the strategy for implementing the newly developed IPFC energy functions in order to ensure a globally optimum control strategy in the Lyapunov sense is presented. The results of the numerical examples show that the magnitudes of the IPFC's series-injected voltages remain set to their maximum values and that only the angles of these voltages change, similar to the "bang-bang" control strategies proposed for some other FACTS devices. [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]

The locational marginal pricing (LMP)-based settlement results in a surplus collected by the system operator from the consumers. The nonlinear transmission losses and the constrained operation of the power system due to operating limits, such as power flow limits on transmission lines, cause the accumulation of this surplus. This accumulated revenue, referred to as the network rental in this paper, has two main components: loss rental and constraint rental. This paper develops a method to calculate these different rental components paid by each consumer, by combining the power flow tracing and KKT optimality conditions. This yields quantitative determination of how each consumer has overpaid in the form of loss rental and constraint rental, which in turn can be used to get a better insight of how the rental is accumulated. Simple three- and four-bus systems are used to demonstrate the proposed method. [ABSTRACT FROM AUTHOR]

Spinning contingency reserve is idle capacity connected to the system to ensure reliable operations in the case of equipment outages. The reserve has an economic value since it reduces the outage costs. In several electricity markets, reserve demand functions have been implemented to take into account the value of reserve in the market clearing process. These often take the form of a step-down function at the reserve requirement level, and as such they may not appropriately represent the reserve value. The value of spinning contingency reserve is impacted by the reliability and dynamic characteristics of system components, the system operation policies, and the economic aspects such as the risk preferences of the demand. In this paper, we take into account these aspects to approximate the reserve value and construct reserve demand functions. The results are obtained in closed form. Illustrative examples show that the demand functions constructed have similarities with those implemented in some markets. [ABSTRACT FROM AUTHOR]

This paper develops a representation of the Northeastern U.S. bulk electric power system, with an emphasis on New York and New England. The representation has two parts: a 36-bus electrical model in PTI-23 format and market data in the form of generator bids and load demands. The market data are distilled from historical data on public web sites. Since the historical data are available on an hourly basis over many years, the representation is quite rich. In addition, this paper includes the mix of generation at each bus in the model so that generation cost (fuel and emissions) and unit commitment constraints can be deduced. The representation is intended to be a test-bed for formulating, simulating and analyzing the combined technical and economic objectives of the changing electric power industry. It is further intended to be a test-bed for comparing methods of simulating electric power systems and electricity markets operating under engineering constraints. It can, for example, be used for power flow, optimal power flow, reliability, market clearing, and other economic studies. The representation as described is intended only for steady-state equilibrium studies and does not account for inter-temporal effects such as unit commitment constraints. It can, however, be extended to account for those effects. [ABSTRACT FROM AUTHOR]

The Swedish energy agency (STEM) has developed a regulatory model to supervise the revenues of the distribution system operators (DSO). The model is referred to as the network performance assessment model (NPAM). The NPAM calculates customer values for a fictive electrical distribution system, with a total cost referred to as the network performance assessment (NPA). The debiting rate for a DSO is defined by the quotient of the revenue and the NPA. If the debiting rate is higher than a certain value, the DSO is placed under review and could be forced to pay back revenue to customers. A lawsuit is currently in progress on this use of the NPAM. This paper shows results from a comprehensive sensitiveness study of the NPAM investigating the robustness of the model. The investigation shows that the model is not robust, since small stochastic variations in input data could lead to larger differences in the results than those from the model. For example, it is shown that a five-meter difference in the coordinates of the nodes in the reference system could result in a difference of 5 million Euros, i.e., approximately US $6.5 million. The understanding of weaknesses in the NPAM presented in this paper provides an important means for future developments of regulatory models in the world. [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]

The idea behind the first proposal of the fuzzy power flow (FPF) was to analyze the impact of the uncertainties in load and generation at the power flow level, when no statistical information is available. Further development of the field addressed the optimal power flow problem and the use of fuzzy methodologies to help planners of the composite generation-transmission system. In a market environment, transmission system adequacy may be defined as the ability of the system to meet reasonable demands for the transmission of electricity. The starting point of this paper is that FPF can be used as a tool to quantify this adequacy, without the need of making too many assumptions about load and generation uncertainties. However, some changes in the basic concept of the FPF are needed in order to accomplish this task—part of this paper is devoted to the description of the adequate formulation. We will also show that this formulation can be used both in the normal operation situation and in the reliability evaluation of the transmission system. An illustrative example completes this paper. [ABSTRACT FROM AUTHOR]

Present-day radial electric power distribution circuit faces multiple challenges due to the increased photovoltaic (PV) generation. This paper aims to examine and design modern distribution circuit topologies for accommodating high PV penetration, while addressing power quality concerns. The central hypothesis of the proposed design approach is that by decreasing the Thevenin impedance at the buses where PVs are connected, the impacts on feeder voltages due to PV generation become less pronounced thereby additional PV capacity can be integrated at the corresponding buses. A novel two-stage optimization framework is proposed. The first stage is a mixed-integer linear programing based formulation to design new optimal configuration for any given distribution circuit. The formulation allows the possibility that the circuit can be operated in either a radial or loop configuration. The second stage, a nonlinear programing based formulation, then finds PV hosting capacity for the identified optimal configuration. The proposed two-stage framework is evaluated for IEEE 123-bus test feeder. It is demonstrated that the PV hosting capacity of the feeder can be increased by 53% by optimally adding two new distribution lines with tie-switches. [ABSTRACT FROM AUTHOR]

Electricity markets based on simple bids provide a very high degree of transparency and simplicity. However, simple bids fail to capture many well-known characteristics of generating units and, therefore, the responsibility for obtaining feasible schedules is transferred to market participants. The purpose of this paper is to help the generating utility to automatically analyze the last energy program cleared in the market and, in case this program is technically unfeasible, to provide an alternative schedule by redispatching the generating units. This is achieved by formulating an optimization problem where the objective is to find the cheapest and feasible instantaneous power trajectory of each generator, trying to minimize the differences between its hourly average values and the last energy program. As the objectives of the utility can vary during the day, three different models are presented. Two of them are formulated as a joint energy and reserve dispatch in order to take into account possible commitments acquired in the ancillary services market of AGC regulation. In this sense, a novel approach for considering discontinuous ancillary regulation curves is proposed. Some numerical examples are included to illustrate the essential features of the models. [ABSTRACT FROM AUTHOR]

A major goal for managers of electric power networks is maximum asset performance. Minimal life cycle cost and maintenance optimization becomes crucial in reaching this goal, while meeting demands from customers and regulators. This necessitates the determination of the optimal balance between preventive and corrective maintenance in order to obtain the lowest total cost. The approach of this paper is to study the problem of balance between preventive and corrective maintenance as a multiobjective optimization problem, with customer interruptions on one hand and the maintenance budget of the network operator on the other. The problem is solved with meta-heuristics developed for the specific problem, in conjunction with an evolutionary particle swarm optimization algorithm. The maintenance optimization is applied in a case study to an urban distribution system in Stockholm, Sweden. Despite a general decreased level of maintenance (lower total maintenance cost), better network performance can be offered to the customers. This is achieved by focusing the preventive maintenance on components with a high potential for improvements. Besides this, this paper displays the value of introducing more maintenance alternatives for every component and choosing the right level of maintenance for the components with respect to network performance. [ABSTRACT FROM AUTHOR]

Nodal electricity prices are designed to send efficient economic signals to market participants for operating and investment decisions. The inherent nonlinearity of transmission losses and the use of marginal loss pricing can obscure the intended economic information in the loss component of nodal prices. As one step in clarifying the determination of the marginal loss price component, this paper discusses the calculation of nodal electricity prices in lossy networks and presents a variety of accepted methods for determining marginal loss. This paper then proposes a method for calculating the marginal loss component of nodal prices during hours with congestion that reflects each market participant's contribution to marginal losses more accurately than current implementations. The proposed method recognizes that increases in incremental energy flows cannot flow across constrained lines, and thus, system-wide marginal losses should not be attributed to generators or loads in the constrained subregions. The objectives of the discussion are to improve the understanding of how marginal losses are determined and also to improve the accuracy of the information conveyed in the marginal loss price component. The ultimate goal is to promote more efficient price signals to electricity market participants for both transmission loss and congestion. [ABSTRACT FROM AUTHOR]

This paper provides a stochastic programming approach to optimally reinforce and expand the transmission network so that the impact of deliberate attacks is mitigated. The network planner selects the new lines to be built accounting for the vulnerability of the transmission network against a set of credible intentional outages. The vulnerability of the transmission network is measured in terms of the expected load shed. An instance of the previously reported terrorist threat problem is solved to generate the set of credible deliberate attacks. The proposed model is formulated as a mixed-integer linear program for which efficient solvers are available. Results from a case study based on the IEEE Two Area Reliability Test System are provided and analyzed. [ABSTRACT FROM AUTHOR]

The risk of blackouts is inherent in complex power systems, despite all efforts to prevent their occurrence. To mitigate the consequences of major blackouts, better restoration plans have been demanded. Commonly, these plans consist of a set of actions textually described. In order to enhance the operating staff comprehension about the restoration plan, this paper proposes a methodology, based on CPM/PERT graph theory, that allows power system restoration plans to be graphically visualized. This approach permits to clearly see the precedence relations among activities and to graphically follow the restoration process during its execution. The methodology can also take advantage of calculations involved with CPM/PERT methods to evaluate the restoration duration and the plan critical path. The application of the proposed approach is illustrated using the IEEE 30-bus network and the restoration plan developed for a portion of the Brazilian interconnected power system. [ABSTRACT FROM AUTHOR]

A competitive generating company (GENCO) can maximize its payoff by optimizing its generation assets. This paper considers the GENCO's arbitrage problem using stochastic price-based unit commitment while considering the associated risks. The GENCO may consider arbitrage opportunities in purchases from qualifying facilities (QFs) as well as simultaneous trades with spot markets for energy, ancillary services, fuel, and emission allowance. The tradeoff between maximizing expected payoffs and minimizing risks due to market price uncertainties is modeled explicitly by including the expected downside risk as a constraint. The downside risk is defined as the unfulfilled profit. The Monte Carlo simulation is applied to generate scenarios, and scenario reduction techniques are applied to reduce the number of scenarios while maintaining a good approximation of the exact solution. The proposed case studies illustrate the significance of arbitrage in multi-commodity markets and the importance of considering the uncertainty of market prices. [ABSTRACT FROM AUTHOR]

This is the second part of a two-part paper in which application methods to enhance distribution horizon planning for a 20+ year period are described. The optimal horizon planning model encompasses all distribution design requirements for primary and secondary systems. The model formulation is described in the companion paper Part I. The model makes use of a generalized feeder layout viewed as a tree-like circuit serving a circular sector of a round or hexagonal service area of uniform load density. The horizon model optimization objective cost function and constraint equation applications are described in this paper. The horizon planning model is validated with analysis of case studies and sensitivity evaluations for input and output variables. The case studies are assessed under various conditions such as changing consumer density, consumer characteristics, cost of energy, and economic assumptions. The application of the model is demonstrated using Snohomish PUD future expansion assumptions with case studies to examine impacts of horizon assumptions on future conductor sizes, primary voltage classes, voltage drop designs, reliability, and consumer cost of service. [ABSTRACT FROM AUTHOR]

This paper is the second of a two-part paper and describes the application of a multiperiod generalized network flow model that is used to analyze the economic efficiencies of the energy movements from the coal and natural gas suppliers to the electric load centers, providing a simulation tool that captures dynamics of and interdependencies between the coal, natural gas, and electricity networks. The modeling approach, mathematical formulation, and modeling assumptions are presented in part I. This sequel presents and discusses numerical results to illustrate the application of the model. The model enables public and private decision makers to carry out comprehensive analyses of a wide range of issues related to the energy sector, such as strategic planning, economic impact assessment, and different regulatory regimes. [ABSTRACT FROM AUTHOR]

This paper is the first of a two-part paper presenting a multiperiod generalized network flow model of the integrated energy system in the United States. Part I describes the modeling approach used to evaluate the economic efficiencies of the systemwide energy flows, from the coal and natural gas suppliers to the electric load centers. Under the proposed problem formulation, fuel supply and electricity demand nodes are connected via a transportation network, and the model is solved for the most efficient allocation of quantities and corresponding prices. The methodology includes physical, economic, and environmental aspects that characterize the different networks. Part II of this paper provides numerical results that demonstrate the application of the model. [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]

In a zonal market, the transmission system operator (TSO) has to compute the transfer limits among areas in advance (weeks or months) with respect to the day-ahead market session. The computation of such limits is usually made starting from some reference scenarios: this choice is arbitrary and has a strong influence on the results of the market. In this paper, a new probabilistic approach is developed to reduce such arbitrariness. A Monte Carlo method is applied to sample many different reference scenarios (in terms of generation patterns) to be adopted for the total transfer capacity (TTC) computation. Eventually, the probability density function of the TTC values is built. The proposed procedure allows the TSO to evaluate, for each possible choice of the TTC limit among areas, the maximum probability of congestion in a market framework, thus selecting the limit corresponding to the acceptable risk level,, The new methodology is applied to the Italian system. [ABSTRACT FROM AUTHOR]

Distribution systems management is becoming an increasingly complicated issue due to the introduction of new energy trading strategies and new technologies. In this paper, an optimal reinforcement strategy to provide reliable and economic service to customers in a given time frame is investigated. In the new deregulated energy market and considering the incentives coming from the political and economical fields, it is reasonable to consider distributed generation (DG) as a viable option for systems reinforcement. In the paper, the DG technology is considered as a possible solution for distribution systems capacity problems, along several years. Therefore, compound solutions comprising the installation of both feeders and substations reinforcement and DG integration at different times are considered in the formulation of a minimum cost distribution systems reinforcement strategy problem. An application on a medium size network, hypothesizing a scenario of reinforcement also using as DG gas micro-turbines, is carried out using a novel optimization technique allowing the identification of optimal paths in trees or graphs. The proposed technique is the Dynamic Ant Colony Search algorithm. [ABSTRACT FROM AUTHOR]