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This paper proposes a methodology to determine the optimal capacity of renewable distributed generation (RDG). The objective in this paper is to maximize cost-savings of energy not supplied (ENS) as well as cost-savings of energy loss according to RDG installation in a distribution network. Additionally, in order to achieve this multi-objective optimization problem, both a restoration matrix and restoration availability are newly proposed. In this case study, a practical Korea Electric Power Corporation (KEPCO) system is presented and discussed, demonstrating the performance and effectiveness of the proposed methods. [ABSTRACT FROM PUBLISHER]

Phase imbalance in the U.K. and European low-voltage (415 V, LV) distribution networks causes additional energy losses. A key barrier against understanding the imbalance-induced energy losses is the absence of high-resolution time-series data for LV networks. It remains a challenge to estimate imbalance-induced energy losses in LV networks that only have the yearly average currents of the three phases. To address this insufficient data challenge, this paper proposes a new customized statistical approach, named as the clustering, classification, and range estimation (CCRE) approach. It finds a match between the network with only the yearly average phase currents (the data-scarce network) and a cluster of networks with time series of phase current data (data-rich networks). Then, CCRE performs a range estimation of the imbalance-induced energy loss for the cluster of data-rich networks that resemble the data-scarce network. Chebyshev's inequality is applied to narrow down this range, which represents the confidence interval of the imbalance-induced energy loss for the data-scarce network. Case studies reveal that, given such a few data from the data-scarce networks, more than 80% of these networks are classified to the correct clusters and the confidence of the imbalance-induced energy loss estimation is 89%. [ABSTRACT FROM AUTHOR]

This paper investigates the impact of the combined effects of load variability and phase imbalance onto simulated low-voltage grid losses. The paper proposes new indices for relative load time-variability and phase-imbalance. With those indices, linear mappings are derived for the relative losses caused by a single three-phase load when modeled as a random variable that is per-phase identical and independently distributed. Impacts of increasingly complex load modeling are then obtained by simulation and used to gain insight into loss estimation errors caused by simplified representations of time-variability and phase-imbalance. Based on the linear mappings and on the simulation results obtained under realistic grid loading, limitations of present day meter resolution are discussed. [ABSTRACT FROM AUTHOR]

This paper proposes a comprehensive framework to detect non-technical losses (NTLs) and recover electrical energy (lost by abnormalities or fraud) by means of a data mining analysis, in the Spanish Power Electric Industry. It is divided into four section: data selection, data preprocessing, descriptive, and predictive data mining. The authors insist on the importance of the knowledge of the particular characteristics of the Power Company customer: the main features available in databases are described. The paper presents two innovative statistical estimators to attach importance to variability and trend analysis of electric consumption and offers a predictive model, based on the Generalized Rule Induction (GRI) model. This predictive analysis discovers association rules in the data and it is supplemented by a binary Quest tree classification method. The quality of this framework is illustrated by a case study considering a real database, supplied by Endesa Company. [ABSTRACT FROM PUBLISHER]

Phase swapping, which rebalances the unbalanced three-phase low voltage (LV, 415 V) networks, improves network efficiency by reducing capacity waste and energy losses. A key challenge against phase swapping is that the majority of LV networks are data scarce, i.e., there is a general lack of data in LV networks. In light of this, this paper proposes a new statistical approach to develop phase swapping guidance for data-scarce LV networks with neither time-series network measurements nor customer metering data. First, given a set of data-rich LV networks (with time-series phase currents data collected at LV substations throughout a year), typical load profiles and their weights in each of the three phases are extracted by applying a nonnegative matrix factorization method. Then, phase swapping guidance are developed for data-rich LV networks along with their rebalancing potentials (rebalancing potentials refer to the reduction of phase imbalance degree). Second, a rapid screening model is developed to efficiently identify the data-scarce LV networks with high rebalancing potentials. Phase swapping guidance are then developed for these data-scarce networks with high rebalancing potentials. Case studies reveal that the statistical approach produces effective phase swapping guidance, which reduce the phase imbalance degrees for 99% of the LV networks and the maximum reduction is 35%. Validation results show that the average reduction of the phase imbalance degree for data-scarce networks is only 14.3% less than that for data-rich networks. [ABSTRACT FROM AUTHOR]

This paper presents an on-line operational optimization approach to determine the optimal reactive power/volt-ampere reactive (VAr) set points for open unified power quality conditioner (UPQC-O) under varying load demand of a distribution network. The UPQC-O consists of series and shunt inverters. The modeling of UPQC-O is done to provide VAr support to a network, to mitigate supply voltage sag to the downstream buses, and to eliminate harmonics present in the line current. A non-linear optimization problem is formulated to determine the optimal VAr set points for the inverters of UPQC-O in each loading condition. The objective function is the minimization of energy loss. The limits on bus voltage magnitude, line current flow, and maximum VAr support capacities of inverters are considered to be the operational constraints. The optimization is performed with the data of hourly varying load demand for different seasons in a year. The optimization problem is solved using CONOPT solver of general algebraic modeling system. The cost-benefit analysis and the infrastructure required for the real time implementation of the proposed methodology are also provided. The simulation results show the effectiveness of the proposed approach in energy loss reduction. [ABSTRACT FROM AUTHOR]

This paper proposes a two-stage energy management scheme (EMS) for AC–DC hybrid smart distribution systems (DSs). The proposed EMS is formulated as a multi-objective optimization problem to minimize the DS operation costs and energy losses. The proposed EMS is achieved in two stages. In the first stage, a network reconfiguration algorithm determines the optimal day-ahead reconfiguration schedule for a hybrid DS. In the second stage, a real-time optimal power flow algorithm determines the real-time operational schedule of the energy resources. This paper also introduces a new linearized power flow model for AC–DC hybrid DSs. This new model facilitates the formulation of the first-stage algorithm as a mixed-integer linear programming problem and the formulation of the second-stage algorithm as a linear programming problem. The proposed two-stage EMS was tested on a case study of a hybrid DS that included different types of loads and distributed generators. The results demonstrate the efficacy of the proposed EMS: the optimal day-ahead reconfiguration schedule was successfully obtained in the first stage, and the proper and optimal real-time operation was achieved in the second stage. [ABSTRACT FROM AUTHOR]

The evolution of power distribution grids from passive to active systems creates reliability and efficiency challenges to the distribution system operators. In this paper, an energy management and control scheme for managing the operation of an active distribution grid with prosumers is proposed. A multi-objective optimization model to minimize (i) the prosumers electricity cost and (ii) the cost of the grid energy losses, while guaranteeing safe and reliable grid operation is formulated. This is done by determining the active and reactive power set-points of the photovoltaic and storage systems integrated in the grid buildings. The resulting optimization model is non-convex, thus a convex second-order cone program is developed by appropriately relaxing the non-convex constraints which yields optimal results in most operating conditions. The convexified model is further utilized to develop an algorithm that yields feasible solutions to the non-convex problem under any operating conditions. Moreover, a second novel algorithm to find the operating point that provides fairness between the prosumers and the grid costs is proposed. Simulation results demonstrate the effectiveness and superiority of the proposed scheme in managing an industrial distribution grid compared to a self-consumption approach. [ABSTRACT FROM AUTHOR]

Power losses estimation under time-varying distributed generation (DG) conditions usually demands several power flow simulations, which is a time-consuming task. To handle this issue, this paper proposes a method that uses the information of only one (base case) power flow to estimate the total power losses of distribution networks for any new DG condition. The method is based on the second-order power flow sensitivities, which are suitable to model the nonlinear nature of power losses. As a result, the method has the potential to speed up the solution of power losses reduction optimization problems, such as DG allocation problems, in which several DG configurations need to be considered. Moreover, a practical index is proposed to quantify the responsibility of each DG for the total power losses in a multi-DG scenario. The test results verified the validity of the proposed concept and method. [ABSTRACT FROM AUTHOR]

While there are growing interests in using pumped hydro storage to facilitate the integration of renewable resources, the flexibility of storage is not being fully utilized by existing energy and market management systems. Today, one common approach to operate pumped hydro storage is to determine schedules for a future time horizon based on a look-ahead operational planning stage, with limited adjustment in real-time. However, as renewable penetration levels increase, such approaches do not fully utilize the flexibility of pumped hydro storage. In this paper, a policy function approach is proposed to enhance the utilization of pumped hydro storage in real-time operations. The performance of the approach is evaluated and compared with other benchmark approaches using the IEEE RTS 24-bus system. The result shows that the policy function approach is effective in utilizing the flexibility of pumped hydro storage and has minimal added computational complexity to the existing dispatch process. [ABSTRACT FROM AUTHOR]

Large-scale adoption of moving electric vehicle (EV) loads significantly accelerates the integration of power and traffic systems. This paper proposes an approach to assess and alleviate the impacts of stochastic EV charging and movement in an integrated power and traffic system. Level of Congestion (LoC), Nodal Voltage Deviation (NVD) and Energy Loss Rate (ELR) are proposed as nodal indices to spatially and temporally assess the impacts due to the inter-node movement of EVs on power system operation. Nodal Time-of-Use (NTOU) price and Road Traffic Congestion (RTC) price are developed to shift the charging and movement of EV loads. EV driver's charging and driving decisions are modeled by fuzzy logic inference system in response to NTOU and RTC prices. Two transportation systems have been developed and integrated with the Roy Billinton test power system (RBTS) to illustrate the proposed technique and model. [ABSTRACT FROM PUBLISHER]

In this paper, a two-stage optimization framework is proposed for optimal placement and centralized real-time control of low-voltage static var compensators (LV-SVCs) in unbalanced distribution circuits to achieve feeder level benefits namely voltage regulation and energy loss minimization. The number, locations, and the optimal real-time reactive power injections from the LV-SVCs are determined from a proposed three-phase unbalanced ac optimal power flow (ACOPF). The ACOPF is formulated as a multi-objective optimization with operating constraints written in rectangular coordinates. The resulting nonlinear nonconvex problem is solved using the predictor-corrector primal-dual interior point method. The proposed approach is scalable for application to large distribution circuits, treats the constraints of physical space limitations effectively, and can take advantage of communication capabilities of LV-SVCs for centralized real-time control. The benefits of the proposed real-time control of LV-SVCs as compared to their operation with local autonomous voltage-based distributed control is demonstrated. The results show that, the proposed approach addresses the LV-SVC placement and control problem effectively to minimize energy losses while maintaining the voltage regulation. [ABSTRACT FROM AUTHOR]

A new generator phasor measurement unit can provide a generator internal response during transient periods, thereby enabling online evaluation of generator damping in detail. In this paper, a method for the online detailed evaluation of the generator damping contribution during oscillation periods based on the damping loss factor (DLF) and multi-scale chirplet sparse signal decomposition (MCSSD) is proposed. First, the DLF in a simple elastic oscillation system, which can be used to quantitatively evaluate the damping characteristics of components, is introduced. After analyzing the feasibility of using the DLF during low-frequency oscillation, the generator damping loss factor (GDLF) is established to quantitatively evaluate the generator damping contribution, including the effects of the excitation system, governor system, and generator winding. Next, the modal composition of the generator dissipation energy is studied to extend the application of the GDLF to a multi-machine power system. Finally, a method for the online evaluation of generator damping during low-frequency oscillation based on the GDLF and MCSSD is presented. The proposed method is examined in detail using a single-machine infinite-bus system and then further demonstrated by applying it to a practical power system with multiple electromechanical oscillations. [ABSTRACT FROM AUTHOR]

A new energy-dissipating hybrid control framework is proposed in this paper. The proposed framework incorporates a plant with continuous dynamics connected in parallel with a hybrid controller that combines logical switches with continuous dynamics. The overall closed-loop system can be described as a hybrid impulsive dynamical system in which the redundant energy preserved in the plant can be damped quickly and continuously due to the enhanced dissipativity of the closed-loop system. The proposed framework is applied to design decentralized nonlinear excitation controllers for synchronous generators in a multimachine system to improve its transient stability, in which the synchronous generators are modeled as port-controlled Hamiltonian systems. Simulation studies on the IEEE 10-generator, 39-bus New England power system are carried out to verify the effectiveness of the proposed energy-dissipating hybrid excitation control to improve the transient stability and dissipativity of the interconnected power system under various fault conditions. [ABSTRACT FROM AUTHOR]

Day-ahead scheduling has played a significant role in the operation of distribution systems, aiming at minimizing the total operation cost. With the excessive integration of information and communication technologies and intelligent electronic devices, distribution system operators may seek to optimally control the active management elements to increase the economic and technical performance of future smart distribution systems. This paper focuses on an integrated day-ahead scheduling scheme that is formulated as a mixed integer second-order cone programming problem to obtain the optimal solution by means of the relaxed power flow model (RPFM). The detailed technical constraints for all the elements are accommodated based on the RPFM-based optimization method. Meanwhile, active management cost and punishment cost of wind power curtailed and customer energy not supplied are also considered in the design objectives of this paper. In order to address the uncertainties, a stochastic robust optimization method is first introduced to decide the active management elements (including capacitor bank, electrical storage system, controllable load, and switch) as the robust decision scheme. Afterwards, the column-and-constraint generation algorithm is applied to solve the proposed stochastic robust two-stage optimization model. Numerical results based on the IEEE 33-bus, PG&E 69-bus, and practical 152-bus systems are obtained to verify the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

Uncertainties from generation sources and loads have introduced tremendous challenges to the optimal dispatch of microgrids. This paper presents a novel two-stage min–max–min robust optimal dispatch model for a representative islanded ac/dc hybrid microgrid that faces uncertainties in renewable energy generation and customer loads. The first stage of the model determines the startup/shutdown state of the diesel engine generator and the operating state of the bidirectional converter of the microgrid. Then, the second stage optimizes the power dispatch of individual units in the microgrid. A new linearized equipment cost model is developed, counting for the degradation of energy storage. The use of this linear model helps maintain the linearity of the objective function without compromising solution accuracy. The column-and-constraint generation algorithm is implemented to efficiently obtain a robust dispatching plan for the microgrid, which minimizes the daily operating cost in the worst-case scenario. A case study and sensitivity analyses further demonstrate the rationale and the unique capability of the proposed model for the operation scheduling of ac/dc hybrid microgrids. [ABSTRACT FROM AUTHOR]

High levels of penetration of distributed generation (DG) are a new challenge for traditional electric power systems. Power injections from DGs change network power flows modifying energy losses. Although it is considered that DG reduce losses, this paper shows that this is not always true. This paper presents an approach to compute annual energy losses variations when different penetration and concentration levels of DG are connected to a distribution network. In addition, the impact on losses of different DG technologies, such as combined heat and power, wind power, photovoltaic, and fuel-cells, is analyzed. Results show that energy losses variation, as a function of the DG penetration level, presents a characteristic U-shape trajectory. Moreover, when DG units are more dispersed along network feeders, higher losses reduction can be expected. Regarding DG technologies, it should be noted that wind power is the one that shows the worst behavior in losses reduction. Finally, DG units with reactive power control provide a better network voltage profile and lower losses. [ABSTRACT FROM AUTHOR]

The multi-objective reactive power coordination control model was presented in this paper to overcome the drawback that reactive power compensation devices lack in coordination and have high active power loss. In this model, the minimum bus voltage deviation and total power loss of reactive power compensation devices are taken as objective functions, by bringing the lower voltage reactors and capacitors into the static var compensator control system and considering the reactive power compensation devices interaction between different transformer substations. Due to the different sensitivity of control variables in control model and lack of the local search ability, control variables are divided into sensitive variables and non-sensitive variables. Then, the improved non-dominated sorting genetic algorithm II (NSGA-II) with secondary search ability is used to search the Pareto optimal solution set. Two substations in large power grid with strong voltage coupling are coordinated in different load level. The results obtained by proposed NSGA-II algorithm can provide a variety of optimal control strategies. Compared to the conventional NSGA-II algorithm and normal boundary intersection method, the improved NSGA-II algorithm has better convergence curve and distribution of the Pareto solution sets. [ABSTRACT FROM PUBLISHER]

Distribution system operators are often challenged by voltage regulation problems, energy losses, and network capacity problems. This paper analyses a real-life 3.9-MVA distribution network in Gujarat State, India. Distributed generation from renewable energy sources like wind and solar, at optimal locations on distribution feeders, may enable energy loss reduction and voltage profile improvement. A methodology is developed and presented for deciding the appropriate location of these embedded renewable generators. Simulations are performed to calculate different scenarios, and the final analysis reveals that the low voltage problem has totally been eliminated on all of the nodes of the distribution network. Complimentary, significant energy loss reductions are also achieved in the distribution, and the network reserve capacity has also increased. [ABSTRACT FROM PUBLISHER]

Steady-state models of the hybrid power flow controller (HPFC) for power flow and optimal power flow (OPF) studies are presented in this paper, considering the multiple control modes of the device. A strategy for control mode switching and limit handling in power flow calculations is proposed. The OPF model of the HPFC represents all the device control and physical limits as constraints in the mathematical formulation, so that the HPFC can be optimally dispatched as a part of the transmission system control assets. The power flow model is demonstrated and validated through loadability studies on a two-area benchmark test system, where the OPF model is used to determine the optimal ratings of the device based on a cost-benefit analysis. A study is also presented of the HPFC application to Ontario-Canada's grid, to address particular congestion problems in this network; an HPFC cost analysis is also shown for this system. The presented studies demonstrate the application of the proposed models for planning and operation studies, illustrating the performance, effectiveness, and feasibility of the controller to solve congestion issues in a real grid. [ABSTRACT FROM AUTHOR]

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]

In the distribution management system (DMS), an essential application for the energy efficiency improvement is loss reduction. Loss reduction often involves the control of reactive power (var) resources to optimize the var flow in the network. Traditionally, most available var resources in the distribution network have been switchable shunt capacitor banks. Today distributed energy resources (DER) are becoming another significant var resource due to their increasing penetration, which brings new opportunities as well as challenges for loss reduction. This paper proposes an advanced loss reduction approach to achieve the optimal control coordination among multiple capacitors and DERs. The proposed approach and solution are developed on the basis of the detailed multi-phase distribution network modeling and the state-of-the-art optimization technology. This work also investigates the impact of the DER var control on the loss reduction improvement and voltage violation correction. The effectiveness of the proposed approach is demonstrated on practical utility distribution circuits with varying degree of unbalance and model complexity. The performance of the solution method proves the capability of online solution speed for large and complex distribution systems. [ABSTRACT FROM PUBLISHER]

Copper losses in low voltage distribution circuits are a significant proportion of total energy losses and contribute to higher customer costs and carbon emissions. These losses can be evaluated using network models with customer demand data. This paper considers the under-estimation of copper losses when the spiky characteristics of real customer demands are smoothed by arithmetic mean averaging. This is investigated through simulation and by analysis of measured data. The mean losses in cables and equipment supplying a single dwelling estimated from half-hourly data were found to have significant errors of 40%, compared to calculations using high resolution data. Similar errors were found in estimates of peak thermal loading over a half-hour period, with significant variation between results for each customer. The errors reduce as the demand is aggregated, with mean losses for a group of 22 dwellings under-estimated by 7% using half-hourly data. This paper investigates the relationship between the demand data time resolution and errors in the estimated losses. Recommendations are then provided for the time resolution to be used in future measurements and simulation studies. A linear extrapolation technique is also presented whereby errors due to the use of averaged demand data can be reduced. [ABSTRACT FROM PUBLISHER]

This paper presents an efficient and fast-converging optimization technique based on a modification of the traditional big bang-big crunch method for optimal placement and sizing of voltage controlled distributed generators. The proposed algorithm deals with the optimization problems incorporating multiple distributed generators for the sake of power as well as energy loss minimization in balanced/unbalanced distribution systems. The proposed algorithm is implemented in MATLAB environment and tested on the 33-bus feeder system and the IEEE 37-node feeder. Validation of the proposed method is done via comparing the results with published results obtained from other competitive methods. [ABSTRACT FROM PUBLISHER]

In this paper, a multiagent clustering-based distributed approach for the optimal planning of wind-distributed generators (DGs) and switched capacitor banks (SCBs) is proposed. First, electrical distance matrices for the power systems are constructed. Additionally, a constrained optimization problem, which includes several indices and a few constraints, for the optimal clustering of distribution networks is formulated and solved. After obtaining optimal clusters, agents are assigned to the clusters, and a second multiobjective optimization problem (MOOP) for the distributed planning of wind DGs and SCBs is formulated and assigned to a head agent. The number of objective functions in the MOOP is equal to the number of agents. The objective function of an agent consists of three indices: annual energy losses, investment costs, and voltage enhancement. Moreover, a deep neural network architecture is designed, and four independent networks are trained with six years of wind speed data for the seasonal wind speed forecasting. Two IEEE unbalanced test feeders, one with 37 nodes and the other with 123 nodes, and eight test cases are considered for simulations. The results show that losses and costs are optimized, and the voltage unbalance of the system is reduced. [ABSTRACT FROM AUTHOR]

This paper proposes a new method to solve the multistage security-constrained transmission expansion planning problem, incorporating lines based on high-voltage alternating current (HVAC) and high-voltage direct current (HVDC) alternatives. A novel mixed-integer linear programming model, which incorporates transmission losses using a piecewise linearization, is presented. An efficient method to reduce the search space of the problem is developed to help in the solution process. Garver's 6-bus system and a modified Southern Brazilian system are used to show the precision and efficiency of the proposed approach. The tests are performed for cases with and without HVDC links and transmission losses. The results indicate that better expansion plans can be found by considering HVDC proposals in the expansion process. The promising trend of using HVDC lines in future networks to improve the reliability in the system is demonstrated. [ABSTRACT FROM PUBLISHER]

The paper presents a new method for loss allocation in radial distribution networks (DN) with dispersed generation (DG). The method is based on the power summation algorithm, the branch-oriented approach in particular, and establishes direct relationship between losses in each branch of the network and injected active and reactive power in the nodes. Active and reactive power at receiving node of each branch of the network is decomposed as a sum of all node injected powers, including branch losses in the branches fed by the particular branch. Allocation of crossed terms of active and reactive power is calculated using quadratic relation between power flows and losses. DG active and reactive power injections in the summation process are treated as negative loads, while active and reactive loads are considered positive. Results of the application of the method on 32-node test system are presented, discussed, and compared with other published methods. [ABSTRACT FROM PUBLISHER]

This paper describes a method for calculating energy losses in any system element assuming that the transmitted energy across it is known. The method identifies two components of losses: load variance and load mean. The load variance component can be neglected for large loads, but it is significant for small loads, which are dominant in low voltage networks. Needed parameters for loss calculation are determined by two load duration curves (LDC5) per load type. The formulae for loss calculation in transformers and distribution lines of various phase systems are given, including the formulae for energy losses and average current in the neutral conductor. A new algorithm for voltage calculation at network nodes is proposed and shown to provide high accuracy of calculated losses. The method enables loss calculation for compounded (nonhomogeneous) loads and gives the exact relationship between traditional Loss factor and the load factor. [ABSTRACT FROM AUTHOR]

Phase imbalance widely exists in the UK's low voltage (415 V, LV) distribution networks. The imbalances not only lead to insufficient use of LV network assets but also cause energy losses. They lead to hundreds of millions of British pounds each year in the UK. The cost-benefit analyses of phase balancing solutions remained an unresolved question for the majority of the LV networks. The main challenge is data-scarcity – these networks only have peak current and total energy consumption that are collected once a year. To perform a cost-benefit analysis of phase balancing for data-scarce LV networks, this paper develops a customized cluster-wise Gaussian process regression (CGPR) approach. The approach estimates the total cost of phase imbalance for any data-scarce LV network by extracting knowledge from a set of representative data-rich LV networks and extrapolating the knowledge to any data-scarce network. The imbalance-induced cost is then translated into the benefit from phase balancing and this is compared against the costs of phase balancing solutions, e.g., deploying phase balancers. The developed CGPR approach assists distribution network operators (DNOs) to evaluate the cost-benefit of phase balancing solutions for data-scarce networks without the need to invest in additional monitoring devices. [ABSTRACT FROM AUTHOR]

This paper proposes a new correlation index, in order to connect the sizing and the siting of a PV unit with the respective impact on Joule losses of a radial distribution feeder. Randomly generated scenarios for PV units siting are investigated and based on the results the proposed index is formulated, corrected, and validated. The index incorporates factors such as: 1) the correlation coefficient between the installed PV capacity per node and the respective power rating of the distribution transformer, and 2) the size of a PV unit in relation to its distance from the feeding end. The importance of this index lies in the fact that it may be used from the DSO to evaluate the contribution of a new PV unit interconnection to the annual Joule losses of a line beforehand, and thus perform a better cost allocation. [ABSTRACT FROM AUTHOR]

It is widely accepted that renewable energy sources are the key to a sustainable energy supply infrastructure since they are both inexhaustible and nonpolluting. A number of renewable energy technologies are now commercially available, the most notable being wind power, photovoltaic, solar thermal systems, biomass, and various forms of hydraulic power. In this paper, a methodology has been proposed for optimally allocating different types of renewable distributed generation (DG) units in the distribution system so as to minimize annual energy loss. The methodology is based on generating a probabilistic generation-load model that combines all possible operating conditions of the renewable DG units with their probabilities, hence accommodating this model in a deterministic planning problem. The planning problem is formulated as mixed integer nonlinear programming (MINLP), with an objective function for minimizing the system's annual energy losses. The constraints include the voltage limits, the feeders' capacity, the maximum penetration limit, and the discrete size of the available DG units. This proposed technique has been applied to a typical rural distribution system with different scenarios, including all possible combinations of the renewable DG units. The results show that a significant reduction in annual energy losses is achieved for all the proposed scenarios. [ABSTRACT FROM AUTHOR]

In this paper, the concepts related to loss partitioning among the phase currents in three-phase distribution systems are revisited in the light of new findings identified by the authors. In particular, the presence of a paradox in the classical loss partitioning approach, based on the use of the phase-by-phase difference between the input and output complex power, is highlighted. The conditions for performing effective loss partitioning without the occurrence of the paradox are thus established. The corresponding results are then used to extend the branch current decomposition loss allocation method for enabling its application to three-phase unbalanced distribution systems with distributed generation. Several numerical examples on a three-phase line with grounded neutral and on the modified IEEE 13-node test system are provided to assist the illustration and discussion of the novel conceptual framework. [ABSTRACT FROM AUTHOR]

In a sinusoidal steady-state circuit, how much of an impedance-branch dissipation power should be assigned to each source? The answer is the basis of electricity transmission pricing, such as the pricing of line loss and line security due to thermal limit. However, it is difficult to obtain a unique and common consent answer because of the nonlinearity of power expression. This paper presents two weakly conditioned imputation formulas, respectively for dissipation active- and reactive-power, to answer the question. First, a detailed form of Shapley value formula and three weak conditions are proposed. On this basis, the two imputation formulas are then derived and proved mathematically. The imputation formulas are explicitly in terms of source currents/voltages, thus analytic and easy to compute. They possess eight mathematical and economic features that lay a good foundation for electricity transmission pricing. The two imputation formulas are also extended to actual power systems where trades are conducted in MWh/MVARh instead of amperes/volts. Numerical examples illustrate their computing process and features. [ABSTRACT FROM AUTHOR]

The introduction of distributed generation (DG) is leading to a fundamental change in how distribution networks are utilized and viewed. Distribution networks are now used as a means to connect geographically dispersed energy sources to the electricity system, thereby converting what were originally energy delivery networks, to networks used both for the delivery and harvesting of energy. This paper presents a methodology which maximizes the amount of energy that may be reaped from a given area, while taking account of the available energy resources, connection costs, losses, frequency of constraint breaches, and other technical constraints. The optimal energy allocation is determined for a sample section of network, illustrating the implementation of the methodology and the scope for non firm access to the distribution network. [ABSTRACT FROM AUTHOR]

Energy storage can contribute to the resource-adequacy needs of power systems. However, the energy-limited nature of energy storage complicates estimating its resource-adequacy contribution. Energy storage that discharges to mitigate a loss-of-load event may have less energy available to mitigate a subsequent loss-of-load event. We present a stochastic-dynamic-optimization approach to capture such impacts endogenously. We demonstrate our approach using an example and two case studies, which show that energy storage's capacity value is sensitive to the load patterns of the system in which it is deployed. [ABSTRACT FROM AUTHOR]

An energy-based method to locate oscillation sources in power systems is proposed. The energy is identical to the transient energy. The amount of energy is consistent with the oscillation amplitude, and then the component producing energy has negative contribution to the damping and is considered as the oscillation source. The consistency of energy dissipation with damping torque of a generator is proved. A method to compute energy flow in the network based on wide area measurement system data and independent of energy functions is proposed. The energy dissipation or production of a component in the system can be obtained from the net energy flow. The components producing energy are oscillation sources and emergency control actions should be taken on them. The method is validated by simulations and actual oscillation incidents analyses. [ABSTRACT FROM PUBLISHER]

Imbalance-induced energy loss accounts for a significant part of energy loss in low-voltage distribution networks. However, due to the prohibitive cost of full monitoring, high-resolution time-series data of low-voltage feeder currents are usually absent for accurate energy loss computation. This letter presents a novel method to estimate the probability distribution of imbalance-induced energy loss. In the proposed method, only the line resistance and statistical data (mean and covariance) of the phase currents are required to estimate imbalanced networks’ energy loss. Furthermore, a Bayesian statistics-based data-driven method is also proposed to get the mean and covariance value of phase current with minimal measurements. Numerical tests on a real three-phase imbalanced circuit show the proposed approach obtains the probability distribution of imbalance-induced energy loss with a low estimating error and low field measurement frequency. [ABSTRACT FROM AUTHOR]

Metal oxide varistors (MOVs) are used in power distribution engineering to suppress lightning and switching surges. Techniques from solid state engineering as well as laboratory experiments have been used to derive models for these devices. The models so derived are combined with circuit models for the distribution system to obtain an integrated, lumped parameter, nonlinear model. The model is used to assess the voltage and current waveshapes in the MOV and to evaluate the energy dissipated in the MOV. The application of such a calculation is illustrated to assess the “energy rating” of an MOV arrester for an electronically controlled distribution circuit. Comments on the switching time of the MOV are provided: the characteristic time of impact ionization events is typically on the order of femtoseconds to picoseconds. [ABSTRACT FROM AUTHOR]

A newly proposed oscillation energy analysis method for power system low frequency oscillation is further developed. The oscillation energy flow in a generator and the energy dissipations of the field winding and the damper winding are studied. The oscillation energy flows into the field winding and the damper winding actually correspond to the electric energy transferred to the windings. The average powers of energy dissipation for oscillation modes with different frequencies are decoupled. For an individual mode, the energy dissipation of generator is computed using eigenvector and energy dissipation coefficient is obtained. The real-part of eigenvalue is negatively proportional to the sum of energy dissipation coefficients of all generators. It means the composite damping of the system comes from the energy dissipations of all generators. Especially in the single-machine system, the energy dissipation coefficient is equal to the damping torque coefficient. The consistency of oscillation energy analysis with damping torque analysis and modal analysis is verified. The energy dissipation leads to a new understanding of damping in power system and can be used for quantitative evaluation of generator damping in both offline and online applications. [ABSTRACT FROM PUBLISHER]

The problem of minimizing losses in distribution networks has traditionally been investigated using a single, deterministic demand level. This has proved to be effective since most approaches are generally able to also result in minimum overall energy losses. However, the increasing penetration of (firm and variable) distributed generation (DG) raises concerns on the actual benefits of loss minimization studies that are limited to a single demand/generation scenario. Here, a multiperiod AC optimal power flow (OPF) is used to determine the optimal accommodation of (renewable) DG in a way that minimizes the system energy losses. In addition, control schemes expected to be part of the future Smart Grid, such as coordinated voltage control and dispatchable DG power factor, are embedded in the OPF formulation to explore the extra loss reduction benefits that can be harnessed with such technologies. The trade-off between energy losses and more generation capacity is also investigated. The methodology is applied to a generic U.K. distribution network and results demonstrate the significant impact that considering time-varying characteristics has on the energy loss minimization problem and highlight the gains that the flexibility provided by innovative control strategies can have on both loss minimization and generation capacity. [ABSTRACT FROM AUTHOR]

Alternative vehicles, such as plug-in hybrid electric vehicles, are becoming more popular. The batteries of these plug-in hybrid electric vehicles are to be charged at home from a standard outlet or on a corporate car park. These extra electrical loads have an impact on the distribution grid which is analyzed in terms of power losses and voltage deviations. Without coordination of the charging, the vehicles are charged instantaneously when they are plugged in or after a fixed start delay. This uncoordinated power consumption on a local scale can lead to grid problems. Therefore, coordinated charging is proposed to minimize the power losses and to maximize the main grid load factor. The optimal charging profile of the plug-in hybrid electric vehicles is computed by minimizing the power losses. As the exact forecasting of household loads is not possible, stochastic programming is introduced. Two main techniques are analyzed: quadratic and dynamic programming. [ABSTRACT FROM AUTHOR]

Focuses on the proposed application of a statistical procedure for the determination of the standard levels of energy losses in primary distribution circuits. Methodology for the standardization of the level of energy losses; circuit Stratification with respect to levels of losses; Categorization of the level of energy losses.

Presents a study which addressed the issue of how transmission power losses should be allocated. Impact of transmission in competition in the electric power industry; Methods; Conclusions.

Presents a method for energy loss reduction for distribution networks. Symbols use in the study; Definition of the problem; The energy loss minimization method; Results of the test; Conclusions.

This letter presents a method for tracking the damping contribution of a power system component in near real-time based upon oscillation energy dissipation. By transforming the energy flow into the frequency domain, the new derivation demonstrates a new theoretical basis and a wider applicability of using the energy-flow theory to analyze power system damping problems. The concept is demonstrated via a non-linear simulation and an actual-system data set. [ABSTRACT FROM PUBLISHER]