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Since power transformers are valuable components of power networks, reliable determination of the remaining lifetime of a transformer is very important for power utilities. Power transformers consist of oil, a core, wire, and paper (cellulose), and their performance and remaining useful lifetime depend on the state of the oil-impregnated paper. Changing the oil over the lifetime of a transformer is possible, but it is not possible to change the insulation paper. Thus, the end of the paper lifetime will also be the end of the transformer lifetime (typically more than 40 years). The health condition of an in-service power transformer can be assessed by chemical and electrical tests of the oil and the paper [1]. [ABSTRACT FROM PUBLISHER]

Presents a listing of the editorial board, board of governors, current staff, committee members, and society editors for this issue of the publication. [ABSTRACT FROM PUBLISHER]

These instructions give guidelines for preparing papers for this publication. Presents information for authors publishing in this journal. [ABSTRACT FROM PUBLISHER]

The article discusses various papers published in various sections of this journal including one by Heydt et al. on electric power and energy engineering, one by Kezonuvic et al. on smart grid and one by Froyd et al. on engineering education.

This paper presents parameter values and ranges of static load models used in a power system analysis for the representation of both individual electrical devices and aggregate system loads. The paper discusses and correlates load models and their parameters following statistical processing of the responses of around 100 transmission system operators and utilities around the world, who participated in a survey initiated by CIGRE Working Group C4.605, with the corresponding information on load models and their parameter values from the existing literature. According to the survey, the most frequently used static load models are voltage dependent, and voltage and frequency dependent exponential load models. The identified typical parameter values and ranges of these static load models, both for low voltage devices and for aggregate loads at higher voltage levels, are results of the analysis of a large number of data. Based on these results, the paper provides recommendations for their further use in power system studies and also introduces a novel method for obtaining the mean values and ranges of parameters of the aggregate system load models. [ABSTRACT FROM AUTHOR]

As innovative energy-related technologies are rapidly developing, new elements are populating the electrical power grid, such as unpredictable renewable energies, plug-in electric vehicles (EVs), smart electrical home appliances, energy efficient homes/buildings, and distributed energy storage. All these elements induce a paradigm shift in power grids, which are evolving from producer-controlled structures to large, distributed, and customer-interactive ones, enhancing the coupling between the physical and the information layer. In order to be effectively employed on a large scale, all these elements must rely on automation, as well as on optimization methods, for the efficient management and consumption of energy resources under varying stochastic conditions. Driven by these changes, power grids have become complex and large-scale platforms with growing needs for automation and optimal energy management services, a concept that can be referred to as smart grids. [ABSTRACT FROM AUTHOR]

In this paper, we study the coordination between biogas producers who can use the biogas themselves, exchange biogas with their neighbors, or deliver it to the various energy grids, such as the low pressure gas grid or the power grid. These producers are called prosumers. In this setting, gas storage, fuel cells, microcombined heat power systems, and heat buffers are all part of the prosumers’ node. We aim to optimize the imbalance, profit, and comfort levels per prosumer, while taking the constraints of the energy grids into account and while allowing prosumers to exchange energy with each other. This results in a two-layer optimization problem formulation. In addition, in practice, the communication between prosumers among each other and with grid operators is done in an asynchronous manner. In this paper, we study the problem of two-layer optimization for biogas prosumers embedded in multiple energy grids, while the (bidirectional) communication between the various partners is done asynchronously. We prove the convergence of the asynchronous coordination algorithm that uses both the inputs and the states. We conduct simulations for the biogas prosumer setting, using realistic data to illustrate the convergence of the algorithm and to study its practical implementation. [ABSTRACT FROM AUTHOR]

Preventive diagnosis and maintenance of transformers have become more and more popular in recent times in order to improve the reliability of electric power systems. Dielectric testing techniques such as return voltage measurement (RVM) and polarization-depolarization current (PDC) measurement are being investigated as potential tools for condition assessment of transformer insulation. A better understanding and analysis of the dielectric test results are only possible with a clear understanding of the physical behavior of the insulation system in response to moisture and aging. A circuit model, which describes the dielectric behavior of the transformer's main insulation system, has been parameterized in this paper. The values of the parameters of the model have been identified from the dielectric tests. A correlation has been developed between the physical condition of the insulation and the equivalent model parameters that enable a clear and transparent interpretation of the dielectric test results. [ABSTRACT FROM AUTHOR]

Networked microgrids that integrate the hydrogen fueling stations (HFSs) with the on-site renewable energy sources (RES), power-to-hydrogen (P2H) facilities, and hydrogen storage could help decarbonize the energy and transportation sectors. In this paper, to support the hydrogen-based networked microgrids planning subject to multiple uncertainties (e.g., RES generation, electric loads, and the refueling demands of hydrogen vehicles), we propose a two-stage stochastic formulation with mixed integer conic program (MICP) recourse decisions. Our formulation involves the holistic investment and operation modeling to optimally site and configure the microgrids with HFSs. The MICP problems appearing in the second-stage capture the nonlinear power flow of networked microgrids system with binary decisions on storage charging/discharging status and energy transactions (including the trading of electricity, hydrogen, and carbon credits to recover the capital expenditures). To handle the computational challenges associated with the stochastic program with MICP recourse, an augmented Benders decomposition algorithm (ABD) is developed. Numerical studies on 33- and 47-bus exemplary networks demonstrate the economics viability of electricity-hydrogen coordination on microgrids level, as well as the benefits of stochastic modeling. Also, our augmented algorithm significantly outperforms existing methods, e.g., the progressive hedging algorithm (PHA) and the direct use of a professional MIP solver, which has largely improved the solution quality and reduced the computation time by orders of magnitude. Note to Practitioners—This paper proposes an optimal planning model for electricity-hydrogen microgrids with the renewable hydrogen production, storage, and refueling infrastructures. Our planning model is extended under a two-stage stochastic framework to address the multi-energy-sector uncertainties, e.g., RES generation, electric loads, and the refueling demands of hydrogen vehicles. The first-stage problem is to optimize the siting and sizing plan of microgrids. Then, in the second-stage problem, the coordinated scheduling of electricity and hydrogen supply systems is modeled as second-order conic programs (SOCPs) to accurately capture the power flow representation under stochastic scenarios. Also, the logical constraints with binary variables are introduced to describe the energy transactions and storage operations, which results in an MICP recourse structure. Note that the stochastic MICP formulation could be very challenging to compute even with a moderate number of scenarios. One challenge certainly comes from integer variables that cause the problem nonconvex. Another challenge follows from the fact that the strong duality of SOCPs might not hold in general. To mitigate those two challenges, we prove that the continuous relaxation of our recourse problem has strong duality, and make use of that continuous relaxation and other enhancements to design an augmented decomposition algorithm. As revealed by our numerical tests, the proposed decomposition method outperforms PHA in both the solution quality and computational efficiency. Comparing to the PHA, our ABD method often achieves tighter bounds with trivial optimality gaps. Also, it could reduce the computation time by orders of magnitude. With the help of advanced analytical tool, the proposed planning framework can be readily implemented in real-world applications. [ABSTRACT FROM AUTHOR]

This paper, as an outcome of the EU project AREUS, heralds an optimization procedure that reduces up to 30% of energy consumption and up to 60% in peak power for the trajectories that have been tested on real industrial robots. We have evaluated a number of cost functions and tested our algorithm for a variety of scenarios such as varying cycle times, payloads, and single/multirobot cases in both ac- and dc-operated robot cells. The significance of our work is not only in the impressive savings, simplicity of implementation, and preserving path and cycle time, but also in the variety of test scenarios that include different kinds of KUKA robots. We have carried out the optimization and experiments in as realistic conditions as possible. [ABSTRACT FROM AUTHOR]

This paper presents an evaluation of the performance of different methods for estimating the parameters required for the application of the Disruptive Effect Model to the analysis of the breakdown characteristics of 15 kV distribution insulators subjected to lightning impulses. The tests involved the application of both the standard (1.2/50 μs) and non-standard lightning impulse voltage waveshapes (1.2/4 1.2/10 3/10 μs) and 7.5/30 μs)of positive and negative polarities. The obtained Vxt characteristics are compared with those predicted by the Disruptive Effect Model using the most common procedures for estimating the parameters necessary for its application, including a novel method which is presented in the paper. An analysis of the results relevant to the various procedures shows that the parameters obtained according to the proposed method lead to a better agreement between theoretical and experimental results. [ABSTRACT FROM AUTHOR]

Merchant transmission planning is considered as a further step toward the full liberalization of the electricity industry. However, previous modeling approaches do not comprehensively explore its social efficiency as they cannot effectively deal with a large number of merchant companies. This paper addresses this fundamental challenge by adopting a novel non-cooperative game-theoretic approach. Specifically, the number of merchant companies is assumed sufficiently large to be approximated as a continuum. This allows the derivation of mathematical conditions for the existence of a Nash equilibrium solution of the merchant planning game. By analytically and numerically comparing this solution against the one obtained through the traditional centralized planning approach, the paper demonstrates that merchant planning can maximize social welfare only when the following conditions are satisfied: a) fixed investment costs are neglected and b) the network is radial and does not include any loops. Given that these conditions do not generally hold in reality, these findings suggest that even a fully competitive merchant transmission planning framework, involving the participation of a very large number of competing merchant companies, is not generally capable of maximizing social welfare. [ABSTRACT FROM AUTHOR]

Load modeling is essential for designing and operating power systems. This paper presents an approach for load modeling on smaller power systems that could be “islanded,” an approach that preserves the detail of a full differential equation simulation of relevant loads while requiring far less computation by employing behavioral models of important loads. Mixed domain models, e.g., stochastic, finite-state machine, and differential equation models, are employed to provide accuracy in a computationally tractable framework. Where simple load models may not be adequate, particularly for generation-constrained systems (in a paper by Sotiropoulos ), and full models are computationally unfavorable, this approach provides excellent results that enable “what-if” studies and flexible re-evaluation during power system design and operational assessment. Naval vessels, particularly warships with relatively large and increasing load power requirements, offer a unique laboratory for understanding isolated power grids. This paper examines the DDG-51 power distribution system as an example. [ABSTRACT FROM PUBLISHER]

This paper presents a new approach for determining the day-ahead bidding strategies of a large-scale hybrid electric energy company. The company has both energy generation and energy retailing businesses in a competitive electricity market. Demand response programs are also considered in the retail side of the company in order to hedge the risk of participation in wholesale market. This paper introduces a max-min bilevel mathematical programming with equilibrium constraint model for offering a strategy that manages the risk of uncertain forecasted rivals’ bids by robust optimization. The max-min bilevel model is converted to its equivalent single-level optimization using Karush–Kuhn–Tucker optimality conditions. The duality theory is utilized to find the equivalent ordinary maximization model of the max-min problem. Strong duality theory and big M method are also used to linearize the final model of offering strategy. Applicability of the proposed approach is shown by implementing it on the IEEE 118-bus test system. [ABSTRACT FROM AUTHOR]

A systematic method to evaluate the conflict between robustness, stability, and energy consumption is proposed in this paper. Energy optimization is combined with robust scheduling techniques to analyze the tradeoff. In rescheduling, slack is often used to protect a schedule from disruptions. However, results from the literature on energy minimization show that a reduction in energy consumption is achieved by extending the execution time of operations. Thus, slack in schedules is diminished on behalf of longer execution times. The proposed method, which quantitatively shows this conflict, is based on a multiobjective optimization formulation where efficient computation of the involved criteria is developed. This includes a convex surrogate stability measure that makes it possible to evaluate different operation sequences by a mixed-integer nonlinear programming formulation. Previous works connecting the two research fields use simulation for analyzing the impact of disruptions in order to generate robust production schedules. Our results show that an increase in energy efficiency comes at a cost of reducing stability and robustness and hence becoming more sensitive to disruptions. [ABSTRACT FROM AUTHOR]

Driven by smart grid technologies, distributed energy resources (DERs) have been rapidly developing in recent years for improving reliability and efficiency of distribution systems. Emerging DERs require effective and efficient coordination in order to reap their potential benefits. In this paper, we consider an optimal DER coordination problem over multiple time periods subject to constraints at both system and device levels. Fully distributed algorithms are proposed to dynamically and automatically coordinate distributed generators with multiple/single storages. With the proposed algorithms, the coordination agent at each DER maintains only a set of variables and updates them through information exchange with a few neighbors. We show that the proposed algorithms with properly chosen parameters solve the DER coordination problem as long as the underlying communication network is connected. The simulation results are used to illustrate and validate the proposed method. [ABSTRACT FROM AUTHOR]

Energy storage (ES) is playing a vital role in providing multiple services in several electricity markets. However, the benefits and risks vary across markets and time, which justifies the importance to optimize ES capacity share in different markets. In this paper, a novel portfolio theory-based approach is proposed for optimally managing ES in various markets to maximize benefits and reduce the risk for ES owners. Three markets are considered, which are energy arbitrage, ancillary services, and distributed network operator's market. They are modeled based on energy cost, frequency response cost, and system congestion cost. Portfolio theory is utilized to quantify ES capacity allocated to each market over time for various levels of risk aversions. The relation between risks and expected return of different markets is efficiently reflected by the portfolio theory, providing implications to storage operation. The extensive demonstration illustrates that the markets that storage can participate in are fundamentally different regarding to its risk aversion. In addition, the optimum portfolio of the markets for storage is on the efficient frontier, providing the maximum return at a certain risk aversion level. This study is particularly useful for guiding market participation and operation of ES to gain maximum economic return at minimum risk. [ABSTRACT FROM AUTHOR]

This paper presents an inverter-interfaced distributed generation (DG) device, dubbed the premium power supply (PPS), which is designed to provide reliable electric power, and to improve power quality. This paper proposes an effective configuration for the PPS, using inverters, an inter-tie breaker, and a small generating unit. When the DGs are operated in parallel with the utility systems, some problems occur due to interconnections on such categories as reverse power flow and island protection. This paper advances both an operating strategy and a control scheme for the PPS, with respect to the interconnection standard, IEEE Standard 1547. Simulation results demonstrate the efficacy of the PPS. [ABSTRACT FROM AUTHOR]

This paper empirically explores the organizational processes at the onset of disruptions and the factors that determine different configurations of responses. It examines how processes of response, both before and in the aftermath of a disruption, support the building and development of organizational resilience. Using case study data from three U.K. based organizations, this paper makes the following three contributions. First, it identifies the common elements involved in decision making at the onset of a disruption, and explains the iterative stages and processes that led to the development of resilience. It explains the criticality and relationships between the elements of detection, activation, and response. Second, this paper explains why responses vary from one situation to another, by identifying two dimensions that determine the configurations of organizational resilience, namely Preparedness and Adaption. Third, this paper presents the resilience configurations matrix that gives rise to and establishes four distinct types of organizational configurations, which are Process Based, Resourceful, At High Risk, and Resilience Focused. This paper concludes by discussing the implications for theory and practice of resilience. [ABSTRACT FROM AUTHOR]

This paper develops an equilibrium-based model for ex ante analysis of capacity withholding under financial virtual divestiture in a day-ahead market, including one dominant producer and a number of small producers considered as a price-taking competitive fringe. We model the offering problem of the dominant producer as a bilevel optimization problem. In the upper-level problem, the dominant producer derives optimal strategy of physical capacity withholding restricted by operational limits of its own generating units and conditions stated in the financial virtual divestiture. In the lower-level problem, market operator clears the day-ahead market on an hourly basis. We recast the bilevel optimization problem as a mathematical programming with equilibrium constraints problem and convert it to a mixed integer linear programming problem. We show how the application of the financial virtual divestiture may mitigate market power in the day-ahead market, through a case study. The numerical results demonstrate that the dominant producer can exploit technological diversification of its own generating units to exercise market power, even in the presence of this market power mitigation policy. [ABSTRACT FROM PUBLISHER]

This paper proposes a generalized approach of the per unit normalization, named complex per unit normalization (cpu), to improve the performance of fast decoupled power flow methods applied to emerging distribution networks. The proposed approach takes into account the changes envisaged and also already faced by distribution systems, such as high penetration of generation sources and more interconnection between feeders, while considering the typical characteristics of distribution systems, as the high R/X ratios. These characteristics impose difficulties on the performance of both backward-forward sweep and decoupled-based power flow methods. The cpu concept is centred on the use of a complex volt-ampere base, which overcomes the numerical problems raised by the high R/X ratios of distribution feeders. As a consequence, decoupled power flow methods can be efficiently applied to distribution system analysis. The performance of the proposed technique and the simplicity of adapting it to existing power flow programs are addressed in the paper. Different distribution network configurations and load conditions have been used to illustrate and evaluate the use of cpu. [ABSTRACT FROM PUBLISHER]

A challenging issue in photovoltaic (PV) systems is the performance monitoring of the PV panels. This is useful to detect the causes that might lower the energy production. In this paper, a novel technique for the transmission of the data obtained by a real time monitoring of a PV system is proposed. The PV panel's voltage, current, and temperature are measured by means of a low-cost smart monitoring and communications module and transferred to the central control system using power lines carriers communications technology on already existing dc power lines, which avoid additional installations costs. Simulations and experimental results together with an estimation of the measurement uncertainty are presented in order to validate the proposed idea. [ABSTRACT FROM PUBLISHER]

The last five years have been one of the most exciting times for the energy storage industry. We have seen significant advancements in the regulatory process to make accommodations for valuing and monetizing energy storage for what it provides to the grid. The most impactful regulatory decision for the energy storage industry has come from California, where the California Public Utilities Commission issued a decision that mandates procurement requirements of 1.325 GW for energy storage to three investor-owned utilities in four stages in 2014, 2016, 2018, and 2020. Furthermore, at the federal level, the U.S. Federal Energy Regulatory Commission's (FERC's) Order 755 requires transmission operators to develop pay-for-performance tariffs for ancillary services. This has had a direct impact on the market design of U.S. competitive wholesale markets and the monetization of fast-responding grid assets. While this order is technology neutral, it clearly plays into the fast-responding capability of energy storage technologies. Today, PJM, CAISO, MISO, NYISO, and NE–ISO have implemented Order 755 and offer new tariff-for-regulation services based on pay-for-performance principles. Furthermore, FERC Order 784, which was issued in July 2013, requires transmission providers to consider speed and accuracy in determining the requirements for ancillary services. In November 2013, FERC issued Order 972, which revises the small generator interconnection agreement that declares energy storage as a power source. This order puts energy storage on par with existing generators. This paper will discuss the implementation of FERC's pay-for-performance regulation order at all independent service operators (ISOs) in the United States under FERC regulatory authority (this excludes ERCOT). Also discussed will be the market impacts and overall impacts on the NERC regulation performance indexes. The paper ends with a discussion on the California, New York, and Ontario, Canada, procurement mandates and the opportunity that it may present to the energy storage industry. [ABSTRACT FROM PUBLISHER]

Energy systems are complex systems consisting of different decision making entities: policy makers (or system operators), generation companies, utility companies, and consumers. In this paper, the focus is on the decisions made by different market competitors, such as the energy generation companies (GENCOs) and their interactions with the policy makers. The goals of the independent system operators (ISOs) in a deregulated market are to minimize the policy cost and to maximize renewable energy penetration. The problem formulation presented in this paper is aimed toward helping the ISO in modeling the lower-level GENCOs' decision problems. GENCOs compete in energy production, while maximizing their net present values and minimizing their capital investments. The market players' decisions result in a lower-level market equilibrium problem, which is formulated as a complementarity problem. The existence and uniqueness of the solution for the lower-level problem are shown. The main aims of the paper are to study the effect of stakeholders' preferences on the solution of the complementarity problem, to analyze the effect of the ISO's design parameters on the generation equilibrium quantities, and to simulate the stochastic complementarity problem using different techniques. The applications of the proposed decision-making framework include computational modeling of policy design scenarios, such as in feed-in-tariff policies. [ABSTRACT FROM AUTHOR]

This paper proposes a mathematical model for transmission planning in an environment where there is imperfect competition in electricity supply industry. The model is developed based on the concept of the leader-followers game in applied mathematics. The leader of the game is the transmission planner and the followers are the strategic electricity producing firms. The reaction of the strategic electricity producing firms to the transmission planning decision is modeled using the introduced concept of the worst-Cournot-Nash equilibrium. The worst-Cournot-Nash equilibrium can handle the multiple Nash equilibria problem. The whole mathematical formulation is a bilevel mixed-integer linear programming problem. This formulation is achieved using the Karush-Kuhn-Tucker optimality conditions and a binary mapping approach. The application of the proposed approach to the three-node example system and the modified six-node Garver's example system are studied. The transmission planning with perfect competition is formulated and used as the benchmark. The numerical results show that the proposed approach in this paper can efficiently allocate the additional transmission capacity to the transmission grid such that it reduces the market power cost in the electricity supply industry. However, further studies should be carried out to scale up the proposed approach to the larger case studies. [ABSTRACT FROM PUBLISHER]

This paper presents the solution algorithm and test results of the market-splitting approach, proposed in the first part of this two-paper series, for the clearing of the forthcoming Internal Electricity Market. The market-splitting approach is implemented in a Europe-wide level, indicatively defining three power pools and 22 power exchanges, comprising 42 bidding areas in total, with each local/national market respecting the standard market regulatory framework of power pools and power exchanges (PXs). The performance and computational requirements of this implementation is presented; the model is tested in terms of problem solvability to its limits, considering a day-ahead market clearing time threshold equal to one hour. The results demonstrate that a viable solution to the clearing of the Internal Electricity Market can be attained with the current state-of-the-art of computers' processing power. Further discussion is made concerning the viability of the proposed approach and other harmonization issues that should be considered for successful market integration. [ABSTRACT FROM PUBLISHER]

In this paper, an online empirical mode decomposition (EMD) based algorithm is proposed for the control of a shunt active filter (AF). Standard EMD algorithm has worked on the principle of time-scale difference between the upper maximum values and lower minimum values of a signal, and for a long time it has been considered good for offline analysis of signals. This paper deals with the real-time application of EMD for the control of AF under balanced and unbalanced loads. Linear interpolators are employed for construction of upper and lower envelopes to avoid computation complexity. Moreover, customized iterative computations for extraction of intrinsic mode functions maintain the efficiency of algorithm. The algorithm extracts the fundamental component of load current and helps in estimating reference currents. Simulations are performed on MATLAB/Simulink platforms. Simulation results are verified with experimental results of a developed prototype of shunt AF. [ABSTRACT FROM PUBLISHER]

This paper applies two experimental economics methods (i.e., agent-based modeling and laboratory experiment) to a market test suite that is based on a fictional European wholesale electricity market. Quantitative results of generators' strategic behavior in this market context are separated between generators played by human subjects (i.e., master students) in a laboratory experiment and generators represented by computational agents in an agent-based model. The behavior is measured through offers that students or agents make when participating in the electricity trading auction and the market outcomes under both methods are discussed in order to illustrate the difference between the behavior of human and computational agents. The paper also identifies the improvements that would need to be made to the market test suite to allow for a more conclusive comparison in future experiments. [ABSTRACT FROM PUBLISHER]

This paper demonstrates how a probabilistic criterion could be explicitly integrated in the unit commitment (UC) formulation. Both spinning reserve and interruptible load are taken into account as the operating reserve facilities. Incorporating the interruption notice time of interruptible load involves some complexities in the evaluation procedure and problem formulation which is considered in this paper. The expected energy not supplied (EENS) is considered as a probabilistic criterion and a new method is proposed to calculate this index in the presence of interruptible load. The reliability-constrained unit commitment (RCUC) problem is formulated based on the mixed-integer programming (MIP) method that can be solved using large-scale commercial solvers. The effectiveness of the proposed formulation is examined using the IEEE-RTS. Numerical results are presented and the implementation issues are discussed. A number of analyses are examined to evaluate the impact of some important factors on the problem solution. [ABSTRACT FROM AUTHOR]

This is the second part of a two-part paper that has arisen from the work of the IEEE Power Engineering Society's Multi-Agent Systems (MAS) Working Group. Part I of this paper examined the potential value of MAS technology to the power industry, described fundamental concepts and approaches within the field of multi-agent systems that are appropriate to power engineering applications, and presented a comprehensive review of the power engineering applications for which MAS are being investigated. It also defined the technical issues which must be addressed in order to accelerate and facilitate the uptake of the technology within the power and energy sector. Part II of this paper explores the decisions inherent in engineering multi-agent systems for applications in the power and energy sector and offers guidance and recommendations on how MAS can be designed and implemented. Given the significant and growing interest in this field, it is imperative that the power engineering community considers the standards, tools, supporting technologies, and design methodologies available to those wishing to implement a MAS solution for a power engineering problem. This paper describes the various options available and makes recommendations on best practice. It also describes the problem of interoperability between different multi-agent systems and proposes how this may be tackled. [ABSTRACT FROM AUTHOR]

This is the first part of a two-part paper that has arisen from the work of the IEEE Power Engineering Society's Multi-Agent Systems (MAS) Working Group. Part I of this paper examines the potential value of MAS technology to the power industry. In terms of contribution, it describes fundamental concepts and approaches within the field of multi-agent systems that are appropriate to power engineering applications. As well as presenting a comprehensive review of the meaningful power engineering applications for which MAS are being investigated, it also defines the technical issues which must be addressed in order to accelerate and facilitate the uptake of the technology within the power and energy sector. Part II of this paper explores the decisions inherent in engineering multi-agent systems for applications in the power and energy sector and offers guidance and recommendations on how MAS can be designed and implemented. [ABSTRACT FROM AUTHOR]

This paper analyzes the behavior of Hong's point estimate methods to account for uncertainties on the probabilistic power flow problem. This uncertainty may arise from different sources as load demand or generation unit outages. Point estimate methods constitute a remarkable tool to handle stochastic power system problems because good results can be achieved by using the same routines as those corresponding to deterministic problems, while keeping low the computational burden. In previous works related to power systems, only the two-point estimate method has been considered. In this paper, four different Hong's point estimate schemes are presented and tested on the probabilistic power flow problem. Binomial and normal distributions are used to model input random variables. Results for two different case studies, based on the IEEE 14-bus and IEEE 118-bus test systems, respectively, are presented and compared against those obtained from the Monte Carlo simulation. Particularly, this paper shows that the use of the 2m + 1 scheme provides the best performance when a high number of random variables, both continuous and discrete, are considered. [ABSTRACT FROM AUTHOR]

This paper proposes to introduce additional constraints in the directional overcurrent relay coordination problem to tackle the sympathy trips. This paper attempts to tackle the sympathy trips in which other relay(s) in the system operate(s) earlier in the designated primary relay. The solution to this problem requires the inclusion of some additional constraints, making the coordination problem too complex. This paper proposes to solve the problem in two phases. In the first phase, the problem is solved by a normal coordination procedure and sympathy trips are identified. In the second phase, the proposed additional constraints are imposed only for the sympathy trips identified in the first phase. For the second phase, three approaches for including additional constraints were investigated. This paper includes results of the proposed algorithm for the IEEE 30-bus system. The results amply suggest that one of the three approaches of including additional constraints successfully tackled the problem of sympathy trip. [ABSTRACT FROM AUTHOR]

In this paper, the frequency-dependent characteristic impedance and propagation constant of lossy transmission lines have been extracted from one-port time-domain reflectometry (TDR) measurements. Nonphysical resistance (R), inductance (L), conductance (C) and capacitance (C) (RLGC) models have been developed for simulating lossy transmission lines using the extracted data. The extraction method has been demonstrated for transmission lines on an organic substrate such as coplanar lines. Using the extracted data and nonphysical RLGC models, the simulation results show good correlation with TDR measurements for coplanar lines. [ABSTRACT FROM AUTHOR]

There is increasing interest in the new deregulated electric utility environment in assessing the customer costs associated with failures in electric power supply and the responsibilities associated with these failures. The customer interruption cost when an electric supply failure occurs depends on many factors, such as the customer types interrupted, the actual load demand at the time of the outage, the duration of the outage, the time of day and the day in which the outage occurs. The absence of many of the data sets required in a detailed evaluation of the customer costs makes it difficult to estimate precise individual customer outage costs due to a specific failure event. This paper illustrates the development of approximate methods for event-based customer interruption cost evaluation on a distribution feeder subjected to a specific outage event. A series of approximate methods are presented and the outage cost estimates are compared with a set of base method results. The approximate methods are based on the use of customer sector data sets, i.e., commercial, industrial, residential data, which are generally available to most utilities. The paper also illustrates further simplifications of the approximate techniques which reduce the effort required to estimate the outage costs. The approximate techniques provide a practical approach to evaluating a specific outage event. [ABSTRACT FROM AUTHOR]

We present in this paper a short-term scheduling of battery in security-constrained unit commitment (SCUC). For economical operation and control purposes, electric power users with photovoltaic (PV)Ibattery systems are interested in the availability and the dispatch of PV/battery power on an hourly basis, which is a cumbersome task due to the complicated operating patterns of PV/battery. The details of battery model in the PV/battery system are presented in this paper. The paper applies a Lagrangian relaxation-based optimization algorithm to determine the hourly charge/discharge commitment of battery in a utility grid. The paper also applies a network flow programming algorithm for the dispatch of committed battery units. The paper analyzes the impact of grid-connected PV/battery system on locational pricing, peak load shaving, and transmission congestion management. An eight-bus test system is used to study the operational pattern of aggregated PV/battery and demonstrate the advantages of utilizing PV/battery systems in the electric utility operation. [ABSTRACT FROM AUTHOR]

The Metal Oxide Varistor (MOV) has been widely utilized in the power industry due to its high degree of nonlinearity and excellent capability of carrying a large amount of electrical current. Though studies have been conducted to understand the current response of the MOV to step voltages qualitatively, modeling the current-step voltage relationship of the MOV quantitatively has never been reported. This paper presents the investigation into the current responses of the MOV to step voltages with different amplitudes. An equivalent circuit representing the MOV in the whole current region and a method for determining its corresponding circuit parameters are proposed based on the fact that the MOV shows polarized current in the low current region and displays conducting delay effect in the heavy current region. Also in the paper, the current response curves of the MOV under different step voltages are analyzed theoretically and experimentally. In order to obtain the dynamic resistance and the dynamic inductance, the current response curve is formulized quantitatively using the exponential equation when the step voltage is small and a diagrammatizing method is adopted when the step voltage is large. The authors discovered that the equivalent circuit of MOV mainly consisted of four branches: the capacitance branch, two polarized branches (fast-polarized branch and slow-polarized branch), and the nonlinear conducting delay branch. [ABSTRACT FROM AUTHOR]

This paper presents a novel approach to model the transfer function of electrical power lines for broadband power line communication. In this approach, the power line is approximated as a transmission line and the two intrinsic parameters, the characteristic impedance and the propagation constants, are derived based on the lumped-element circuit model. Using these intrinsic parameters, the transfer characteristics for a N-branch power distribution network are derived based on the scattering matrix method. Detail derivation of this line model is given in this paper. The model has been verified with practical measurements conducted on actual power networks. It is demonstrated that the model accurately determine the line characteristics under different network configuration and when different household appliances are connected. [ABSTRACT FROM AUTHOR]

Portfolios of renewable electricity sources are interesting risk-management mechanisms for trading in electricity contract markets. When formed by players belonging to different companies, their stability relies on the way the benefit generated by the optimal portfolio is allocated. The challenge of finding a fair and efficient allocation can be mathematically formulated in terms of finding the Core of a cooperative game, which in turn is stated as an optimization problem with a set of constraints that exponentially grows with the number of participants, quickly becoming computationally intractable. Moreover, the right-hand-side of each constraint relies on a given coalition value, which in our case is obtained by a two-stage stochastic optimization model. This paper presents an efficient methodology based on mixed —linear programming and Benders decomposition to find the Nucleolus share of large-scale renewable portfolios. Case studies are presented with data from the Brazilian power system. [ABSTRACT FROM PUBLISHER]

This paper presents a novel energy encryption strategy for wireless power transfer (WPT) systems, which can effectively improve the security performance of wirelessly transferred energy. In a WPT system, energy is expected to transfer to specific receptors as well as to switch off other unauthorized energy transmission channels, so the security of energy transmission is an important issue. In the proposed secure WPT system, the energy is encrypted by chaotically regulating the frequency of the power source. Then, the authorized receptor can receive the energy by simultaneously adjusting the circuit to decrypt the encrypted energy based on the security key obtained from the power supply, while the unauthorized receptor cannot receive the energy without knowledge of the security key. Hence, a secure energy transmission channel is established to effectively prevent unauthorized receptors from stealing the energy. In this paper, both simulation and experimental results are provided to verify the validity of the proposed encrypted WPT system. [ABSTRACT FROM AUTHOR]

This paper proposes a new formulation for the corrective security-constrained optimal power flow (SCOPF) problem with DC power flow constraints. The goal is to produce a generation schedule which has a minimal number of post-contingency corrections as well as a minimal amount of total MW rescheduled. In other words, the new SCOPF model effectively clears contingencies with corrective actions that have a minimal impact on system operations. The proposed SCOPF model utilizes sparse optimization techniques to achieve computational tractability for large-scale power systems. We also propose two efficient decomposition algorithms. Extensive computational experiments show the advantage of the proposed model and algorithms on several standard IEEE test systems and large-scale real-world power systems. [ABSTRACT FROM PUBLISHER]

In this paper, we propose a method to compute linear sensitivity distribution factors (DFs) in near real time without relying on a power flow model of the system. Specifically, we compute the injection shift factors (ISFs) of a particular line of interest with respect to active power injections at all buses (all other DFs can be determined from ISFs). The proposed ISF estimation method relies on the solution of an underdetermined system of linear equations that arise from high-frequency synchronized measurements obtained from phasor measurement units. We exploit a sparse representation (i.e., one in which many elements are zero) of the vector of desired ISFs via rearrangement by electrical distance and an appropriately chosen linear transformation, and cast the estimation problem into a sparse vector recovery problem. As we illustrate through case studies, the proposed approach provides accurate DF estimates with fewer sets of synchronized measurements than earlier approaches that rely on the solution of an overdetermined system of equations via the least-squares errors estimation method. [ABSTRACT FROM PUBLISHER]

Currently, demand response resources can sell load reductions in wholesale energy markets. However, paying for load reductions ultimately results in an unbalanced market, where the amount of resources sold (megawatts) is less than the amount of resources bought (megawatts and “negawatts”). To resolve this imbalance, the ISO must allocate the cost of compensating demand response to those buyers who benefit from reduced LMPs. Current cost allocation methods are quite broad and based on each energy buyer's share of the total load. In an uncongested network, this results in a “fair” allocation of costs, i.e., an allocation proportional to the benefits that each party accrues. However, in a congested network, this is no longer the case, as price separation occurs between nodes. In this paper, we therefore propose a cost allocation method based on LMP sensitivity that accounts for the effect of congestion on the distribution of benefits between nodes with different LMPs. Since this sensitivity-based method only takes into account the cost allocation per node, we also propose a means of allocating costs between individual load serving entities (LSEs) at a single node. Due to this refinement, LSEs are rewarded according to their individual contribution to demand response. Finally, we define a fairness index to evaluate the performance of the proposed method as compared to a load-based allocation. We find that when load reductions are small (1%–3% total load), the fairness index of the proposed method is very close to zero, indicating almost identical benefit to cost ratios for all market participants. Although the fairness index increases with increasing load reductions, results show that even for larger load reductions, the fairness index is still lower for the proposed method than for the load-based allocation method. [ABSTRACT FROM PUBLISHER]

This paper presents a new stochastic multi-layer agent-based model to study the behavior of electricity market participants. The wholesale market players including renewable power producers are modeled in the first layer of the proposed multi-agent environment. The players optimize bidding/offering strategies to participate in the electricity markets. In the second layer, responsive customers including plug-in electric vehicle (PEV) owners and consumers who participate in demand response (DR) programs are modeled as independent agents. The objective of the responsive customers is to increase their benefit while retaining welfare. The interaction between market players in day-ahead and real-time markets is modeled using an incomplete information game theory algorithm. Due to the uncertainties of resources and customers' behavior, the model is developed using a stochastic framework. A case study containing wind power producers (WPPs), PEV aggregators and retailers providing DR is considered to demonstrate the usefulness and proficiency of the proposed multi-layer agent-based model. [ABSTRACT FROM PUBLISHER]

The integration of artificial-intelligence techniques in traditional real-time systems is a promising approach to cope with the growing complexity of real-world applications. Real-time expert systems are online knowledge-based systems that combine analytical process models with conventional process control to monitor complex industrial processes and to assist in problem identification. The expert system interfaces with the external distributed control system (DCS) via an object linking and embedding for process control module which acquires measurement data and identifies processes alarms for diagnosis. This paper proposes generating new rules from the plant measurement data using a learning engine. We present an efficient algorithm that generates all significant rules based on the data. The association-based algorithms were compared and those best suited for this process application were selected. The application for the learning system is studied in a powerplant application This innovative approach should assist in sustainable growth of automation in the power sector. [ABSTRACT FROM PUBLISHER]

The application of cascaded multilevel converters in large-scale photovoltaic plants connected to the utility grid has many advantages, such as the absence of sinusoidal filters and line-frequency transformers. Improved overall performance under partial shading conditions is possible due to the distribution of arrays among a large number of maximum power point trackers. In this situation, although the cells operate at different power levels, the three-phase currents injected into the point of common coupling must be balanced. A suitable control technique is required to achieve this goal. This paper presents a complete algorithm to handle three-phase power balance and single-phase power harvesting simultaneously. Simulation results assuming a medium-voltage system connected to a typical utility grid illustrate the dynamic and steady-state performance capability of the proposed strategy. Experimental results of a low-voltage, solid-state transformer-based, three-cell prototype are also included. [ABSTRACT FROM AUTHOR]

Determining the Nash equilibria (NEs) in a competitive electricity market is a challenging economic game problem. Although finding one equilibrium has been well studied, detecting multiple ones is more practical and difficult, with a few attempts to solve such discrete game problems. However, most of the real-life game problems, such an energy market is a continuous one containing infinite sets of strategy that can be adopted by each player. Therefore, in this paper, a co-evolutionary approach is proposed for detecting multiple NEs in a single run involving continuous games among ${N}$ -players. Five standard test functions and three IEEE energy market problems in three different scenarios are solved, and their results are compared with those obtained from state-of-the-art algorithms. The results clearly show the benefits of the proposed approach in terms of both the quality of solutions and efficiency. [ABSTRACT FROM AUTHOR]

An algorithm facilitating automated purchase of energy on real-time balancing market is proposed in this paper. The main inputs of the algorithm are a prediction of the area control error, its uncertainty in the form of a standard deviation and a set of previously procured ancillary services (contracted power reserves) available for power balance control. The algorithm evaluates all possible power balance scenarios for the closest hour in a probabilistic manner and gives a cost-optimal recommendation for the real-time balancing market demand. A case study on realistic data for the Czech Republic control area was performed by simulation of the power balance control with a Monte Carlo simulator of the Czech transmission system. The results showed potential for savings on the regulation energy costs. [ABSTRACT FROM PUBLISHER]

Flux reversal machines (FRMs) have received extensive attentions in recent years due to their high torque densities, robust structures, fast transient responses, etc. This paper focuses on the analysis of the torque performances including average torque, cogging torque, and ripple torque of three-phase FRMs. First, the general expressions of instantaneous torque under no-load and rated-load conditions are analytically derived. Then, based on the analytical equations, the effects of rotor slot number, split ratio, permanent magnet thickness, and stator and rotor slot opening ratio on the torque performances are investigated and analyzed, which can be used for optimizing the structural parameters for maximum torque density and minimum pulsating torque. Finally, the theoretical analyses are validated by experiments on a 12-stator-slot/17-rotor-slot FRM prototype. Good agreements have been achieved between the simulated and experimental results. [ABSTRACT FROM PUBLISHER]

This paper proposes a novel multi-resolution clustering (MRC) method that for the first time classifies end customers directly from massive, volatile and uncertain smart metering data. It will firstly extract spectral features of load profiles by multi-resolution analysis (MRA), and then cluster and classify these features in the spectral-domain instead of time-domain. The key advantage is that the proposed method will allow a dynamic load profiling to be flexibly re-constructed from each spectral level. MRC addresses three key limitations in time-series based load profiling: i) large sample size: sample size is reduced by a novel two-stage clustering, which firstly clusters each customers' massive daily profiles into several Gaussian mixture models (GMMs) and then clusters all GMMs; ii) volatility: it avoids the interferences between different load features (e.g. magnitude, overall trend, spikes) by decomposing them onto different resolution levels, and then clustering separately; iii) uncertainties: as the GMM can give a probabilistic cluster membership instead of a deterministic one, an additive classification model based on the posterior probability is proposed to reflect the uncertainty between days. The proposed method is implemented on 6369 smart metered customers from Ireland, and compared with the load profiles used by the U.K. industry and traditional K-means clustering. The results show that the developed MRC outperformed the traditional methods in its ability in profiling load for big, volatile and uncertain smart metering data. [ABSTRACT FROM PUBLISHER]