Electric Power System Management Research Articles

Embedding Mosfets

A new technology that uses chip embedding of power MOSFETs in PCBs can meet increasing requirements for electrical power management systems

The Extended Kalman Filter in the Dynamic State Estimation of Electrical Power Systems

The state estimation and the analysis of load flow are very important subjects in the analysis and management of Electrical Power Systems (EPS). This article describes the state estimation in EPS using the Extended Kalman Filter (EKF) and the method of Holt to linearize the process model and then calculates a performance error index as indicators of its accuracy. Besides, this error index can be used as a reference for further comparison between methodologies for state estimation in EPS such as the Unscented Kalman Filter, the Ensemble Kalman Filter, Monte Carlo methods, and others. Results of error indices obtained in the simulation process agree with the order of magnitude expected and the behavior of the filter is appropriate due to follows adequately the true value of the state variables. The simulation was done using Matlab and the electrical system used corresponds to the IEEE 14 and 30 bus test case systems. State Variables to consider in this study are the voltage and angle magnitudes.

Inexact Fuzzy Chance-Constrained Fractional Programming for Sustainable Management of Electric Power Systems

An inexact fuzzy chance-constrained fractional programming model is developed and applied to the planning of electric power systems management under uncertainty. An electric power system management system involves several processes with socioeconomic and environmental influenced. Due to the multiobjective, multilayer and multiperiod features, associated with these various factors and their interactions extensive uncertainties, may exist in the study system. As an extension of the existing fractional programming approach, the inexact fuzzy chance-constrained fractional programming can explicitly address system uncertainties with complex presentations. The approach can not only deal with multiple uncertainties presented as random variables, fuzzy sets, interval values, and their combinations but also reflect the tradeoff in conflicting objectives between greenhouse gas mitigation and system economic profit. Different from using least-cost models, a more sustainable management approach is to maximize the ratio between clean energy power generation and system cost. Results of the case study indicate that useful solutions for planning electric power systems management practices can be generated.

A Multi-Objective Energy and Environmental Systems Planning Model: Management of Uncertainties and Risks for Shanxi Province, China

In this study, a fuzzy chance-constrained fractional programming (FCFP) approach is developed to help tackle various uncertainties involved in electric power systems (EPSs) management. The FCFP approach is capable of solving ratio optimization decision problems in power systems associated with random and fuzzy information by chance-constrained programming (CCP) method, fuzzy measure programming, fractional programming (FP) into a general framework. It can tackle inexact information expressed as fuzzy set and probability distributions, comprehensively reflect the decision maker’s pessimistic and optimistic preferences, and balance dual objectives of system economy and sustainability. To demonstrate its applicability, FCFP approach is then applied to a case study of Shanxi Province, a typical coal-heavy electricity region in China. The results indicate that the FCFP approach reveals uncertain interactions among the decision maker’s preferences and various random variables. Reasonable solutions have been generated for Shanxi EPS management practices, which can provide strategies in mitigating pollutant emissions, reducing system costs, and promoting coalbed methane as an alternative energy source for coal-fired and plays an essential role in Shanxi’s municipal planning. The solutions will help decision makers generate alternatives in the event of the reducing coal-fired power generation and could be applicable in other coal-heavy electricity regions.

Application of functional safety to electrical power equipment and systems in process industries

In process industries, the application of functional safety in preventing major incidents is a well-established practice. The functional safety standard IEC 61511 (IEC, 2016) is applied to the safety instrumented system (SIS) protection layers to avoid the undesired events or reduce the likelihood of the events or impacts due to failures in the process, process equipment, or its control system including human interactions. However, there are risks of catastrophic incidents due to electrical equipment failures as well. Therefore, one should not underestimate the importance of the management, design, installation, operation, and maintenance of electrical power systems and protection devices. Regulatory authorities, in some countries, require the owners or operators to address the risks that arise from electrical equipment failure.The risk-based assessment, allocation of safety functions to protection devices, the establishment of integrity requirements, design, installation, operation, and maintenance of electrical protection devices must be managed like the protection layers for the process units. This paper focusses on the application of IEC 61511 to the protection of electrical equipment and systems, available industry guidelines, and the unique challenges in implementing the functional safety standards. The paper guides the electrical engineers with an example risk assessment, identification of protection device and its safety integrity level (SIL), verification of the reliability of the protection device and establishing a maintenance and operation program.

Full-infinite interval two-stage credibility constrained programming for electric power system management by considering carbon emission trading

In this study, a full-infinite interval two-stage credibility constrained programming (FITCP) method is developed for optimizing electric power system (EPS) by considering CO2 mitigation and air pollutant emission control. Through integrating full-infinite programming (FIP), interval two-stage programming (ITSP) and credibility constrained programming (CCP) within a general framework, the developed FITCP method can tackle multiple uncertainties in terms of interval values (both crisp and functional interval values), probabilistic and possibilistic distributions. Then, a FITCP-based electric power system (FITCP-EPS) model has been formulated for EPS planning where carbon emission trading (CET) scheme and air pollutant emission limitation are introduced to cope with the problem of carbon and air pollutant mitigation. Scenarios in response to diverse carbon mitigation levels, different trading schemes and different environmental policies are generated. Moreover, sensitive analysis and value of information analysis are conducted to help decision makers to have a clear view of the effects of data variation and uncertainty data collection. Results reveal that (i) CET scheme can bring more economic benefits for power plants especially when mitigation level is high; (ii) whether the CET is carried out or not, a corresponding construction of carbon capture and storage infrastructure should be implemented to achieve the mitigation target; (iii) the expected system benefit would increase [0, 2.17] % by resolving the uncertainty of CO2 emission levels. The results also indicate that FITCP-EPS model can not only provide an effective linkage between the pre-regulated generation targets and environmental policies, but also generate more decision options under different credibility levels and CO2 emission levels, which are useful for helping decision makers to make appropriate generation targets, plan electricity generation mix, as well as gain in-depth insight into the effects of carbon emission trading and pollutant control on EPS.

Planning of Electric Power Systems Considering Virtual Power Plants with Dispatchable Loads Included: An Inexact Two-Stage Stochastic Linear Programming Model

In this study, an inexact two-stage stochastic linear programming (ITSLP) method is proposed for supporting sustainable management of electric power system under uncertainties. Methods of interval-parameter programming and two-stage stochastic programming were incorporated to tackle uncertainties expressed as interval values and probability distributions. The dispatchable loads are integrated into the framework of the virtual power plants, and the support vector regression technique is applied to the prediction of electricity demand. For demonstrating the effectiveness of the developed approach, ITSLP is applied to a case study of a typical planning problem of power system considering virtual power plants. The results indicate that reasonable solutions for virtual power plant management practice have been generated, which can provide strategies in mitigating pollutant emissions, reducing system costs, and improving the reliability of power supply. ITSLP is more reliable for the risk-aversive planners in handling high-variability conditions by considering peak-electricity demand and the associated recourse costs attributed to the stochastic event. The solutions will help decision makers generate alternatives in the event of the insufficient power supply and offer insight into the tradeoffs between economic and environmental objectives.

Conceptual study of a mechanically integrated parallel hybrid electric turbofan

In the paper, options for mechanically integrated parallel hybrid propulsion are evaluated, and a conceptual sizing and performance study of a mechanically integrated parallel hybrid electric turbofan engine for a short-range aircraft application is presented and discussed. Through a methodical down-selection procedure, a most promising power plant system architectural concept is identified from an initial cloud of concept candidates. The design of the preferred configuration is conceptualized including initial performance analyses, both at the isolated power plant as well as at the integrated aircraft level. Beside the basic power plant definition, the multidisciplinary concept elaboration includes solutions proposed for the electric systems architectural layout, the major electrical components involved as well as important airframe integration aspects. The components of the electrical power management and distribution system are sized, and efficiency and weights are evaluated under special consideration of thermal management requirements. In result, a best and balanced degree of power hybridization is determined for the studied mechanically integrated parallel hybrid power plants taking account of electric system design and weight impacts as well as power plant operational robustness in case of electric system failure. The overall system assessment includes the evaluation of fuel reduction potentials through a parametric aircraft sizing study including the derivation of key technological requirements for onboard electrical energy storage. In the paper, essential design and sizing strategies for mechanically integrated parallel hybrid aero propulsion systems are derived, and a brief characterization of the associated key technological challenges is provided.

Induction Machine for More Electric Aircraft: Enabling New Electrical Power System Architectures

With the trend toward more electric aircraft (mea), the onboard electrical power generation and distribution requires increased electrical power-generation capacity; improved electrical power system (EPS) availability and reliability; and optimized system weight, volume, and efficiency. New EPS architectures are needed to fulfill these performance improvement requirements, where the type of electrical generator can have greater impact on the fundamentals of the newly designed EPS architecture. This article explores the option of using an induction generator in a distributed EPS for commercial transport MEA. Induction generator-based electrical power generation and management system architectures for both the main-engine generation system and auxiliary power unit (APU) system are introduced, with a brief explanation of their operation principles and control methods.

An inexact multistage fuzzy-stochastic programming for regional electric power system management constrained by environmental quality

Electric power system involves different fields and disciplines which addressed the economic system, energy system, and environment system. Inner uncertainty of this compound system would be an inevitable problem. Therefore, an inexact multistage fuzzy-stochastic programming (IMFSP) was developed for regional electric power system management constrained by environmental quality. A model which concluded interval-parameter programming, multistage stochastic programming, and fuzzy probability distribution was built to reflect the uncertain information and dynamic variation in the case study, and the scenarios under different credibility degrees were considered. For all scenarios under consideration, corrective actions were allowed to be taken dynamically in accordance with the pre-regulated policies and the uncertainties in reality. The results suggest that the methodology is applicable to handle the uncertainty of regional electric power management systems and help the decision makers to establish an effective development plan.

SAMPLING OF THE PLAN OF REPAIRS OF THE MAIN EQUIPMENT IN THE ELECTRICAL POWER SYSTEM

The main aspects of creation of the formal-and-functional mathematical models supporting a system for prompt resolution of repair requires in a complex electric power system are considered in the article. In accordance with the standards of repairs, inspections, replacement of elements of the main equipment or devices of a system of automation, inclusion of spare capacity, various switches, as well as with the frequency of outages adopted in practice, the decisionmaking process is formalized and automated as the problem of scheduling optimal daily schedules of blackouts, functioning as a part of automated system of dispatching management of electric power system. The main problems that hinder mathematical modeling of decision-making concerning operational applications for the repair of the main power equipment of power system are: the need for a coherent account of a large number of limiting factors and indicators of effectiveness of the solutions; the need of information and algorithmic trade-offs with the objectives of adjacent levels of spatial, temporal and functional hierarchy; the lack of developments in the standardization of information structures that adequately reflect the process of finding solutions; the computational complexity of several restrictions of the optimization problem subject to mandatory registration.

A fuzzy-stochastic power system planning model: Reflection of dual objectives and dual uncertainties

In this study, a fuzzy stochastic dynamic fractional programming (FSDFP) method is proposed for supporting sustainable management of electric power system (EPS) under dual uncertainties. As an improvement upon the mixed-integer linear fractional programming, FSDFP can not only tackle multi-objective issues effectively without setting weights, but also can deal with uncertain parameters which have both stochastic and fuzzy characteristics. Thus, the developed method can help provide valuable information for supporting capacity-expansion planning and in-depth policy analysis of EPS management problems. For demonstrating these advantages, FSDFP has been applied to a case study of a typical regional EPS planning, where the decision makers have to deal with conflicts between economic development that maximizes the system profit and environmental protection that minimizes the carbon dioxide emissions. The obtained results can be analyzed to generate several decision alternatives, and can then help decision makers make suitable decisions under different input scenarios. Furthermore, comparisons of the solution from FSDFP method with that from fuzzy stochastic dynamic linear programming, linear fractional programming and dynamic stochastic fractional programming methods are undertaken. The contrastive analysis reveals that FSDFP is a more effective approach that can better characterize the complexities and uncertainties of real EPS management problems.

The Need for a Whole Life Framework in Electrical Power System Asset Management and the Problems with Individual Silo like Asset Management System Contributions

The asset management of electrical power systems both in industry and academia currently offers up a wide spectrum of engineering practices and guidance to detect, diagnose and to combat asset deterioration. In doing so research largely aims to better enable enhanced decision or prediction making in single engineering applications such as partial discharge or dielectric condition measurements. This paper reviews the current state of the art as related to electrical asset management and sets out how todays engineering and maintenance heavy approaches are insufficient to meet the nature of the complex adaptive (Generation, Transmission & Distribution) systems. Furthermore this paper explains the need for a truly holistic governance framework capable of managing such complexities for power companies by using complex adaptive system science whilst grounded in the engineering, business and socio-technical attributes that applied engineering makes possible. In addition this paper outlines how utilising retroductive case study with hypothesis framework represents the best approach in creating such a fully holistic asset management capability for power companies.

Control of Energy Storage Systems for Aeronautic Applications

Future aircraft will make more and more use of automated electric power system management onboard. Different solutions are currently being explored, and in particular the use of a supercapacitor as an intelligent energy storage device is addressed in this paper. The main task of the supercapacitor is to protect the electric generator from abrupt power changes resulting from sudden insertion or disconnection of loads or from loads with regenerative power capabilities, like electromagnetic actuators. A controller based on high-gain concepts is designed to drive a DC/DC converter connecting the supercapacitor to the main electric bus. Formal stability proofs are given for the resulting nonlinear system, and strong robustness results from the use of high-gain and variable structure control implementation. Moreover, detailed simulations including switching devices and electrical parasitic elements are provided for different working scenarios, showing the effectiveness of the proposed solution.

Load curve classification for the evaluation of demand side management programs

The demand side management of electrical power systems is an issue of growing concern. In this study, annual load curves those have been obtained by field measurements on MV (31.5kV) feeders in an electricity distribution company in Turkey have been studied. Feeders supplying different type of customers (Agricultural irrigation, Commercial & Industrial and Residential) are classified through Peak and Night Ratio for the assessment of convenient incentive or price based methods. Statistical parameters, such as peak-to-average ratio, load factor and standard deviation are calculated. Active power deviations on annual and daily load curves are discussed.

A Fine Day for an Eclipse: It's Never Too Early to Start Planning for One

On 21 August 2017, the United States will experience one of the most amazing phenomena imaginable. A total eclipse of the sun will occur, and essentially everyone in the contiguous 48 states will experience it to some extent. What?s more, the so-called "path of totality" will stretch from coast to coast-Oregon to South Carolina (Figure 1). It's likely that more people will experience this solar eclipse than any in history. The approximately 12 million people who live within the 70-mi-wide path of totality, plus the thousands more who'll travel sometimes very long distances, will see a once-in-a-lifetime event: the disk of the moon completely and exactly blocking the disk of the sun. Assuming they have clear skies, of course. Nevertheless, those of us who are involved in the operation or management of electric power systems in north America may have good reason to be concerned. On 20 March 2015, a solar eclipse occurred in heavily populated europe. how did it affect the European power systems, and what can we learn from their experience?

Prognostic Reasoner based Adaptive Power Management System for a More Electric Aircraft

This research work presents a novel approach that addresses the concept of an adaptive power management system design and development framed in the Prognostics and Health Monitoring(PHM) perspective of an Electrical power Generation and distribution system(EPGS).PHM algorithms were developed to detect the health status of EPGS components which can accurately predict the failures and also able to calculate the Remaining Useful Life(RUL), and in many cases reconfigure for the identified system and subsystem faults. By introducing these approach on Electrical power Management system controller, we are gaining a few minutes lead time to failures with an accurate prediction horizon on critical systems and subsystems components that may introduce catastrophic secondary damages including loss of aircraft. The warning time on critical components and related system reconfiguration must permits safe return to landing as the minimum criteria and would enhance safety. A distributed architecture has been developed for the dynamic power management for electrical distribution system by which all the electrically supplied loads can be effectively controlled.A hybrid mathematical model based on the Direct-Quadrature (d-q) axis transformation of the generator have been formulated for studying various structural and parametric faults. The different failure modes were generated by injecting faults into the electrical power system using a fault injection mechanism. The data captured during these studies have been recorded to form a “Failure Database” for electrical system. A hardware in loop experimental study were carried out to validate the power management algorithm with FPGA-DSP controller. In order to meet the reliability requirements a Tri-redundant electrical power management system based on DSP and FPGA has been developed.

Electric power system planning with renewable energy accommodation for supporting the sustainable development of Tangshan City, China

In this study, considering break the original energy structure dominated by coal and make the most use of renewable energy in the future, an inexact stochastic robust mixed-integer programming (ITSRMP) method was developed for supporting regional electric power system management in Tangshan City, China. The developed method incorporated interval-parameter programming (IPP), stochastic robust optimization (SRO), two-stage stochastic programming (TSP), and mixed integer programming (MIP) within a general optimization framework to reflect uncertainties expressed as interval values and probability distributions in the regional electric power system. Three scenarios corresponding to different subsidy price levels and three cases associated with different pollutants emission reduction levels were designed. The electricity generation schemes, facility-expansion, pollutant emission, and system cost considering the subsidy policy and air pollution mitigation control had been obtained. The results indicated that subsidy policy would exert an important influence on the development of Tangshan's electric power system, which can reduce the cost advantage of conventional power generation and enhance the development enthusiasm of renewable power generation to power enterprises. In detail, the electricity generation amount of renewable energy would increase with the improvement of subsidy price level. Moreover, decision makers could identify the possible policy implementations and enforcements under considering the trade-off among system economy, security and environmental objectives. The modeling results were valuable for promoting new energy accommodation and supporting the sustainable development of social economy.

Study of power estimation and competitive electrical power management in LEV based on Gray model GM(1, n)

ABSTRACTIn this paper, a new electrical power management system is proposed for light electric vehicles (LEV). The main power sources are lithium battery and proton exchange membrane fuel cell (PEMFC). According to the gray theory, the gray model is used for power evaluation, which will help the competitive electrical power management system to make a good switching. Then, the powers of Li-battery and PEMFC can compare each other and share its power by switching way which can achieve the objective of power management more efficiently. The parameters of LEV are voltage, current and power. The performance of lithium battery and PEMFC should be tested before designing the LEV power management system. The result shows that the proposed competitive electrical power management system can provide power continuously until the fuel is burnt out, and good power management performance is demonstrated.

An Inexact Credibility Chance-Constrained Integer Programming for Greenhouse Gas Mitigation Management in Regional Electric Power System under Uncertainty

Electric power system (EPS) management considering greenhouse gas (GHG) mitigation is a challenging task, since many system parameters such as electric demand, resource availability, system cost as well as their interrelationships may appear uncertain. To reflect these uncertainties, in this study, an interval-parameter credibility constrained programming (ICCP) method was developed for electric power system planning in light of GHG mitigation. The method was advantageous in tackling uncertainties expressed as not only fuzzy possibilistic distributions associated with the right-hand-side components of model constraints but also discrete intervals in the objective function. In addition, ICCP allowed satisfaction of system constraints at specified confidence level, leading to model solutions with low system cost under acceptable risk magnitudes. The obtained results indicated that stable intervals for the objective function and decision variables could be generated, which were useful for helping decision makers identify the desired electric power generation patterns, capacity expansion schemes and GHG-emission reduction under complex uncertainties, and gain in-depth insights into the trade-offs between system economy and reliability.