Iranian Journal of Electrical and Electronic Engineering

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Electric power restructuring offers a major change to the vertically integrated monopoly. The change manifests the main part of engineers’ efforts to reshape the three components of today’s vertically integrated monopoly: generation, distribution and transmission. In a restructured environment, the main tasks of these three components will remain the same as before, however, to comply with FERC orders, new types of unbundling, coordination and rules are to be established to guarantee competition and non-discriminatory open access to all users. This paper provides the generation schedule of a GENCO in a deregulated power system. It is shown that the goal of generation schedule in the new structure is different from the traditional centralized power systems. The modeling of generation scheduling problem in a competitive environment is demonstrated by taking into account the main purposes of GENCOs which are selling electricity as much as possible and making higher profit. The GENCOs of an area are introduced via a model whose objective function consists of hourly spot market price as income and different kinds of costs. The constraints are the general ones of such a problem e.g. minimum up/down time, minimum and maximum generation and ramp rate. Using one of the classical optimization methods, the hourly generation schedule of the generating units will be obtained in this competitive environment. The results of this section will be used by ISO. The ISO will finalize the schedules of GENCOs by taking into account the technical considerations like the power flow of transmission lines. The model and the optimization methods are implemented on IEEE-RTS benchmark with 24 buses and 32 generating units.

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Medium-term modeling of electricity market has essential role in generation expansion planning. On the other hand, uncertainties strongly affect modeling and consequently, strategic analysis of generation firms in the medium term. Therefore, models considering these uncertainties are highly required. Among uncertain variables considered in the medium term generation planning, demand and hydro inflows are of the greatest importance. This paper proposes a new approach for simulating the operation of power market in medium-term, taking into account demand and hydro inflows uncertainties. The demand uncertainty is considered using Monte-Carlo simulations. Standard Deviation over Expected Profit (SDEP) of generation firms based on simulation results is introduced as a new index for analyzing the influence of the demand uncertainty on the behavior of market players. The correlation between capacity share of market players and their SDEP is also demonstrated. The uncertainty of inflow as a stochastic variable is dealt using scenario tree representation. Rational uncertainties as strategic behavior of generation firms, intending to maximize their expected profit, is considered and Nash-Equilibrium is determined using the Cournot model game. Market power mitigation effects through financial bilateral contracts as well as demand elasticity are also investigated. Case studies confirm that this representation of electricity market provides robust decisions and precise information about electricity market for market players which can be used in the generation expansion planning framework.

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The operation of Fuel Cell Distributed Generation (FCDG) systems in distribution systems is introduced by modeling, controller design, and simulation study of a Solid Oxide Fuel Cell (SOFC) distributed generation (DG) system. The physical model of the fuel cell stack and dynamic models of power conditioning units are described. Then, suitable control architecture based on fuzzy logic control for the overall system is presented in order to active power control and power quality improvement. A MATLAB/Simulink simulation model is developed for the SOFC DG system by combining the individual component models and the controllers designed for the power conditioning units. Simulation results are given to show the overall system performance including active power control and voltage regulation capability of the distribution system.

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This paper describes a DC isolated network which is fed with Distributed Generation (DG) from photovoltaic (PV) renewable sources for supplying unbalanced AC loads. The battery energy storage bank has been connected to the DC network via DC/DC converter to control the voltage of the network and optimize the operation of the PV generation units. The PV arrays are connected to the DC network via its own DC/DC converter to ensure the required power flow. The unbalanced AC loads are connected to the DC network via its own DC/AC converter. This paper proposes a novel control strategy for storage converter which has a DC voltage droop regulator. Also a novel control system based on Park rotating frame has been proposed for DC/AC converters. In this paper, the proposed operation method is demonstrated by simulation of power transfer between PV arrays, unbalanced AC loads and battery unit. The simulation results based on PSCAD/EMTDC software show that DC isolated distribution system including PV generation systems can provide the high power quality to supplying unbalanced AC loads.

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This paper proposes a novel approach for generation scheduling using sensitivity

characteristic of a Security Analyzer Neural Network (SANN) for improving static security

of power system. In this paper, the potential overloading at the post contingency steadystate

associated with each line outage is proposed as a security index which is used for

evaluation and enhancement of system static security. A multilayer feed forward neural

network is trained as SANN for both evaluation and enhancement of system security. The

input of SANN is load/generation pattern. By using sensitivity characteristic of SANN,

sensitivity of security indices with respect to generation pattern is used as a guide line for

generation rescheduling aimed to enhance security. Economic characteristic of generation

pattern is also considered in the process of rescheduling to find an optimum generation

pattern satisfying both security and economic aspects of power system. One interesting

feature of the proposed approach is its ability for flexible handling of system security into

generation rescheduling and compromising with the economic feature with any degree of

coordination. By using SANN, several generation patterns with different level of security

and cost could be evaluated which constitute the Pareto solution of the multi-objective

problem. A compromised generation pattern could be found from Pareto solution with any

degree of coordination between security and cost. The effectiveness of the proposed

approach is studied on the IEEE 30 bus system with promising results.

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This paper presents the modeling and simulation of a proton exchange membrane fuel cell (PEMFC) generation system for off-grid and on-grid operation and configuration. A fuel cell DG system consists of a fuel cell power plant, a DC/DC converter and a DC/AC inverter. The dynamic model for fuel cell array and its power electronic interfacing are presented also a multi-input single output (MISO) DC/DC converter and its control scheme is proposed and analyzed. This DC/DC converter is capable of interfacing fuel cell arrays to the DC/AC inverter. Also the mathematical model of the inverter is obtained by using average technique. Then the novel control strategy of DC/AC inverter for different operating conditions is demonstrated. The simulation results show the effectiveness of the suggested control systems under both on-grid and off-grid operation modes.

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The recent trends in electrical power distribution system operation and management are aimed at improving system conditions in order to render good service to the customer. The reforms in distribution sector have given major scope for employment of distributed generation (DG) resources which will boost the system performance. This paper proposes a heuristic technique for allocation of distribution generation source in a distribution system. The allocation is determined based on overall improvement in network performance parameters like reduction in system losses, improvement in voltage stability, improvement in voltage profile. The proposed Network Performance Enhancement Index (NPEI) along with the heuristic rules facilitate determination of feasible location and corresponding capacity of DG source. The developed approach is tested with different test systems to ascertain its effectiveness.

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Islanded operation of distributed generators is a problem that can take place when they are connected to a distribution system. In this paper an islanding detection method is presented for inverter based distributed generation (DG) using under/over voltage relay. The method is an adaptive one and is based on the change of DG active power reference (Pref) in inverter control interface. The active power reference has a fixed value in normal condition, whereas, if the point of common coupling (PCC) voltage changes, Pref has determined as a linear function of voltage. The slope of Pref is dependent to the load active power (Pload) and should be changed if Pload changes. The non-detection zone (NDZ) of the proposed method is dependent on the accuracy of the voltage measurement equipment if changing of the PCC voltage is sensed, then, islanding will be detected if it is occurred. Also it does not have any negative effects on the distribution system in normal conditions. Moreover, the proposed technique can be applied when two-DG is in the island. The proposed method is evaluated according to the requirements of the IEEE 1547 and UL 1741 standards, using PSCAD/EMTDC software.

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Identification of intentional and unintentional islanding situations of dispersed generators (DGs) is one of the most important protection concerns in power systems. Considering safety and reliability problems of distribution networks, an exact diagnosis index is required to discriminate the loss of the main network from the existing parallel operation. Hence, this paper introduces a new islanding detection method for synchronous machine–based DGs. This method uses the average value of the generator frequency to calculate a new detection index. The proposed method is an effective supplement of the over/under frequency protection (OFP/UFP) system. The analytical equations and simulation results are used to assess the performance of the proposed method under various scenarios such as different types of faults, load changes and capacitor bank switching. To show the effectiveness of the proposed method, it is compared with the performance of both ROCOF and ROCOFOP methods.

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Microgrid (MG) is one of the important blocks in the future smart distribution systems. The scheduling pattern of MGs affects distribution system operation. Also, the optimal scheduling of MGs will be result in reliable and economical operation of distribution system. In this paper, an operational planning model of a MG which considers multiple demand response (DR) programs is proposed. In the proposed approach, all types of loads can participate in demand response programs which will be considered in either energy or reserve scheduling. Also, the renewable distributed generation uncertainty is covered by reserve prepared by both DGs and loads. The novelty of this paper is the demand side participation in energy and reserve scheduling, simultaneously. Furthermore the energy and reserve scheduling is proposed for day-ahead and real-time. The proposed model was tested on a typical MG system in connected mode and the results show that running demand response programs will reduce total operation cost of MG and cause more efficient use of resources.

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This paper proposes an autonomous and economic droop control scheme for DC microgrid application. In this method, a cost-effective power sharing technique among various types of DG units is properly adopted. The droop settings are determined based on an algorithm to individually manage the power management without any complicated optimization methods commonly applied in the centralized control method. In the proposed scheme, the system retains all the advantages of the traditional droop method while minimizes the generation costs of the DC microgrid. In the proposed method, all DGs are classified in a sorting rule based on their total generation cost and the reference voltage of their droop equations is then determined. The proposed scheme is applied to a typical DC microgrid consisting of four different types of DGs and a controllable load. The simulation results are presented to verify the effectiveness of the proposed method using MATLAB/SIMULINK software.

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Development of distributed generations’ technology, trends in the use of these sources to improve some of the problems such as high losses, low reliability, low power quality and high costs in distributed networks. Choose the correct location to install and proper capacity of these sources, such as important things that must be considered in their use. Since distribution networks are actually unbalanced and asymmetric consumption loads are different, so in this paper with optimal placement and sizing of distributed generation sources that dependent on the load model and type of load connection and the uncertainties which caused by the generated power of wind turbines and solar panels, the positive effects of these sources have been examined on unbalanced distribution network. Hence with linear three-phase unbalanced load flow method and IPSO algorithm, allocation of distributed generation sources in IEEE standard of 37 bus unbalanced network have been done. Obtained results show improvement of voltage profile in each phase and reduction of network power losses and buses’ voltage unbalance factor. 

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By increasing the use of distributed generation (DG) in the distribution network operation, an entity called virtual power plant (VPP) has been introduced to control, dispatch and aggregate the generation of DGs, enabling them to participate either in the electricity market or the distribution network operation. The participation of VPPs in the electricity market has made challenges to fairly allocate payments and benefits between VPPs and distribution network operator (DNO). This paper presents a bilevel scheduling approach to model the energy transaction between VPPs and DNO.  The upper level corresponds to the decision making of VPPs which bid their long- term contract prices so that their own profits are maximized and the lower level represents the DNO decision making to supply electricity demand of the network by minimizing its overall cost. The proposed bilevel scheduling approach is transformed to a single level optimizing problem using its Karush-Kuhn-Tucker (KKT) optimality conditions. Several scenarios are applied to scrutinize the effectiveness and usefulness of the proposed model. 

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The increasing concern of global climate changes, the promotion of renewable energy sources, primarily wind generation, is a welcome move to reduce the pollutant emissions from conventional power plants. Integration of wind power generation with the existing power network is an emerging research field. This paper presents a meta-heuristic algorithm based approach to determine the feasible dispatch solution for wind integrated thermal power system. The Unit Commitment (UC) process aims to identify the best feasible generation scheme of the committed units such that the overall generation cost is reduced, when subjected to a variety of constraints at each time interval. As the UC formulation involves many variables and system and operational constraints, identifying the best solution is still a research task. Nowadays, it is inevitable to include power system reliability issues in operation strategy. The generator failure and malfunction are the prime influencing factor for reliability issues hence they have considered in UC formulation of wind integrated thermal power system. The modern evolutionary algorithm known as Grey Wolf Optimization (GWO) algorithm is applied to solve the intended UC problem. The potential of the GWO algorithm is validated by the standard test systems. Besides, the ramp rate limits are also incorporated in the UC formulation. The simulation results reveal that the GWO algorithm has the capability of obtaining economical resolutions with good solution quality.

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Distribution systems can be operated in multiple configurations since they are possible combinations of radial and loop feeders. Each configuration leads to its own power losses and reliability level of supplying electric energy to customers. In order to obtain the optimal configuration of power networks, their reconfiguration is formulated as a complex optimization problem with different objective functions and network operating constraints. In this paper, a multi-objective framework is proposed for optimal network reconfiguration with objective functions of minimization of power losses, System Average Interruption Frequency Index (SAIFI), System Average Interruption Duration Index (SAIDI), Average Energy Not Supplied (AENS), and Average Service Unavailability Index (ASUI). The optimization problem is solved by the Imperialist Competitive Algorithm (ICA) as one of the most modern heuristic tools. Since objective functions have different scales, a fuzzy membership is utilized here to transform objective functions into a same scale and then to determine the satisfaction level of the afforded solution using the fuzzy fitness. The efficiency of the proposed method is confirmed by testing it on 32-bus and 69-bus distribution test systems. Simulation results demonstrate that the proposed method not only presents intensified exploration ability but also has a better converge rate compared with previous methods.
 

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