Power System Stability
Ahmadreza Nafar; Gholam Reza Arab Markadeh; Amir Elahi; Reza pouraghababa
Volume 4, Issue 1 , June 2016, , Pages 16-28
Abstract
In the conventional structure of the wind turbines along with the doubly-fed induction generator (DFIG), the stator is directly connected to the power grid. Therefore, voltage changes in the grid result in severe transient conditions in the stator and rotor. In cases where the changes are severe, the ...
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In the conventional structure of the wind turbines along with the doubly-fed induction generator (DFIG), the stator is directly connected to the power grid. Therefore, voltage changes in the grid result in severe transient conditions in the stator and rotor. In cases where the changes are severe, the generator will be disconnected from the grid and consequently the grid stability will be attenuated. In this paper, a completely review of conventional methodes for DFIG control under fault conditions is done and then a series grid side converter (SGSC) with sliding mode control method is proposed to enhance the fault ride through capability and direct power control of machine. By applying this controlling strategy, the over current in the rotor and stator windings will totally be attenuated without using additional equipments like as crowbar resistance; Moreover, the DC link voltage oscillations will be attenuated to a great extent and the generator will continue operating without being disconnected from the grid. In addition, the proposed method is able to improve the direct power control of DFIG in harmonically grid voltage condition. To validate the performance of this method, the simulation results are presented under the symmetrical and asymmetrical faults and harmonically grid voltage conditions and compared with the other conventional methods.
Energy Management
A. Dolatabadi; R. Ebadi; B. Mohammadi-Ivatloo
Abstract
Ships play the major role in bulk transportation and they need their special energy system. This paper proposes a stochastic programing method for optimal sizing of a hybrid ship power system with energy storage system (ESS), photovoltaic power (PV) and diesel generator. To account for uncertainties, ...
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Ships play the major role in bulk transportation and they need their special energy system. This paper proposes a stochastic programing method for optimal sizing of a hybrid ship power system with energy storage system (ESS), photovoltaic power (PV) and diesel generator. To account for uncertainties, in this study a two-stage stochastic mixed-integer non-linear programing is used to model the optimal design problem of hybrid system for ships. The uncertainty of the hourly global solar irradiation and its effect on the output power of the PV system is taken into account. The probability density function of the global solar radiation follows a normal distribution. The Monte Carlo sampling approach is used to generate the scenarios with a specified probability and a proper scenario reduction method is used to decrease the computational burden of problem. Three cases are studied and the results are presented and compared.
F. Sedaghati; S. Ebrahimzadeh; H. Dolati; H. Shayeghi
Abstract
Switched capacitor multilevel inverters with low input DC voltage sources and voltage boost capability are very attractive to producing a high voltage levels in the output. The paper introduces a modified switched capacitor multilevel inverter with voltage boost capability. The suggested topology can ...
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Switched capacitor multilevel inverters with low input DC voltage sources and voltage boost capability are very attractive to producing a high voltage levels in the output. The paper introduces a modified switched capacitor multilevel inverter with voltage boost capability. The suggested topology can be extended into symmetric and asymmetric configurations. Nearest-level modulation method is employed to generate high-quality output waveforms. The presented multilevel inverter is compared with the similar configurations by considering various criteria. Finally, to confirm the operation of the suggested topology, a laboratory scale of the suggested inverter is implemented and the results are given.
Power System Operation
E. Babaei; N. Ghorbani
Volume 3, Issue 1 , June 2015, , Pages 23-33
Abstract
Reliability investigation has always been one of the most important issues in power systems planning. The outages rate in power system reflects the fact that more attentions should be paid on reliability indices to supply consumers with uninterrupted power. Using reliability indices in economic dispatch ...
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Reliability investigation has always been one of the most important issues in power systems planning. The outages rate in power system reflects the fact that more attentions should be paid on reliability indices to supply consumers with uninterrupted power. Using reliability indices in economic dispatch problem may lead to the system load demand with high reliability and low probability of power's outage rate. In this paper, the Economic Dispatch (ED) problem is optimized using the reliability indices. That is, ED problem and system reliability are proposed as Combined Economic Dispatch and Reliability (CEDR) problem. In CEDR problem, it is tried to utilize generating units in a way that we have high reliability in supplying the system load demand as well as the minimum fuel costs. Due to multi-objective and non-convex characteristics of this problem, Particle Swarm Optimization with Smart Inertia Factor (PSO-SIF) is used to solve the problem. In this research, the ED of power plants is successfully implemented in two systems with 6 and 26 generating units considering emission and system reliability.
R. Kazemzadeh; A. Hatefi
Volume 1, Issue 2 , November 2013, , Pages 84-95
Abstract
Economic dispatch with valve point effect and Prohibited Operating Zones (POZs) is a non-convex and discontinuous optimization problem. Harmony Search (HS) is one of the recently presented meta-heuristic algorithms for solving optimization problems, which has different variants. The performances of these ...
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Economic dispatch with valve point effect and Prohibited Operating Zones (POZs) is a non-convex and discontinuous optimization problem. Harmony Search (HS) is one of the recently presented meta-heuristic algorithms for solving optimization problems, which has different variants. The performances of these variants are severely affected by selection of different parameters of the algorithm. Intelligent Tuned Harmony Search (ITHS) is a recently developed variant, which mitigates the drawbacks of parameter initializing by maintaining a proper balance between diversification and intensification throughout the search process. The proposed method is applied to five different cases of power systems and the effectiveness, feasibility, and robustness of method is explored through the comparison with reported results in recent literature. First three case studies are systems with 3, 13, and 40-units, considering valve- point effect. The fourth and fifth cases are six and 15-generation unit taking into account generator constraints including POZs, ramp rate limit and transmission line losses which is a challenging Economic Dispatch (ED) problem due to restriction in search space. Computation results imply the efficiency of the proposed method toward other optimization methods reported in recent literature, judged in terms of the objective function value and solution robustness.
H. Bagheri Tolabi; M. H. Ali; M. Rizwan
Volume 2, Issue 2 , December 2014, , Pages 91-102
Abstract
This paper presents a new hybrid method for optimal multi-objective reconfiguration in a distribution feeder in addition to determining the optimal size and location of multiple-Distributed Generation (DG). The purposes of this research are mitigation of losses, improving the voltage profile and equalizing ...
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This paper presents a new hybrid method for optimal multi-objective reconfiguration in a distribution feeder in addition to determining the optimal size and location of multiple-Distributed Generation (DG). The purposes of this research are mitigation of losses, improving the voltage profile and equalizing the feeder load balancing in distribution systems. To reduce the search space, the improved analytical method has been employed to select the optimum candidate locations for multiple-DGs, and the intelligent water drops approach as a novel swarm intelligence based algorithm is used to simultaneously reconfigure and identify the optimal capacity for installation of DG units in the distribution network. In order to facilitate the algorithm for multi-objective search ability, the optimization problem is formulated for minimizing fuzzy performance indices. The proposed method is validated using the Tai-Power 11.4-kV distribution system as a real distribution network. The obtained results proved that this combined technique is more accurate and has the lowest fitness value as compared with other intelligent search algorithms. Also, the obtained results leadto the conclusion that multi-objective simultaneous placement of DGs along with reconfiguration can be more beneficial than separate single-objective optimization.
Distribution Systems
Soheil Derafshi Beigvand; Hamdi Abdi,
Volume 3, Issue 2 , December 2015, , Pages 102-115
Abstract
This paper proposes an Optimal Power Flow (OPF) algorithm by Direct Load Control (DLC) programs to optimize the operational cost of smart grids considering various scenarios based on different constraints. The cost function includes active power production cost of available power sources and a novel ...
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This paper proposes an Optimal Power Flow (OPF) algorithm by Direct Load Control (DLC) programs to optimize the operational cost of smart grids considering various scenarios based on different constraints. The cost function includes active power production cost of available power sources and a novel flexible load curtailment cost associated with DLC programs. The load curtailment cost is based on a virtual generator for each load (which participates in DLC program). To implement the load curtailment in the objective function, we consider incentive payments for participants and a load shedding priority list in some events. The proposed OPF methodology is applied to IEEE 14, 30-bus, and 13-node industrial power systems as three examples of the smart grids, respectively. The numerical results of the proposed algorithm are compared with the results obtained by applying MATPOWER to the nominal case by using the DLC programs. It is shown that the suggested approach converges to a better quality solution in an acceptable computation time.
Power System Operation
E. Heydarian-Forushani; H. Aalami
Volume 4, Issue 2 , December 2016, , Pages 104-116
Abstract
Increasing the penetration of variable wind generation in power systems has created some new challenges in the power system operation. In such a situation, the inclusion of flexible resources which have the potential of facilitating wind power integration is necessary. Demand response (DR) programs and ...
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Increasing the penetration of variable wind generation in power systems has created some new challenges in the power system operation. In such a situation, the inclusion of flexible resources which have the potential of facilitating wind power integration is necessary. Demand response (DR) programs and emerging utility-scale energy storages (ESs) are known as two powerful flexible tools that can improve large-scale integration of intermittent wind power from technical and economic aspects. Under this perspective, this paper proposes a multi objective stochastic framework that schedules conventional generation units, bulk ESs, and DR resources simultaneously with the application to wind integration. The proposed formulation is a sophisticated problem which coordinates supply-side and demand-side resources in energy and up/down spinning reserve markets so that the cost, emission, and multi objective functions are minimized separately. In order to determine the most efficient DR program which can potentially coordinate with bulk ESs in the system with a significant amount of wind power, a comprehensive DR programs portfolio including time- and incentive-based programs is designed. Afterwards, strategy success index (SSI) is employed to prioritize DR programs from independent system operator (ISO) perspective. The IEEE-RTS is used to reveal the effectiveness of the proposed method.
Z. Faramarzi; S. Abazari; S. Hoghoughi; N.R. Abjadi
Abstract
In this paper, Doubly Feed Induction Generator (DFIG) improves the dynamic stability of the power system in the presence of Static Synchronous Series Compensator (SSSC) using nonlinear control theory. The control method used in this study is based on the nonlinear multi-input adaptive backstepping control. ...
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In this paper, Doubly Feed Induction Generator (DFIG) improves the dynamic stability of the power system in the presence of Static Synchronous Series Compensator (SSSC) using nonlinear control theory. The control method used in this study is based on the nonlinear multi-input adaptive backstepping control. The control signals are assigned to DFIG and SSSC and synchronous generator excitation system. The applied control method is more effective than the conventional linear and nonlinear ones which are reported in the literature. Also in this study, control inputs are designed considering their appropriate constraints. The controller coefficients are optimally selected using intelligent algorithms that increase the performance of the controller in terms of achieving stability. The designed control is robust against parameter variations and load changes as well as changing in the location of the disturbances. This method is simulated in two aspects of the synchronous machine model as a third-order model and a second-order one. The methods are implemented on a 39-bus IEEE system and the simulation results show the effectiveness of the proposed control mechanism.
Distribution Systems
A. Bagheri; R. Noroozian; J. Gholinezhad
Abstract
In the most recent heuristic methods, the high potential buses for capacitor placement are initially identified and ranked using loss sensitivity factors (LSFs) or power loss index (PLI). These factors or indices help to reduce the search space of the optimization procedure, but they may not always indicate ...
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In the most recent heuristic methods, the high potential buses for capacitor placement are initially identified and ranked using loss sensitivity factors (LSFs) or power loss index (PLI). These factors or indices help to reduce the search space of the optimization procedure, but they may not always indicate the appropriate placement of capacitors. This paper proposes an efficient approach for the optimal capacitor placement in radial distribution networks with the aim of annual costs minimization based on the sequential placement of capacitors and calculation of power loss index. In the proposed approach, initially, the number of capacitors location is estimated using the total reactive power demand and the average range of capacitors available in the market. Then, the high potential buses can be identified using sequential power loss index-based method. This method leads to achieve the optimal or near optimal locations for the capacitors and decrease the search space of the optimization procedure significantly. The particle Swarm Optimization (PSO) algorithm takes the final decision for the optimum size and location of capacitors. To evaluate the efficiency of the conducted approach, it is tested on several well-known distribution networks, and the results are compared with those of existing methods in the literature. The comparisons verify the effectiveness of the proposed method in producing fast and optimal solutions.
Distribution Systems
M.A. Tavakoli Ghazi Jahani; P. Nazarian; A. Safari; M.R. Haghifam
Abstract
Network reconfiguration is a nonlinear optimization procedure which calculates a radial structure to optimize the power losses and improve the network reliability index while meeting practical constraints. In this paper, a multi-objective framework is proposed for optimal network reconfiguration with ...
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Network reconfiguration is a nonlinear optimization procedure which calculates a radial structure to optimize the power losses and improve the network reliability index while meeting practical constraints. In this paper, a multi-objective framework is proposed for optimal network reconfiguration with the objective functions of minimization of power losses and improvement of reliability index. The optimization problem is solved by multi-objective grasshopper optimization algorithm (MOGOA) which is one of the most modern heuristic optimization tools. To solve an optimization problem, the suggested algorithm mathematically mimics and formulates the behavior of grasshopper swarms. The modifying comfort zone coefficient needs grasshoppers to balance exploration and exploitation, which helps the MOGOA to find an exact approximation of global optimization and not trapped in local optima. The efficiency of the suggested technique is approved regarding the 33-bus and 69-bus test systems. Optimization results expressed that the suggested technique not only presents the intensified exploration ability but also has a better solution compared with previous algorithms.
Smart Grid
H. Rashidizadeh-Kermani; H. R. Najafi; A. Anvari-Moghaddam; J. M. Guerrero
Abstract
Electric vehicle (EV) aggregator, as an agent between the electricity market and EV owners, participates in the future and pool market to supply EVs’ requirement. Because of the uncertain nature of pool prices and EVs’ behaviour, this paper proposed a two-stage scenario-based model to obtain ...
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Electric vehicle (EV) aggregator, as an agent between the electricity market and EV owners, participates in the future and pool market to supply EVs’ requirement. Because of the uncertain nature of pool prices and EVs’ behaviour, this paper proposed a two-stage scenario-based model to obtain optimal decision making of an EV aggregator. To deal with mentioned uncertainties, the aggregator’s risk aversion is applied using conditional value at risk (CVaR) method in the proposed model. The proposed two-stage risk-constrained decision-making problem is applied to maximize EV aggregator’s expected profit in an uncertain environment. The aggregator can participate in the future and pool market to buy the required energy of EVs and offer optimal charge/discharge prices to the EV owners. In this model, in order to assess the effects of EVs owners’ reaction to the aggregator’s offered prices on the purchases from electricity markets, a sensitivity analysis over risk factor is performed. The numerical results demonstrate that with the application of the proposed model, the aggregator can supply EVs with lower purchases from markets.
Power System Operation
M. R. Behnamfar; H. Barati; M. Karami
Abstract
This study addresses a stochastic structure for generation companies (GenCoʼs) that participate in hydro-thermal self-scheduling with a wind power plant on short-term scheduling for simultaneous reserve energy and energy market. In stochastic scheduling of HTSS with a wind power plant, in addition to ...
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This study addresses a stochastic structure for generation companies (GenCoʼs) that participate in hydro-thermal self-scheduling with a wind power plant on short-term scheduling for simultaneous reserve energy and energy market. In stochastic scheduling of HTSS with a wind power plant, in addition to various types of uncertainties such as energy price, spinning /non-spinning reserve prices, uncertainties of RESs, such as output power of the wind power plant are also taken into account. In the proposed framework, mixed-integer non-linear programming of the HTSS problem is converted into a MIP. Since the objective of the study is to show how GenCosʼ aim to achieve maximum profit, mixed-integer programming is used here. Therefore, to formulate the MIP for the problem of HTSS with a wind power plant in the real-time modeling, some parameters like the impact of valve loading cost (VLC) that are accompanied by linear modeling, are considered. Furthermore, in thermal units, parameters such as prohibited operating zones (POZs) and different uncertainties like the energy price and wind power are included to formulate the problem more suitably. The point that is worth noting is the use of dynamic ramp rate (DRR). Also, the application of multi-functional curves (L) of hydro plants is considered when studying inter-unit scheduling. Finally, the required tests are conducted on a modified IEEE 118-bus system to verify the accuracy and methodology of the proposed method.
M. Khadem Maaref; J. Salehi
Abstract
Microgrids are known as the main components of energy networks because they can accommodate a large share of renewable energy sources. Peer-to-peer energy trading is one of the most effective ways to implement decentralized patterns in the electricity market. In peer-to-peer trades, each actor negotiates ...
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Microgrids are known as the main components of energy networks because they can accommodate a large share of renewable energy sources. Peer-to-peer energy trading is one of the most effective ways to implement decentralized patterns in the electricity market. In peer-to-peer trades, each actor negotiates directly with a set of partners without any intermediaries. Peer-to-peer energy exchange methods allow direct energy exchange between producers and consumers. This study tested the peer-to-peer trading method on networks consisting of 4 microgrids. Existing microgrids have different generating sources, such as solar energy, wind turbines, and microturbines, each of which is modeled separately. Moreover, in order to reduce the uncertainty in the production of renewable sources, a battery storage system has been used in this network. Also, to encourage microgrids to use renewable resources, cut-off costs have been considered by these resources. This research uses the constrained optimization method and GAMS software with a Baron solver to optimize the problem. In the end, the uncertainty of producing renewable resources for different modes is examined using the information gap decision theory method. The available results show the power distribution between microgrids and other network components based on the objective function and existing constraints.
M.R. Behnamfar; M. Abasi
Abstract
The present study focuses on the harris hawks optimizer. harris hawks optimization (HHO) is introduced based on population and nature patterns. The HHO algorithm imitates harris hawks attacking behavior and includes two phases called exploration and exploitation, which can be modeled with three ...
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The present study focuses on the harris hawks optimizer. harris hawks optimization (HHO) is introduced based on population and nature patterns. The HHO algorithm imitates harris hawks attacking behavior and includes two phases called exploration and exploitation, which can be modeled with three strategies, 1) discovering the prey, 2) surprising attack, and 3) prey attack. The main purpose of using this type of algorithm is to optimally solve the short-term hydro-thermal self-scheduling (STHTSS) problem with wind power(WP), photovoltaic (PV), small hydro (SH) and pumped hydro storage (PHS) powr plants while considering uncertainties such as energy prices, ancillary services prices, etc, in the energy market. It will be shown how energy generation companies can use this algorithm and other algorithms and innovative methods that will be introduced in the future to achieve profit maximum with careful scheduling. It is worth mentioning that in this study, the effect of the presence and absence of two important factors, namely valve load cost (VLC) effect and prohibited operating zones (POZs) (with linear modeling) that can affect the profit of units (power plants) has been pointed out. Finally, as shown in this study, several tests perfomed on the IEEE118-bus system validate the precision and credibility of the harris hawks optimization algorithm.
Power market
N. Mostaghim; M. R. Haghifam; M. Simab
Abstract
Improving performance of electrical distribution companies, as the natural monopoly entities in electric industry, has always been one of the main concerns of the regulators. In this paper, a new incentive regulatory scheme is proposed to improve the performances of electrical distribution companies. ...
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Improving performance of electrical distribution companies, as the natural monopoly entities in electric industry, has always been one of the main concerns of the regulators. In this paper, a new incentive regulatory scheme is proposed to improve the performances of electrical distribution companies. The proposed scheme utilizes several efficiency assessments and a 3-dimentional reward-penalty scheme (3DRPS). Through efficiency assessments, economic efficiency and service quality, as two aspects of companies’ performances, are assessed and according to the results of such assessments, reasonable capital expenditure (CAPEX) and operational expenditure (OPEX) for each company are calculated. Then, according to the reasonable CAPEX and OPEX, allowed revenues are calculated for next regulatory period. Moreover, the 3DRPS on quality is used to encourage the companies to maintain and improve their service quality during the regulatory period. The 3DRPS gives the incentive to the companies based on changes in their quality indices. The incentives are added to companies’ allowed revenues. Finally, the proposed scheme is applied to Iranian distribution companies and the results are discussed.
Behnam Mohammadi-Ivatloo; A. Mokari; H. Seyedi; S. Ghasemzadeh
Volume 2, Issue 1 , June 2007, , Pages 22-31
Abstract
When a distribution network consisting of Distributed Generations (DGs) is disconnected from upstream network, the system may be exposed to severe power imbalance. In order to prevent the damage of power plants, frequency relays operate and remove DGs from the network. In contrast to traditional methods, ...
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When a distribution network consisting of Distributed Generations (DGs) is disconnected from upstream network, the system may be exposed to severe power imbalance. In order to prevent the damage of power plants, frequency relays operate and remove DGs from the network. In contrast to traditional methods, the main objective in new methods is to keep DG units in service in the islanded distribution system. Under-Frequency Load Shedding (UFLS) is one of the most important protection systems, which is the last chance for avoiding a system blackout following severe disturbance. This paper dealt with an adaptive UFLS method and considered the priority of loads to be shed, depending on the intensity of event, and loads look up table built by Rate of Change of Frequency of Loads (ROCOFL) indices based on the frequency of centre of inertia (fCOI). Different loads were shed depending on the event type diagnosed by measuring the initial Rate of Change of Frequency (ROCOF) in the method. The proposed UFLS method can stabilize the frequency of the distribution system in islanding mode by shedding sufficient loads. The simulation results confirmed the advantages of the methods in comparison to other proposed algorithms.
N. Bigdeli; E. Ghanbaryan; K. Afshar
Volume 1, Issue 1 , June 2013, , Pages 22-32
Abstract
In this paper, the Unified Power Flow Controller (UPFC) is enhanced with a Chaotic Particle Swarm Optimization (CPSO) Damping Controller in order to mitigate the Low Frequency Oscillations (LFO) in a Single Machine Infinite Bus (SMIB) power system. The designed damping controller is an optimized lead-lag ...
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In this paper, the Unified Power Flow Controller (UPFC) is enhanced with a Chaotic Particle Swarm Optimization (CPSO) Damping Controller in order to mitigate the Low Frequency Oscillations (LFO) in a Single Machine Infinite Bus (SMIB) power system. The designed damping controller is an optimized lead-lag controller, which extracts the speed deviation of the generator rotor and generates the output feedback signal, which aims to modulate the reference values of the UPFC normal controller to achieve the best damping of LFO. In order to examine the better damping option, the damping controller is applied to both series and shunt converter of the UPFC and the results are comprehensively compared in three different operating points. Simulation results are performed in MATLAB/Simulink in three different cases and a Performance Index (PI) analysis is carried out.
Energy Management
H. Moayedirad; M. A. Shamsi Nejad
Abstract
A dual stator winding squirrel-cage induction motor (DSWIM) is a brushless single-frame induction motor that contains a stator with two isolated three-phase windings wound with dissimilar numbers of poles. Each stator winding is fed by an independent three-phase inverter. The appropriate efficiency of ...
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A dual stator winding squirrel-cage induction motor (DSWIM) is a brushless single-frame induction motor that contains a stator with two isolated three-phase windings wound with dissimilar numbers of poles. Each stator winding is fed by an independent three-phase inverter. The appropriate efficiency of this motor is obtained when the ratio of two frequencies feeding the machine is equal to the ratio of the number of poles. In the vector control method at low speeds, flux is difficult to estimate because the voltage drop on the stator resistance is comparable with the input stator voltage, disturbing the performance of the motor drive. To solve the abovementioned problem, researchers have benefited from the free capacity of the two windings of the stator. This makes the motor deviate from its standard operating mode at low speeds. The main purpose of this paper is reducing the power losses of the inverter unit in the DSWIM drive at low speeds via the proposed control method and a five-leg inverter. This paper deals with two topics: 1. Using the idea of rotor flux compensation at low speeds, the motor works in its standard operating mode. Therefore, the power losses of the utilized power electronic converters are also reduced to a considerable extent; and 2. Reduction in capital cost can be achieved by utilizing a five-leg power electronic converter. The proposed methods are simulated in MATLAB/Simulink software, and the results of simulation confirm the assumptions.
N. R. Abjadi
Abstract
Due to the development of renewable energy and the need for sustainable electricity, AC microgrids (MGs) have received a lot of attention and the growing need for them is becoming more and more apparent. Medium voltage MGs will be very important in providing electrical energy in the near future. This ...
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Due to the development of renewable energy and the need for sustainable electricity, AC microgrids (MGs) have received a lot of attention and the growing need for them is becoming more and more apparent. Medium voltage MGs will be very important in providing electrical energy in the near future. This paper represents a robust and effective control method with rather simple implementation capability for islanded MGs based on master-slave (MS) technique. The designed control is a type of terminal sliding mode control, which has a high response speed and good convergence with robustness against some uncertainties. Stability and high performance are very essential for islanded MGs. The designed control meets these requirements so that the output voltage of the inverter based distributed generation (DG) sources includes a very low amount of harmonics and the generated active and reactive powers track their reference values perfectly. The effectiveness of the proposed control method is evaluated by simulation in SIMULINK/MATLAB environment. The simulation results are presented considering five cases, which include feedback linearization control (FLC) and conventional sliding mode control (CSMC) of DGs, harmonic load and high impedance transmission lines simulation results. The obtained results show the perfect tracking and robustness of the proposed control scheme considering uncertainties in parameters and it is illustrated that a high accuracy power sharing between DG sources is achieved.
Power System Operation
R. Kazemzadeh; M. Moazen
Abstract
Many different methods have been presented to solve unit commitment (UC) problem in literature with different advantages and disadvantages. The need for multiple runs, huge computational burden and time, and poor convergence are some of the disadvantages, where are especially considerable in large scale ...
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Many different methods have been presented to solve unit commitment (UC) problem in literature with different advantages and disadvantages. The need for multiple runs, huge computational burden and time, and poor convergence are some of the disadvantages, where are especially considerable in large scale systems. In this paper, a new analytical and non-iterative method is presented to solve UC problem. In the proposed method, improved pre-prepared power demand (IPPD) table is used to solve UC problem, and then analytical “λ-logic” algorithm is used to solve economic dispatch (ED) sub-problem. The analytical and non-iterative nature of the mentioned methods results in simplification of the UC problem solution. Obtaining minimum cost in very small time with only one run is the major advantage of the proposed method. The proposed method has been tested on 10 unit and 40-100 unit systems with consideration of different constraints, such as: power generation limit of units, reserve constraints, minimum up and down times of generating units. Comparing the simulation results of the proposed method with other methods in literature shows that in large scale systems, the proposed method achieves minimum operational cost within minimum computational time.
M.R. Negahdari; A. Ghaedi; M. Nafar; M. Simab
Abstract
For providing required load in n coastal and island regions, tidal barrage can be integrated in microgrids. To produce electricity from tides, in tidal barrage, water is moved between sea and reservoir through sluices containing turbines to generate electricity. In operation phase, produced power of ...
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For providing required load in n coastal and island regions, tidal barrage can be integrated in microgrids. To produce electricity from tides, in tidal barrage, water is moved between sea and reservoir through sluices containing turbines to generate electricity. In operation phase, produced power of tidal barrages depends on number of turbines, sluices and hydro-pumps. Thus, to maximize generated energy of tidal barrage, optimum number of turbines, sluices and hydro-pumps can be obtained through heuristic optimization techniques. Because of tidal level variation, generated power of tidal barrages changes over time. Thus, for load supplying, other renewable resources such as photovoltaic units, batteries, fuel-based generation units and grid-connected mode of microgrid are utilized. In this research, two-stage optimal operation of microgrids composed of tidal barrage, photovoltaic units, batteries and fuel-based generation units is done. In first stage, optimum number of turbines, sluices and hydro-pumps related to tidal barrage is determined for maximizing produced energy of tidal unit during time horizon of the study. In second stage, remaining load of microgrid is provided by photovoltaic units, batteries, fuel-based generation units and main network. To this end, generated power of fuel-based plants and power exchanged between microgrid and main grid are determined for minimizing operating cost of microgrid. The operating cost including operating cost of fuel-based generation units, cost of exchanged power between main grid and microgrid and penalties of load curtailment is optimized using particle swarm optimization method. Numerical results presents among different optimization algorithms, particle swarm method has performed best in operation studies of tidal barrage. For understudied microgrid, maximum generated energy of tidal barrage is 25.052 MWh, and minimum operating cost of the microgrid is 39868 $.
Power System Operation
Ehsan Dehnavi; Hamdi Abdi,; Farid Mohammadi
Volume 4, Issue 1 , June 2016, , Pages 29-41
Abstract
Nowadays, demand response programs (DRPs) play an important role in price reduction and reliability improvement. In this paper, an optimal integrated model for the emergency demand response program (EDRP) and dynamic economic emission dispatch (DEED) problem has been developed. Customer’s behavior ...
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Nowadays, demand response programs (DRPs) play an important role in price reduction and reliability improvement. In this paper, an optimal integrated model for the emergency demand response program (EDRP) and dynamic economic emission dispatch (DEED) problem has been developed. Customer’s behavior is modeled based on the price elasticity matrix (PEM) by which the level of DRP is determined for a given type of customer. Valve-point loading effect, prohibited operating zones (POZs), and the other non-linear constraints make the DEED problem into a non-convex and non-smooth multi-objective optimization problem. In the proposed model, the fuel cost and emission are minimized and the optimal incentive is determined simultaneously. The imperialist competitive algorithm (ICA) has solved the combined problem. The proposed model is applied on a ten units test system and results indicate the practical benefits of the proposed model. Finally, depending on different policies, DRPs are prioritized by using strategy success indices.
Power System Operation
A. Badri; K. Hoseinpour Lonbar
Volume 3, Issue 1 , June 2015, , Pages 34-46
Abstract
This paper proposes a novel decision making framework for an electricity retailer to procure its electric demand in a bilateral-pool market in presence of charging and discharging of electric vehicles (EVs). The operational framework is a two-stage programming model in which at the first stage, the retailer ...
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This paper proposes a novel decision making framework for an electricity retailer to procure its electric demand in a bilateral-pool market in presence of charging and discharging of electric vehicles (EVs). The operational framework is a two-stage programming model in which at the first stage, the retailer and EV aggregator do their medium-term planning. Determination of retailer's optimum selling price and the amount of energy that should be purchased from bilateral contracts are medium-term decisions that are made one month prior to real-time market. At the second stage, market agents deal with their activities in the short-term period. In this stage the retailer may modify its preliminary strategy by means of pool market option, interruptible loads (ILs), self-scheduling and EVs charging and discharging (V2G). Thus, a bi-level programming is introduced in which the upper sub-problem maximizes retailer profit, whereas the lower sub-problem minimizes the aggregated EVs charging and discharging costs. Final decision making is obtained in this stage that may be considered as a day-ahead market, keeping in mind the medium-term decisions. Due to the volatility of pool price and uncertainties associated with the consumers and EVs demand, the proposed framework is a mixed integer nonlinear stochastic optimization problem; therefore, Monte Carlo Simulation (MCS) is applied to solve it. Furthermore, a market quota curve is utilized to model the uncertainty of the rivals and obtaining retailer's actual market share. Finally, a case study is presented in order to show the capability and accuracy of the proposed framework.
K. Afshar; A. Shokri Gazafroudi
Volume 1, Issue 2 , November 2013, , Pages 96-109
Abstract
Wind power generation is variable and uncertain. In the power systems with high penetration of wind power, determination of equivalent operating reserve is the main concern of systems operator. In this paper, a model is proposed to determine operating reserves in simultaneous market clearing of energy ...
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Wind power generation is variable and uncertain. In the power systems with high penetration of wind power, determination of equivalent operating reserve is the main concern of systems operator. In this paper, a model is proposed to determine operating reserves in simultaneous market clearing of energy and reserve by stochastic programming based on scenarios generated via Monte Carlo simulation (MCS). This model considers the wind power, load and network uncertainties and includes the cost of involuntary load shedding and wind spillage. The proposed methodology is examined on an example and a case study to investigate various effects of wind power generation on the system operating reserves and costs.
