The transmission usage cost allocation is one of the major issues experienced by the Electric Supply Industries. In this paper, authors have considered Line Outage Distribution Factor (LODF) for allocating the transmission usage cost allocation under contingency condition. Authors have modified the
distribution factor for maximum flow and propose a novel Maximum Line Outage Distribution Factor (MLODF) which depends upon the redistribution of the generation in the line flow considering N-1 security constraints. Similarly, for transmission loss cost allocation under contingency condition Maximum Line Outage Loss Distribution Factor (MLOLDF) is developed. Full recovery policy of transmission cost allocation is considered. The reliability and accuracy of the proposed method is tested
on the sample 6 bus system.
techTransmission usage and cost allocation using shapley value and tracing me...elelijjournal
In the deregulated power system, transmission pricing has become a very important task because it is necessary to develop an efficient, feasible and reliable pricing scheme that can generate the useful economic signals to network users such as generating companies, transmission companies, distribution companies and customers. The objective of this paper is to compare transmission usage and cost allocation scheme to loads (and/or generators) based on Shapley value method and power flow tracing method.Modified Kirchhoff matrix is used for power flow tracing. A comparison is done between the both methods.
A case study based on sample 6 bus power system is applied to check the feasibility and reliability of the proposed usage and cost allocation methodology.
A MULTIPURPOSE MATRICES METHODOLOGY FOR TRANSMISSION USAGE, LOSS AND RELIABIL...ecij
In the era of power system restructuring there is a need of simplified method which provides a complete allocation of usage, transmission losses and transmission reliability margin. In this paper, authors presents a combined multipurpose matrices methodology for Transmission usage, transmission loss and transmission reliability margin allocation. Proposed methodology is simple and easy to implement on large power system. A modified Kirchhoff matrix is used for allocation purpose. A sample 6 bus system is used to demonstrate the feasibility of proposed methodology.
Allocation of Transmission Cost Using Power Flow Tracing MethodsIJERA Editor
In the open access restructured power system market, it is necessary to develop an appropriate pricing scheme that can provide the useful economic information to market participants, such as generation, transmission companies and customers. Though many methods have already been proposed, but accurately estimating and allocating the transmission cost in the transmission pricing scheme is still a challenging task. This work addresses the problem of allocating the cost of the transmission network to generators and demands. In this work four methods using DC Power flow and AC power flow have been attempted. They are MW-Mile Method, MVA-Mile Method, GGDF method and Bialek Tracing method.MVA-Mile method and Bialek Tracing method applies AC power flow and considers apparent power flows. The purpose of the present work is to allocate the cost pertaining to the transmission lines of the network to all the generators and demands. A load flow solution is run and, the proposed method determines how line flows depend on nodal currents. This result is then used to allocate network costs to generators and demands. The technique presented in this work is related to the allocation of the cost to GENCO‘s TRANSCO‘s and DISCO‘s. A technique for tracing the flow of electricity of lines among generators with GGDF and Bialek upstream looking algorithm is proposed. With these methods correct economic signals are generated for all players. All these methods are tested on IEEE 14 bus system.
Cost Allocation of Reactive Power Using Matrix Methodology in Transmission Ne...IJAAS Team
In the deregulated market environment as generation, transmission and distribution are separate entities; reactive power flow in transmission lines is a question of great importance. Due to inductive load characteristic, reactive power is inherently flowing in transmission line. Hence under restructured market this reactive power allocation is necessary. In this work authors presents a power flow tracing based allocation method for reactive power to loads. MVAr-mile method is used for allocation of reactive power cost. A sample 6 bus and IEEE 14 bus system is used for showing the feasibility of developed method.
Optimal power flow based congestion management using enhanced genetic algorithmsIJECEIAES
Congestion management (CM) in the deregulated power systems is germane and of central importance to the power industry. In this paper, an optimal power flow (OPF) based CM approach is proposed whose objective is to minimize the absolute MW of rescheduling. The proposed optimization problem is solved with the objectives of total generation cost minimization and the total congestion cost minimization. In the centralized market clearing model, the sellers (i.e., the competitive generators) submit their incremental and decremental bid prices in a real-time balancing market. These can then be incorporated in the OPF problem to yield the incremental/ decremental change in the generator outputs. In the bilateral market model, every transaction contract will include a compensation price that the buyer-seller pair is willing to accept for its transaction to be curtailed. The modeling of bilateral transactions are equivalent to the modifying the power injections at seller and buyer buses. The proposed CM approach is solved by using the evolutionary based Enhanced Genetic Algorithms (EGA). IEEE 30 bus system is considered to show the effectiveness of proposed CM approach.
Recent many works have concentrated on
dynamically turning on/off some base stations (BSs) in order to
improve energy efficiency in radio access networks (RANs). In
this survey, we broaden the research over BS switching
operations, which should competition up with traffic load
variations. The proposed method formulate the traffic variations
as a Markov decision process which should differ from dynamic
traffic loads which are still quite challenging to precisely forecast.
A reinforcement learning framework based BS switching
operation scheme was designed in order to minimize the energy
consumption of RANs. Furthermore a transfer actor-critic
algorithm (TACT) is used to speed up the ongoing learning
process, which utilizes the transferred learning expertise in
historical periods or neighboring regions. The proposed TACT
algorithm performs jumpstart and validates the feasibility of
significant energy efficiency increment.
techTransmission usage and cost allocation using shapley value and tracing me...elelijjournal
In the deregulated power system, transmission pricing has become a very important task because it is necessary to develop an efficient, feasible and reliable pricing scheme that can generate the useful economic signals to network users such as generating companies, transmission companies, distribution companies and customers. The objective of this paper is to compare transmission usage and cost allocation scheme to loads (and/or generators) based on Shapley value method and power flow tracing method.Modified Kirchhoff matrix is used for power flow tracing. A comparison is done between the both methods.
A case study based on sample 6 bus power system is applied to check the feasibility and reliability of the proposed usage and cost allocation methodology.
A MULTIPURPOSE MATRICES METHODOLOGY FOR TRANSMISSION USAGE, LOSS AND RELIABIL...ecij
In the era of power system restructuring there is a need of simplified method which provides a complete allocation of usage, transmission losses and transmission reliability margin. In this paper, authors presents a combined multipurpose matrices methodology for Transmission usage, transmission loss and transmission reliability margin allocation. Proposed methodology is simple and easy to implement on large power system. A modified Kirchhoff matrix is used for allocation purpose. A sample 6 bus system is used to demonstrate the feasibility of proposed methodology.
Allocation of Transmission Cost Using Power Flow Tracing MethodsIJERA Editor
In the open access restructured power system market, it is necessary to develop an appropriate pricing scheme that can provide the useful economic information to market participants, such as generation, transmission companies and customers. Though many methods have already been proposed, but accurately estimating and allocating the transmission cost in the transmission pricing scheme is still a challenging task. This work addresses the problem of allocating the cost of the transmission network to generators and demands. In this work four methods using DC Power flow and AC power flow have been attempted. They are MW-Mile Method, MVA-Mile Method, GGDF method and Bialek Tracing method.MVA-Mile method and Bialek Tracing method applies AC power flow and considers apparent power flows. The purpose of the present work is to allocate the cost pertaining to the transmission lines of the network to all the generators and demands. A load flow solution is run and, the proposed method determines how line flows depend on nodal currents. This result is then used to allocate network costs to generators and demands. The technique presented in this work is related to the allocation of the cost to GENCO‘s TRANSCO‘s and DISCO‘s. A technique for tracing the flow of electricity of lines among generators with GGDF and Bialek upstream looking algorithm is proposed. With these methods correct economic signals are generated for all players. All these methods are tested on IEEE 14 bus system.
Cost Allocation of Reactive Power Using Matrix Methodology in Transmission Ne...IJAAS Team
In the deregulated market environment as generation, transmission and distribution are separate entities; reactive power flow in transmission lines is a question of great importance. Due to inductive load characteristic, reactive power is inherently flowing in transmission line. Hence under restructured market this reactive power allocation is necessary. In this work authors presents a power flow tracing based allocation method for reactive power to loads. MVAr-mile method is used for allocation of reactive power cost. A sample 6 bus and IEEE 14 bus system is used for showing the feasibility of developed method.
Optimal power flow based congestion management using enhanced genetic algorithmsIJECEIAES
Congestion management (CM) in the deregulated power systems is germane and of central importance to the power industry. In this paper, an optimal power flow (OPF) based CM approach is proposed whose objective is to minimize the absolute MW of rescheduling. The proposed optimization problem is solved with the objectives of total generation cost minimization and the total congestion cost minimization. In the centralized market clearing model, the sellers (i.e., the competitive generators) submit their incremental and decremental bid prices in a real-time balancing market. These can then be incorporated in the OPF problem to yield the incremental/ decremental change in the generator outputs. In the bilateral market model, every transaction contract will include a compensation price that the buyer-seller pair is willing to accept for its transaction to be curtailed. The modeling of bilateral transactions are equivalent to the modifying the power injections at seller and buyer buses. The proposed CM approach is solved by using the evolutionary based Enhanced Genetic Algorithms (EGA). IEEE 30 bus system is considered to show the effectiveness of proposed CM approach.
Recent many works have concentrated on
dynamically turning on/off some base stations (BSs) in order to
improve energy efficiency in radio access networks (RANs). In
this survey, we broaden the research over BS switching
operations, which should competition up with traffic load
variations. The proposed method formulate the traffic variations
as a Markov decision process which should differ from dynamic
traffic loads which are still quite challenging to precisely forecast.
A reinforcement learning framework based BS switching
operation scheme was designed in order to minimize the energy
consumption of RANs. Furthermore a transfer actor-critic
algorithm (TACT) is used to speed up the ongoing learning
process, which utilizes the transferred learning expertise in
historical periods or neighboring regions. The proposed TACT
algorithm performs jumpstart and validates the feasibility of
significant energy efficiency increment.
Small Signal Stability Improvement and Congestion Management Using PSO Based ...IDES Editor
In this paper an attempt has been made to study the
application of Thyristor Controlled Series Capacitor (TCSC)
to mitigate small signal stability problem in addition to
congestion management of a heavily loaded line in a
multimachine power system. The Flexible AC Transmission
System (FACTS) devices such as TCSC can be used to control
the power flows in the network and can help in improvement
of small signal stability aspect. It can also provide relief to
congestion in the heavily loaded line. However, the
performance of any FACTS device highly depends upon its
parameters and placement at suitable locations in the power
network. In this paper, Particle Swarm Optimization (PSO)
method has been used for determining the optimal locations
and parameters of the TCSC controller in order to damp small
signal oscillations. Transmission Line Flow (TLF) Sensitivity
method has been used for curtailment of non-firm load to
limit power flow congestion. The results of simulation reveals
that TCSC controllers, placed optimally, not only mitigate
small signal oscillations but they can also alleviate line flow
congestion effectively.
Heuristic remedial actions in the reliability assessment of high voltage dire...IJECEIAES
Planning of high voltage direct current (HVDC) grids requires inclusion of reliability assessment of alternatives under study. This paper proposes a methodology to evaluate the adequacy of voltage source converter/VSCHVDC networks. The methodology analyses the performance of the system using N-1 and N-2 contingencies in order to detect weaknesses in the DC network and evaluates two types of remedial actions to keep the entire system under the acceptable operating limits . The remedial actions are applied when a violation of these limits on the DC system occurs; those include topology changes in the network and adjustments of power settings of VSC converter stations. The CIGRE B4 DC grid test system is used for evaluating the reliability/adequacy performance by means of the proposed methodology in this paper. The proposed remedial actions are effective for all contingencies; then, numerical results are as expected. This work is useful for planning and operation of grids based on VSC-HVDC technology.
In this study, optimal economic load dispatch problem (OELD) is resolved by
a novel improved algorithm. The proposed modified moth swarm algorithm
(MMSA), is developed by proposing two modifications on the classical moth
swarm algorithm (MSA). The first modification applies an effective formula
to replace an ineffective formula of the mutation technique. The second
modification is to cancel the crossover technique. For proving the efficient
improvements of the proposed method, different systems with discontinuous
objective functions as well as complicated constraints are used. Experiment
results on the investigated cases show that the proposed method can get less
cost and achieve stable search ability than MSA. As compared to other
previous methods, MMSA can archive equal or better results. From this view,
it can give a conclusion that MMSA method can be valued as a useful method
for OELD problem.
Power loss reduction, improvement of voltage profile, system reliability and system security are the important objectives that motivated researchers to use custom power devices/FACTS devices in power systems. The existing power quality problems such as power losses, voltage instability, voltage profile problem, load ability issues, energy losses, reliability problems etc. are caused due to continuous load growth and outage of components. The significant qualities of custom power devices /FACTS devices such as power loss reduction, improvement of voltage profile, system reliability and system security have motivated researchers in this area and to implement these devices in power system. The optimal placement and sizing of these devices are determined based on economical viability, required quality, reliability and availability. In published literatures, different algorithms are implemented for optimal placement of these devices based on different conditions. In this paper, the published literatures on this field are comprehensively reviewed and elaborate comparison of various algorithms is compared. The inference of this extensive comparative analysis is presented. In this research, Meta heuristic methods and sensitive index methods are used for determining the optimal location and sizing of custom power devices/FACTS devices. The combination of these two methods are also implemented and presented.
The paper discusses about a hybrid model with an evolutionary algorithm (HEA) for identifying the multi-type flexible AC transmission systems (FACTS) procedures to improve the total transfer capability (TTC). To reduce the loss of power this transferences among various control regions. FACTS devices with Multi objective optimal power flow (OPF) which include TTC to determine a reasonable value without violating system limitations. The results are simulated for FACTS devices with the HEA algorithm which emerges TTC value using an efficient methods using conventional transmission system. The simulation results are obtained by MATLAB/SIMULINK environment.
Coordinated planning in improving power quality considering the use of nonlin...IJECEIAES
Power quality has an important role in the distribution of electrical energy. The use of non-linear load can generate harmonic spread which can reduce the power quality in the radial distribution system. This research is in form of coordinated planning by combining distributed generation placement, capacitor placement and network reconfiguration to simultaneously minimize active power losses, total harmonic distortion (THD), and voltage deviation as an objective function using the particle swarm optimization method. This optimization technique will be tested on two types of networks in the form 33-bus and 69-bus IEEE Standard Test System to show effectiveness of the proposed method. The use of MATLAB programming shows the result of simulation of increasing power quality achieved for all scenario of proposed method.
A novel method for determining fixed running time in operating electric train...IJECEIAES
Tracking the optimal speed profile in electric train operation has been proposed as a potential solution for reducing energy consumption in electric train operation, at no cost to improve infrastructure of existing Metro lines as well. However, the optimal speed profile needs to meet fixed running time. Therefore, this paper focuses on a new method for determining the fixed running time complied with the scheduled timetable when trains track the optimal speed profile. The novel method to ensure the fixed running time is the numerical-analytical one. Calculating accelerating time ta, coasting time tc, braking time tb via values of holding speed vh, braking speed vb of optimal speed profile with the constraint condition: the running time equal to the demand time. The other hands, vh and vb are determined by solving nonlinear equations with constraint conditions. Additionally, changing running time suit for each operation stage of metro lines or lines starting to conduct schedules by the numerical-analytical method is quite easy. Simulation results obtained for two scenarios with data collected from electrified trains of Cat Linh-Ha Dong metro line, Vietnam show that running time complied with scheduled timetables, energy saving by tracking optimal speed profile for the entire route is up to 8.7%, if the running time is one second longer than original time, energy saving is about 11.96%.
Frequency regulation service of multiple-areas vehicle to grid application in...IJECEIAES
Regarding a potential of electric vehicles, it has been widely discussed that the electric vehicle can be participated in electricity ancillary services. Among the ancillary service products, the system frequency regulation is often considered. However, the participation in this service has to be conformed to the hierarchical frequency control architecture. Therefore, the vehicle to grid (V2G) application in this article is proposed in the term of multiple-areas of operation. The multiple-areas in this article are concerned as parking areas, which the parking areas can be implied as a V2G operator. From that, V2G operator can obtain the control signal from hierarchical control architecture for power sharing purpose. A power sharing concept between areas is fulfilled by a proposed adaptive droop factor based on battery state of charge and available capacity of parking area. A nonlinear multiplier factor is used for the droop adaptation. An available capacity is also applied as a limitation for the V2G operation. The available capacity is analyzed through a stochastic character. As the V2G application has to be cooperated with the hierarchical control functions, i.e. primary control and secondary control, then the effect of V2G on hierarchical control functions is investigated and discussed.
Resource aware wind farm and D-STATCOM optimal sizing and placement in a dist...IJECEIAES
Doubly fed induction generators (DFIG) based wind farms are capable of providing reactive power compensation. Compensation capability enhancement using reactors such as distributed static synchronous compensator (D-STATCOM) while connecting distribution generation (DG) systems to grid is imperative. This paper presents an optimal placement and sizing of offshore wind farms in a coastal distribution system that is emulated on an IEEE 33 bus system. A multi-objective formulation for optimal placement and sizing of the offshore wind farms with both the location and size constraints is developed. Teaching learning algorithm is used to optimize the multi-objective function constraining on the capacity and location of the offshore wind farms. The proposed formulation is a multi-objective problem for placement of the wind generator in the power system with dynamic wind supply to the power system. The random wind speed is generated as the input and the wind farm output generated to perform the optimal sizing and placement in the distributed system. MATLAB based simulation developed is found to be efficient and robust.
A New Methodology for Active Power Transmission Loss Allocation in Deregulate...IJECEIAES
This paper presents a new method for transmission loss allocation in a deregulated power system. As the power loss is a nonlinear quantity, so to allocate the loss in a common transmission corrider is a difficult task. It allocates transmission losses to loads based on the actual power flow in the lossy lines due to the concerned load. Each lossy line is subdivided into as many sub-lines as corresponding to the numbers of load attached to it. The tracing of power flow through each sub-line is worked out by using proportional sharing method. The power loss in each lossy line is equal with the total loss due to all the sub-lines under it. Then by using Pro-rata for each lossy line, the individual loss for each sub-line is formulated. As the application of Pro-rata is limited to an individual line of the system, so the error in calculation is minimized. The total loss allocated to a particular load is the sum of losses occurred in each lossy lines through which the power is flowing to the concerned load. As this method is based on the actual flow of power in the transmission line corresponding to the concerned load, hence, the loss allocation made by the method gives proper and justifiable allocations to the different loads which are attached to the system. The proposed method is applied to a six-bus system and finds the mismatch in the commonly used methods. Then, it is applied to higher bus systems in which more accurate results are obtained compared to the other methods.
Optimal cost allocation algorithm of transmission losses to bilateral contractsTELKOMNIKA JOURNAL
One of the trends in electricity reform is the involvement of bilateral contracts that will participate in electricity business development. Bilateral agreements require fair transmission loss costs compared with the integrated power system. This paper proposes a new algorithm in determining the optimal allocation of transmission loss costs for bilateral contracts based on the direct method in economic load dispatch. The calculation for an optimal power flow applies fast decoupled methods. At the same time, the determination of a fair allocation of transmission losses uses the decomposition method. The simulation results of the optimal allocation of power flow provide comparable results with previous studies. This method produces a fair allocation of optimal transmission loss costs for both integrated and bilateral parties. The proportion allocation of the transmission lines loss incurred by the integrated system and bilateral contracts reflects a fair allocation of R. 852.589 and R. 805.193, respectively.
Analysis of the Use of Universal Distribution Factors in SEC Power Gridresearchinventy
Distribution factors have been extensively used in many power system analysis and planning studies. In recent power system studies, the AC distribution factors are insensitive to the operating point and relatively sensitive at certain degree to changes in network topology. These factors are linear approximations of sensitivities of variables with various inputs. This paper presents the calculation of the universal distribution factors (UDF’s) applies them on several practical scenarios of Saudi Electricity Company (SEC) power grid. The results are analyzed and evaluated considering various system conditions of SEC load. The results show that the accuracy of the used approach is acceptable compared with exact method. This is practically beneficial to SEC in computing its grid complex power flows using UDF's at the base case without the need to recalculate UDF’s which save efforts and time.
Transmission Loss Allocation Based on Lines Current FlowIJAPEJOURNAL
In this paper, the transmission loss allocation problem has been studied and a new method for loss allocation in pool electricity markets has been proposed. To do that, at first using a transmission line loss equations respect to bus injected currents, the share of each bus from the mentioned transmission line losses has been determined. Then, this method has been applied to the total network transmission lines and the share of each bus from the total losses has been acquired. The proposed method is based on the main network relations and no any simplifying suppose has been used. Finally, the proposed method is studied on a typical network.
This paper presents a novel approach for static transmission expansion planning and
allocation of the associated expansion costs to individual market entities in a restructured power
system. The approach seeks the optimal addition of transmission lines among the possible candidate
transmission lines minimizing the overall system costs and at the same time satisfying the system
operational and security constraints. Novelty of the approach lies in applying a widely known
technique used for overload security analysis to an area such as Transmission expansion planning.
Transmission expansion costs are allocated using distribution factors to the individual entities in a
fair and transparent manner. The results for modified Garver Test system demonstrate that the
approach with the advantage of its simplicity can be applied to transmission expansion planning and
cost allocation in restructured power system
Small Signal Stability Improvement and Congestion Management Using PSO Based ...IDES Editor
In this paper an attempt has been made to study the
application of Thyristor Controlled Series Capacitor (TCSC)
to mitigate small signal stability problem in addition to
congestion management of a heavily loaded line in a
multimachine power system. The Flexible AC Transmission
System (FACTS) devices such as TCSC can be used to control
the power flows in the network and can help in improvement
of small signal stability aspect. It can also provide relief to
congestion in the heavily loaded line. However, the
performance of any FACTS device highly depends upon its
parameters and placement at suitable locations in the power
network. In this paper, Particle Swarm Optimization (PSO)
method has been used for determining the optimal locations
and parameters of the TCSC controller in order to damp small
signal oscillations. Transmission Line Flow (TLF) Sensitivity
method has been used for curtailment of non-firm load to
limit power flow congestion. The results of simulation reveals
that TCSC controllers, placed optimally, not only mitigate
small signal oscillations but they can also alleviate line flow
congestion effectively.
Heuristic remedial actions in the reliability assessment of high voltage dire...IJECEIAES
Planning of high voltage direct current (HVDC) grids requires inclusion of reliability assessment of alternatives under study. This paper proposes a methodology to evaluate the adequacy of voltage source converter/VSCHVDC networks. The methodology analyses the performance of the system using N-1 and N-2 contingencies in order to detect weaknesses in the DC network and evaluates two types of remedial actions to keep the entire system under the acceptable operating limits . The remedial actions are applied when a violation of these limits on the DC system occurs; those include topology changes in the network and adjustments of power settings of VSC converter stations. The CIGRE B4 DC grid test system is used for evaluating the reliability/adequacy performance by means of the proposed methodology in this paper. The proposed remedial actions are effective for all contingencies; then, numerical results are as expected. This work is useful for planning and operation of grids based on VSC-HVDC technology.
In this study, optimal economic load dispatch problem (OELD) is resolved by
a novel improved algorithm. The proposed modified moth swarm algorithm
(MMSA), is developed by proposing two modifications on the classical moth
swarm algorithm (MSA). The first modification applies an effective formula
to replace an ineffective formula of the mutation technique. The second
modification is to cancel the crossover technique. For proving the efficient
improvements of the proposed method, different systems with discontinuous
objective functions as well as complicated constraints are used. Experiment
results on the investigated cases show that the proposed method can get less
cost and achieve stable search ability than MSA. As compared to other
previous methods, MMSA can archive equal or better results. From this view,
it can give a conclusion that MMSA method can be valued as a useful method
for OELD problem.
Power loss reduction, improvement of voltage profile, system reliability and system security are the important objectives that motivated researchers to use custom power devices/FACTS devices in power systems. The existing power quality problems such as power losses, voltage instability, voltage profile problem, load ability issues, energy losses, reliability problems etc. are caused due to continuous load growth and outage of components. The significant qualities of custom power devices /FACTS devices such as power loss reduction, improvement of voltage profile, system reliability and system security have motivated researchers in this area and to implement these devices in power system. The optimal placement and sizing of these devices are determined based on economical viability, required quality, reliability and availability. In published literatures, different algorithms are implemented for optimal placement of these devices based on different conditions. In this paper, the published literatures on this field are comprehensively reviewed and elaborate comparison of various algorithms is compared. The inference of this extensive comparative analysis is presented. In this research, Meta heuristic methods and sensitive index methods are used for determining the optimal location and sizing of custom power devices/FACTS devices. The combination of these two methods are also implemented and presented.
The paper discusses about a hybrid model with an evolutionary algorithm (HEA) for identifying the multi-type flexible AC transmission systems (FACTS) procedures to improve the total transfer capability (TTC). To reduce the loss of power this transferences among various control regions. FACTS devices with Multi objective optimal power flow (OPF) which include TTC to determine a reasonable value without violating system limitations. The results are simulated for FACTS devices with the HEA algorithm which emerges TTC value using an efficient methods using conventional transmission system. The simulation results are obtained by MATLAB/SIMULINK environment.
Coordinated planning in improving power quality considering the use of nonlin...IJECEIAES
Power quality has an important role in the distribution of electrical energy. The use of non-linear load can generate harmonic spread which can reduce the power quality in the radial distribution system. This research is in form of coordinated planning by combining distributed generation placement, capacitor placement and network reconfiguration to simultaneously minimize active power losses, total harmonic distortion (THD), and voltage deviation as an objective function using the particle swarm optimization method. This optimization technique will be tested on two types of networks in the form 33-bus and 69-bus IEEE Standard Test System to show effectiveness of the proposed method. The use of MATLAB programming shows the result of simulation of increasing power quality achieved for all scenario of proposed method.
A novel method for determining fixed running time in operating electric train...IJECEIAES
Tracking the optimal speed profile in electric train operation has been proposed as a potential solution for reducing energy consumption in electric train operation, at no cost to improve infrastructure of existing Metro lines as well. However, the optimal speed profile needs to meet fixed running time. Therefore, this paper focuses on a new method for determining the fixed running time complied with the scheduled timetable when trains track the optimal speed profile. The novel method to ensure the fixed running time is the numerical-analytical one. Calculating accelerating time ta, coasting time tc, braking time tb via values of holding speed vh, braking speed vb of optimal speed profile with the constraint condition: the running time equal to the demand time. The other hands, vh and vb are determined by solving nonlinear equations with constraint conditions. Additionally, changing running time suit for each operation stage of metro lines or lines starting to conduct schedules by the numerical-analytical method is quite easy. Simulation results obtained for two scenarios with data collected from electrified trains of Cat Linh-Ha Dong metro line, Vietnam show that running time complied with scheduled timetables, energy saving by tracking optimal speed profile for the entire route is up to 8.7%, if the running time is one second longer than original time, energy saving is about 11.96%.
Frequency regulation service of multiple-areas vehicle to grid application in...IJECEIAES
Regarding a potential of electric vehicles, it has been widely discussed that the electric vehicle can be participated in electricity ancillary services. Among the ancillary service products, the system frequency regulation is often considered. However, the participation in this service has to be conformed to the hierarchical frequency control architecture. Therefore, the vehicle to grid (V2G) application in this article is proposed in the term of multiple-areas of operation. The multiple-areas in this article are concerned as parking areas, which the parking areas can be implied as a V2G operator. From that, V2G operator can obtain the control signal from hierarchical control architecture for power sharing purpose. A power sharing concept between areas is fulfilled by a proposed adaptive droop factor based on battery state of charge and available capacity of parking area. A nonlinear multiplier factor is used for the droop adaptation. An available capacity is also applied as a limitation for the V2G operation. The available capacity is analyzed through a stochastic character. As the V2G application has to be cooperated with the hierarchical control functions, i.e. primary control and secondary control, then the effect of V2G on hierarchical control functions is investigated and discussed.
Resource aware wind farm and D-STATCOM optimal sizing and placement in a dist...IJECEIAES
Doubly fed induction generators (DFIG) based wind farms are capable of providing reactive power compensation. Compensation capability enhancement using reactors such as distributed static synchronous compensator (D-STATCOM) while connecting distribution generation (DG) systems to grid is imperative. This paper presents an optimal placement and sizing of offshore wind farms in a coastal distribution system that is emulated on an IEEE 33 bus system. A multi-objective formulation for optimal placement and sizing of the offshore wind farms with both the location and size constraints is developed. Teaching learning algorithm is used to optimize the multi-objective function constraining on the capacity and location of the offshore wind farms. The proposed formulation is a multi-objective problem for placement of the wind generator in the power system with dynamic wind supply to the power system. The random wind speed is generated as the input and the wind farm output generated to perform the optimal sizing and placement in the distributed system. MATLAB based simulation developed is found to be efficient and robust.
A New Methodology for Active Power Transmission Loss Allocation in Deregulate...IJECEIAES
This paper presents a new method for transmission loss allocation in a deregulated power system. As the power loss is a nonlinear quantity, so to allocate the loss in a common transmission corrider is a difficult task. It allocates transmission losses to loads based on the actual power flow in the lossy lines due to the concerned load. Each lossy line is subdivided into as many sub-lines as corresponding to the numbers of load attached to it. The tracing of power flow through each sub-line is worked out by using proportional sharing method. The power loss in each lossy line is equal with the total loss due to all the sub-lines under it. Then by using Pro-rata for each lossy line, the individual loss for each sub-line is formulated. As the application of Pro-rata is limited to an individual line of the system, so the error in calculation is minimized. The total loss allocated to a particular load is the sum of losses occurred in each lossy lines through which the power is flowing to the concerned load. As this method is based on the actual flow of power in the transmission line corresponding to the concerned load, hence, the loss allocation made by the method gives proper and justifiable allocations to the different loads which are attached to the system. The proposed method is applied to a six-bus system and finds the mismatch in the commonly used methods. Then, it is applied to higher bus systems in which more accurate results are obtained compared to the other methods.
Optimal cost allocation algorithm of transmission losses to bilateral contractsTELKOMNIKA JOURNAL
One of the trends in electricity reform is the involvement of bilateral contracts that will participate in electricity business development. Bilateral agreements require fair transmission loss costs compared with the integrated power system. This paper proposes a new algorithm in determining the optimal allocation of transmission loss costs for bilateral contracts based on the direct method in economic load dispatch. The calculation for an optimal power flow applies fast decoupled methods. At the same time, the determination of a fair allocation of transmission losses uses the decomposition method. The simulation results of the optimal allocation of power flow provide comparable results with previous studies. This method produces a fair allocation of optimal transmission loss costs for both integrated and bilateral parties. The proportion allocation of the transmission lines loss incurred by the integrated system and bilateral contracts reflects a fair allocation of R. 852.589 and R. 805.193, respectively.
Analysis of the Use of Universal Distribution Factors in SEC Power Gridresearchinventy
Distribution factors have been extensively used in many power system analysis and planning studies. In recent power system studies, the AC distribution factors are insensitive to the operating point and relatively sensitive at certain degree to changes in network topology. These factors are linear approximations of sensitivities of variables with various inputs. This paper presents the calculation of the universal distribution factors (UDF’s) applies them on several practical scenarios of Saudi Electricity Company (SEC) power grid. The results are analyzed and evaluated considering various system conditions of SEC load. The results show that the accuracy of the used approach is acceptable compared with exact method. This is practically beneficial to SEC in computing its grid complex power flows using UDF's at the base case without the need to recalculate UDF’s which save efforts and time.
Transmission Loss Allocation Based on Lines Current FlowIJAPEJOURNAL
In this paper, the transmission loss allocation problem has been studied and a new method for loss allocation in pool electricity markets has been proposed. To do that, at first using a transmission line loss equations respect to bus injected currents, the share of each bus from the mentioned transmission line losses has been determined. Then, this method has been applied to the total network transmission lines and the share of each bus from the total losses has been acquired. The proposed method is based on the main network relations and no any simplifying suppose has been used. Finally, the proposed method is studied on a typical network.
This paper presents a novel approach for static transmission expansion planning and
allocation of the associated expansion costs to individual market entities in a restructured power
system. The approach seeks the optimal addition of transmission lines among the possible candidate
transmission lines minimizing the overall system costs and at the same time satisfying the system
operational and security constraints. Novelty of the approach lies in applying a widely known
technique used for overload security analysis to an area such as Transmission expansion planning.
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fair and transparent manner. The results for modified Garver Test system demonstrate that the
approach with the advantage of its simplicity can be applied to transmission expansion planning and
cost allocation in restructured power system
International Journal of Engineering Research and Development (IJERD)IJERD Editor
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Framework Development to Analyze the Distribution System for Upper Karnali Hy...IJMERJOURNAL
ABSTRACT: Upper Karnali Hydropower Project is a 900 MW run of river hydro project in Nepal, from where the generated power will be transmitted to Indian grid via a dedicated transmission line, and hence local consumers will not be fed through this plant. As per the concession agreement executed between the Government of Nepal and the developers, a 2 MW hydro plant shall be developed at the toe of the dam by using the environmental release discharge. A previous study conducted by the authors, identified the optimal electric network, taking into consideration different factors such as demography, topography, socio-economic and technical feasibility. In this study, however, the authors analyze the performance of the system by carrying out a techno-economic study using computational grid network design analysis. A framework for Load Flow Analysis is developed and used to analyze the developed network. For verification, the results obtained are compared with those from standard 33 bus radial distribution feeder system and Forward/Backward based Sweep algorithm creating paired sample T-test. No significant difference between the results for a 95% confidence of interval is observed. After observing the results, it is concluded that the developed framework, as well as the grid network, are technical, computationally and economically efficient.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Nowadays, the electricity demand is increasing daily and hence it is important not only to extract electrical energy from all possible new power resources but also to reduce power losses to an acceptable minimum level in the existing distribution networks where a huge amount of power dissipation occurred. A lot of power is remarkably dissipated in Yangon distribution system. Network reconfiguration method is employed for loss reduction and exhaustive search technique is also applied to achieve the minimal loss switching scheme. Network reconfiguration is performed by opening sectionalizing switches and closing tie switches of the network for loss reduction. The distribution network for existing and reconfiguration conditions are modelled and simulated by Electrical Transient Analyzer Program (ETAP) 7.5 version software. The proposed method is tested on 83-Bus and 74-Bus radial distribution system in Yangon city since it is long-length, overloaded lines and high level of power dissipation is occurred in this system. According to simulation results of load flow analysis, voltage profile enhancement, power loss reduction and cost saving for proposed system are revealed in this paper.
Keywords — exhaustive search technique, loss reduction, load flow analysis, cost saving
.
A Proactive Greedy Routing Protocol Precludes Sink-Hole Formation in Wireless...ijwmn
The International Journal of Wireless & Mobile Networks (IJWMN) is a bi monthly open access peer-reviewed journal that publishes articles which contribute new results in all areas of Wireless & Mobile Networks. The journal focuses on all technical and practical aspects of Wireless & Mobile Networks. The goal of this journal is to bring together researchers and practitioners from academia and industry to focus on advanced wireless & mobile networking concepts and establishing new collaborations in these areas.
The effect of load modelling on phase balancing in distribution networks usin...IJECEIAES
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Investigation of Ant Colony Optimization Algorithm for Efficient Energy Utili...IJCNCJournal
Maintaining the energy conservation is considered as an important approach to increase the lifetime of WSN. In fact, an energy reduction mechanism is considered as the main concept to enhance the lifespan of the network. In this paper, the performance analysis/evaluation of optimization technique, specifically, Ant Colony Optimization (ACO) and modified ACO (m-ACO) in the routing method are investigated. This network analysis is done by 100 iterations and differentiated with 50, 75 and 100 numbers of nodes. Finally, experimental results illustrate that the performance of m-ACO algorithm obtained the obvious performance, which is comparatively better than ACO algorithm, because it improves the routing efficiency by pheromone evaporation control and energy threshold value. It demonstrates that m-ACO algorithm gives better results than ACO in terms of throughput (1.41%), transmission delay (1.43%), packet delivery ratio (1.41%), energy consumption (2.05%), and the packet loss (9.70%). The convergence rate is analysed for ACO and m-ACO algorithms with respect to 100 number of iterations for WSNs.
Investigation of Ant Colony Optimization Algorithm for Efficient Energy Utili...IJCNCJournal
Maintaining the energy conservation is considered as an important approach to increase the lifetime of WSN. In fact, an energy reduction mechanism is considered asthe main concept to enhance the lifespan of the network. In this paper, the performance analysis/evaluation of optimization technique, specifically, Ant Colony Optimization (ACO) and modified ACO (m-ACO) in the routing method are investigated. This network analysis is done by 100 iterations and differentiated with 50, 75 and 100 numbers of nodes. Finally, experimental results illustrate that the performance of m-ACO algorithm obtained the obvious performance,which is comparatively better than ACO algorithm, because it improves the routing efficiency by pheromone evaporation control and energy threshold value. It demonstrates that m-ACO algorithm gives better results than ACO in terms of throughput (1.41%), transmission delay (1.43%), packet delivery ratio (1.41%), energy consumption (2.05%), and the packet loss (9.70%). The convergence rate is analysed for ACO and m-ACO algorithms with respect to 100 number of iterations for WSNs.
New solutions for optimization of the electrical distribution system availabi...Mohamed Ghaieth Abidi
This paper deals with the availability in microgrids that are composed of a set of sources (Photovoltaic generators, wind turbines, diesel generators and batteries) and a set of loads (critical and uncritical loads). The energy produced by various sources will be grouped in an alternative bus (AC bus), and it will be distributed on loads through an electrical distribution system. The occurrence of a fault in the system can cause a total or partial unavailability of energy required by the loads. The objective of this paper is to characterize the fault caused by the limited reliability of the components of the electrical distribution system and to propose an new design methodology to optimize the availability of this system (as well as the availability of power supply) by taking into account all the economic constraints. The proposed methodology is based on the redundancy of electrical distribution paths. An application of this optimization to a petroleum platform shows clearly a high degree of supply availability distribution in microgrid.
Influencing Factors on Power Losses in Electric Distribution NetworkIJAEMSJORNAL
Line losses reduction greatly affects the performance of the electric distribution network. This paper aims to identify the influencing factors causing power losses in that network. Newton-Raphson method is used for the loss assessment and the Sensitivity analysis by approach One-Factor-At-A-Time (OAT) for the influencing factors identification. Simulation with the meshed IEEE-30 bus test system is carried out under MATLAB environment. Among the 14 parameters investigated of each line, the result shows that the consumed reactive powers by loads, the bus voltages and the linear parameters are the most influencing on the power losses in several lines. Thus, in order to optimize these losses, the solution consists of the reactive power compensation by using capacitor banks; then the placement of appropriate components in the network according to the corresponding loads; and finally, the injection of other energy sources into the bus which recorded high level losses by using the hybrid system for instance.
Power Quality Improvement in Power System using UPFCijtsrd
Occurrence of a fault in a power system causes transients. To stabilize the system, Power System Stabilizer (PSS) and Automatic Voltage Regulator (AVR) are used. Load flow analysis is done to analyze the transients introduced in the system due to the occurrence of faults. The Flexible Alternating Current Transmission (FACTS) devices such as UPFC are becoming important in suppressing power system oscillations and improving system damping. The UPFC is a solid-state device, which can be used to control the active and reactive power. This paper considers a power system as a case study for investigating the performance of UPFC is achieving stability. By using a UPFC the oscillation introduced by the faults, the voltage deviations and speed deviations can be damped out quickly than a system without a UPFC. The effectiveness of UPFC in suppressing power system oscillation is investigated by analyzing their voltage deviations and reactive power support in this paper. A proportional integral (PI) controller has been employed for the UPFC. It is also shown that a UPFC can control independently the real and reactive power flow in a transmission line. Navneet Kaur | Gagan Deep Yadav"Power Quality Improvement in Power System using UPFC" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-2 | Issue-1 , December 2017, URL: http://www.ijtsrd.com/papers/ijtsrd7139.pdf http://www.ijtsrd.com/engineering/electrical-engineering/7139/power-quality-improvement-in-power-system-using-upfc/navneet-kaur
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ACTIVE POWER AND COST ALLOCATION IN OPEN ACCESS ENVIRONMENT UTILIZING POWER FLOW TRACING METHOD CONSIDERING N-1 CONTINGENCY CONDITION
1. Electrical & Computer Engineering: An International Journal (ECIJ) Volume 3, Number 2, June 2014
DOI : 10.14810/ecij.2014.3203 25
ACTIVE POWER AND COST ALLOCATION IN OPEN
ACCESS ENVIRONMENT UTILIZING POWER FLOW
TRACING METHOD CONSIDERING N-1
CONTINGENCY CONDITION
Pawan Rathore1
, Garima Naidu2
, Ganga Agnihotri3
and Baseem Khan4
1,2,3,4
Department of Electrical Engineering, MANIT, Bhopal, India
ABSTRACT
The transmission usage cost allocation is one of the major issues experienced by the Electric Supply
Industries. In this paper, authors have considered Line Outage Distribution Factor (LODF) for
allocating the transmission usage cost allocation under contingency condition. Authors have modified the
distribution factor for maximum flow and propose a novel Maximum Line Outage Distribution Factor
(MLODF) which depends upon the redistribution of the generation in the line flow considering N-1
security constraints. Similarly, for transmission loss cost allocation under contingency condition
Maximum Line Outage Loss Distribution Factor (MLOLDF) is developed. Full recovery policy of
transmission cost allocation is considered. The reliability and accuracy of the proposed method is tested
on the sample 6 bus system.
KEYWORDS
LODF, MLODF, MLOLDF, MW-Mile method, Transmission cost allocation, Transmission loss cost
allocation, Transmission Pricing.
NOMENCLATURE
P i,m Power flow in the line i after an outage in the line m.
Pi Normal power flow in the line i.
TCt Cost allocated to network user t.
TC Total transmission usage cost.
TLC Total transmission loss cost.
Pt Power of user t at the time of system peak.
Pmax System maximum load.
Ck Cost per MW per unit length of line k.
Lk Length of the line k.
MWt,i Power flow in the line i due to user t.
Ft,i Power flow on the facility i caused by user t.
Fmax,i Capacity of facility i.
Fopt,k Optimal capacity of transmission line k.
p_linei Power flow in the line i.
pl_linei Power loss in the line i.
Km Modified Kirchhoff Matrix.
I Identity Matrix
PG Total active power of generators.
2. Electrical & Computer Engineering: An International Journal (ECIJ) Volume 3, Number 2, June 2014
26
PL Total active power of loads.
1. INTRODUCTION
Electricity growth is very important for any country’s development. Transmission System plays
a vital role in the power system. It is considered as the backbone of the system. In every country
transmission system is considered natural monopoly. The transmission usage and cost is
allocated on a non discriminate basis depending on the actual power flows and point of
interconnection. If any new generation is coming up, then it has to first plan for evacuation of
power to the grid. Now due to deregulation in the electric market, the transmission system has
been opened to private participants. Electricity has become commodity; one can buy or sell the
electricity. Transmission pricing technique should be sufficient to fulfill following issues:
• Transmission pricing method should be non-discriminatory in nature.
• Charges to all generators and loads are in a comparable manner.
• It should be able to recover the full fixed cost of the transmission system.
• There should be proper monitoring in the branch flows.
• It should periodically update the transmission system cost.
• It should be able to encourage new generators to be established.
Electric utilities traditionally allocate the transmission cost to each generator and load based on
Postage Stamp and Contract Path methods [1]. In the Postage Stamp method, transmission
network users are charged based on an average cost and the magnitude of the allocated power.
On the other hand, in the Contract Path method, power is confined to flow along an artificially
specified path. Based on the calculation of the actual extent of use of the transmission network
MW Mile method is proposed [2], [3]. The cost depends upon the magnitude, the path and the
distance travelled by the transacted power. Various modified MW Mile methodologies have been
proposed in the literature [4-7].
Tsukamoto and Iyoda [11] introduced the concept of cooperative game theory for fixed-cost
allocation to wheeling transactions in a power system. Yu et al. [12] presented a method for
transmission embedded cost allocation based on the use of line capacity. Tan and Lie [13]
applied the Shapley value approach for the transmission network cost allocation. Zolezzi and
Rudnick [14] allocated the cost of existing or expanding the network based on a model that
integrates cooperation and coordination among the agents with solutions based on the Nucleolus
and Shapley value approaches. Yu et al. [15] allocated the capacity-use and reliability-based
transmission embedded cost using the Nucleolus and Shapley value concept. Stamtsis and Erlich
[16] analyzed the cost allocation problem for the fixed cost of a power system and realized that
the Shapley value is preferable when it lies in the core of the game [17].
In Aug 2013, Orfanos et al. [18] explained a power flow based method to allocate the
transmission fixed cost in a pool based electricity market considering contingencies. They
considered that the possible maximum used capacity of a transmission network is the maximum
power flow during contingency analysis. The first attempt to trace real and reactive power flow
was done by Bialek et al. [19] when Topological Generation Distribution factors based Power
flow tracing were proposed in March 1996 which explained the method for tracing generators’
output. Proportional Sharing method was used to trace the flow of electricity. Distribution factors
[20] are defined by sensitivity analysis relating a change in power injection at a certain bus to a
change in the power flow on a particular line. In 1996, Bialek [20] presented a method which
allows allocating the supplement charge for transmission services to individual load or generator.
Topological factor represents the share of the load in a power flow while the generalized factor
3. Electrical & Computer Engineering: An International Journal (ECIJ) Volume 3, Number 2, June 2014
27
shows the impact of the load on the power flow. Generalized Generation / Load Distribution
Factors (GGDFs/GLDFs) are dependent upon line parameter not on the reference bus position.
In Feb 1997, Kirschen et al. [21] introduced a power flow tracing method based on the
proportional sharing assumption which introduced the concept of domains, commons, and links.
In Nov 2000, Gubina et al. [22] presented a new method to determine the generators’
contribution to a particular load by using the nodal generation distribution factors (NGDF-s). The
method also handled the reactive power. In Aug 2000, Felix et al. [23] proposed the use of graph
theory to calculate the contributions of individual generator and load to line flows and the real
power transfer between individual generator and load. A matrix inverse calculation is required
which is a time taking process for a large power system.
In 2008, Xie et al. [24] proposed and explained the power flow tracing algorithms found in the
Extended Incidence Matrix (EIM) considering loop flows. Charges had been allocated to
generators and loads in 50:50 ratios. In Feb 2007, Conejo et al. [25] proposed a method of
network cost allocation based on Z-bus matrix. In Aug 2006, Abhyankar et al. [26] proposed real
power flow tracing method based on linear constrained optimization approach. They introduced a
modified postage stamp method which evaluates a traceable solution that minimizes overall
deviation from the postage stamp allocation. In Aug 2010, Rao et al. [27] explained the Min-Max
fair allocation criteria for transmission system usage allocation.
In 2004, P. N. Biskas et al. [28] proposed a security constrained optimal power flow (SC-OPF)
solution to trace each user’s contribution to the line flows of the network. For this, first usage
and then TRM allocation was done. In 1998, Silva et al. [29] considered the transmission
network operation under normal as well as contingency condition for allocating cost to
generators. In July 2004, D. Hur et al. [30] proposed various methods to allocate reliability
contribution to market participants.
In June 2010, V. Vijay et al [31] proposed a novel probabilistic transmission pricing
methodology with consideration of transmission reliability margin. In 2008, H. Monsef et al.
[32] presented the transmission cost allocation based on use of reliability margin under
contingency condition. For this purpose a probability index was defined. The cost of the unused
facility under normal system operation, i.e. the reliability margin cost has been proposed in [33-
35] to be allocated to transmission users following a contingency analysis.
In this paper, authors has presented a technique for allocating the usage and cost of the
transmission system based on Shapley Value and power flow tracing method (Proportional
Sharing). Different recovery policies for allocating the usage and cost are as follows:-
• Allocating 100% usage and cost to all loads.
• Allocating 100% usage and cost to all generators.
• Allocating 50% - 50% usage and cost to all generators and loads respectively.
• Allocating 33% - 67% usage and cost to all generators and loads respectively.
• Allocating 23% - 77% usage and cost to all generators and loads respectively.
In this paper, authors has considered 100% usage and cost allocation to all loads only. In this
paper, Line Outage Distribution Factor (LODF) [35] and proposed Maximum Line Outage
Distribution Factor (MLODF) are considered for transmission usage cost allocation. Network
usage cost is determined by LODF and MLODF. MW-Mile method is used for proposed cost
allocation method. Allocation to generators and loads is done by using modified Kirchhoff
matrix methodology [6], [7]. Transmission pricing mechanism should be able to provide
following signals:
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28
• If in any particular area the generation charges are high and there is adequate
transmission capability, transmission charges will reduce by adding generation there.
• If in any particular area the generation charges are high and transmission system is
operating close to capability, transmission charges will increase by adding generation
there.
• If the demand is more near the generation hub, then the transmission charges due to flow
of the power is low.
Figure 1. shows the process chart for the determination of transmission charges.
Figure 1. Process chart for the determination of transmission charges
2. POWER FLOW TRACING METHOD
Kirchhoff matrix is considered for power flow tracing [6]. In Modified Kirchhoff matrix the
sum of all elements in the column j equals the total active power of generators at bus i.e.
T
Gm
T
PKI )(= (1)
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The above equation can be rewritten as follows:
G
T
m PKI )(
1−
= (2)
From the above matrix, inverse of Modified Kirchhoff matrix ( ) is obtained which is used
for power flow tracing. The active power distribution of ith
generator is given as:
∑ =
=
n
j LjijGi PtP 1
(3)
where denotes the active power distribution of generator output at bus to the load
situated at bus [6]. Thus
Ljijji PtP =→ (4)
Eq. (4) gives the generators’ share to loads in the system.
On the same line for calculating the generators’ share to line flows Eq. (4) is modified by
replacing load power from the line flows as shown in Eq.(5). For example, the generators’ share
situated at bus s to the line s-t is given by
gstistsi aPtP =−→ (5)
Hence Eq. (4) and Eq. (5) give the generators’ share to loads and line flows. Similarly, the usage
allocated to a load for the use of all lines can be defined by using instead of .
For calculating the loads’ share in line flows and generated power, same procedure is followed.
Consider dual of Eq. (2).
G
T
mLLL PKPP )(
1−
= (6)
where the diagonal matrix and R= is the
extraction factor matrix of loads from generators [7].
By using an extraction factor matrix, loads’ share in generating power and line flows is
calculated.
For transmission loss allocations to generator, consider Eq. (5). In this equation, line flow Pst is
replaced by the transmission loss which is coming from the elements of the Kirchhoff loss
matrix and .
Hence transmission losses of line s-t allocated to generator located at bus i is given by:
st
l
istsi
l
PtP =−→ (7)
Similarly, transmission losses of line s-t allocated to load situated at bus j is given by:
st
l
jstsj
l
PrP =−→ (8)
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From Eq. (7) and Eq. (8) losses are allocated to generators and loads respectively. This method
of loss allocation is said to be direct because all the calculation is already done for usage
allocation.
3. TRANSMISSION ACTIVE COST ALLOCATION
Transmission usage cost allocation to users should be based on usage. The most common
method used by electric utilities is Postage Stamp method. It depends upon the average system’s
cost and some factors which are usually the functions of the season, working day or holiday.
The total transmission cost to network users using Postage Stamp method is as follows:
max
*
P
P
TCTC t
t = (9)
In a power pool market, power flow based methods are used to calculate the contributions of
each network user (generators or loads) to transmission lines by using power flow tracing
algorithm [20] or the distributed factors [25]. After power flow allocation, network cost is
allocated using MW Mile method [34].
In the MW Mile method, transmission usage cost allocation reflects the relative usage of the
transmission network.
∑∑
∑
∈ ∈
∈
=
Tt Ii
itii
Kk
itii
t
MWLc
MWLc
TCTC
,
,
**
**
* (10)
System charges can be evaluated based on either the unused or the used capacity. Full recovery
of the transmission cost is guaranteed in the unused method. In the unused and used absolute
methods, charges are calculated as follows:
∑
∑
∈
∈
=
Tt
it
it
Ii
iunusedabst
F
F
CTC
||
||
*
,
,
_, (11)
i
it
Ii
iusedabst
F
F
CTC
max,
,
_,
||
*∑∈
= (12)
The optimal capacity of each line under contingency condition is given as:
mmiimi linepLODFlineplinefp _*__ ,, += (13)
mmiimi linepMLODFlineplinefp _*__ ,, += (14)
The possible maximum usage capacity of each line is given as follows:
max,
max,
,2,1,, *|)_||,...._||,_max(|
i
c
i
Iiiiiopt
F
F
linefplinefplinefpF = (15)
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31
Fc
i,max is the short term emergency rating of the line [18]. Due to optimal power flow in the line,
the transmission usage cost to users is given as follows [18]:
∑∈
=
Ii iopt
it
ioptt
F
F
CTC
,
,
,
||
* (16)
Total transmission loss cost to users is given as follows:
∑∈
=
Ii iopt
it
ioptt
Fl
Fl
ClTLC
,
,
,
||
* (17)
3. DISTRIBUTION FACTORS
During outage, the power flow in a line is different from that of normal conditions. The LODF
is defined as the redistribution of the particular generation after an outage. Thus, Line Outage
Distribution Factor is defined as the ratio of difference of the power flow in the line i after an
outage in the line m and the normal power flow in the line m to that of normal power flow in the
line i whereas MLODF is the ratio of difference in the power flow in the line i after an outage in
the line m and the normal power flow in the line m to that of maximum power flow in the line i
after an outage. The LODF is given by:
( ) },{ ,
,
imi
i
mmi
PP
P
PP
LODF >
−
= (18)
The MLODF is given as:
( ) },{ ,
,
,
imi
iopt
mmi
PP
P
PP
MLODF >
−
= (19)
For loss allocation, above two factors are modified as follows:
( ) },{ ,
,
imi
i
mmi
PlPl
Pl
PlPl
LOLDF >
−
= (20)
The MLOLDF is given as:
( ) },{ ,
,
,
imi
iopt
mmi
PlPl
Pl
PlPl
MLOLDF >
−
= (21)
Line Outage Loss Distribution Factor is defined as the ratio of difference of the power loss in
the line i after an outage in the line m and the normal power loss in the line m to that of normal
power loss in the line i whereas MLODF is the ratio of difference in the power loss in the line i
after an outage in the line m and the normal power loss in the line m to that of maximum power
loss in the line i after an outage. After calculating the distribution factors, maximum loss of each
line is calculated using Eq. (24) and then the loss cost is allocated by using Eq. (17).
mmiimi lineplLOLDFlinepllinefpl _*__ ,, += (22)
mmiimi lineplMLOLDFlinepllinefpl _*__ ,, += (23)
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The possible maximum loss of each line is given as follows:
max,
max,
,2,1,, *|)_||,...._||,_max(|
i
c
i
Iiiiiopt
F
F
linefpllinefpllinefplFl = (24)
3. TEST ON SAMPLE 6 BUS SYSTEM
The feasibility and the efficiency of the proposed method are tested on the sample 6 bus system.
Figure 2. shows the sample 6 bus system. It consists of three generator bus and three load bus.
Table 1. shows the line data details of the 6 bus system.
Figure 2. Sample 6 Bus System.
Table 1. Line data Details of the 6 Bus System
Line R (p.u.) X (p.u.) BL (p.u.)
1-2 0.10 0.20 0.04
1-4 0.05 0.20 0.04
1-5 0.08 0.30 0.06
2-3 0.05 0.25 0.06
2-4 0.05 0.10 0.02
2-5 0.10 0.30 0.04
2-6 0.07 0.20 0.05
3-5 0.12 0.26 0.05
3-6 0.02 0.10 0.02
4-5 0.20 0.40 0.08
5-6 0.10 0.30 0.06
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The contribution of each generator and load is calculated with the help of Modified Kirchhoff
matrix based power flow tracing method. Table 2. shows the total flows in the lines supplied by
the different generators. In the first three lines it is observed that only Gen 1 is supplying power.
Table 3. shows the total power is fully extracted by the different loads. It can be seen that the
power extracted by Load 4 is lower than that of power extracted by loads of the lines 3-5, 3-6
and 5-6. For the line 4-5, entire power is extracted by the Load 6 only. The power flow in the
lines 4-5 and 5-6 are extracted by a single load i.e. Load 4 and Load 5 respectively. For the line
2-3, nearly equal power is extracted by the different loads. Table 4. shows the loss allocation to
different generators.
Table 2. Analysis of Flow to Generators for Sample 6 Bus System
Line
Flow
(MW)
Supplied
by Gen 1
(MW)
Supplied
by Gen 2
(MW)
Supplied
by Gen 3
(MW)
1-2 29.1 29.07 0 0
1-4 43.7 43.66 0 0
1-5 35.6 35.56 0 0
2-3 3 1.12 1.92 0
2-4 33.3 12.4 21.3 0
2-5 15.5 5.77 9.91 0
2-6 26.4 9.83 16.88 0
3-5 19.3 0.34 0.59 18.4
3-6 43.6 0.77 1.32 41.56
4-5 4.2 3.17 1.21 0
5-6 1.7 1.07 0.28 0.44
Table 3. Analysis of Flow to Loads for Sample 6 Bus System
Line
Flow
(MW)
Extracted
by Load 4
(MW)
Extracted
by Load 5
(MW)
Extracted
by Load 6
(MW)
1-2 29.1 14.2 11.77 3.13
1-4 43.7 21.32 17.67 4.71
1-5 35.6 17.36 14.4 3.83
2-3 3 1.21 0.69 1.11
2-4 33.3 13.37 7.61 12.32
2-5 15.5 6.22 3.54 5.74
2-6 26.4 10.6 6.03 9.77
3-5 19.3 0 5.78 13.52
3-6 43.6 0 13.07 30.53
4-5 4.2 3.96 0.23 0.01
5-6 1.7 0 1.66 0.04
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Table 4. Analysis of Loss to Generators for Sample 6 Bus System
Line
Loss
(MW)
Supplied
by Gen 1
(MW)
Supplied
by Gen 2
(MW)
Supplied
by Gen 3
(MW)
1-2 0.22 0.22 0 0
1-4 0.26 0.26 0 0
1-5 0.26 0.26 0 0
2-3 0.01 0 0.01 0
2-4 0.38 0.14 0.24 0
2-5 0.13 0.05 0.08 0
2-6 0.14 0.05 0.09 0
3-5 0.29 0.01 0.01 0.27
3-6 0.25 0 0.01 0.24
4-5 0.01 0.01 0 0
5-6 0.01 0.01 0 0
In the MW-Mile method, charges are calculated based on the MW-Miles of network used by
each user, ignoring the direction of the power flow in the circuit [34]. It is considered that the
cost of the line is based on the impedance of the line. By using Eq. (16), the transmission
embedded cost allocation to each participant is done. Different recovery policies for allocating
the cost are as follows:-
100% cost allocation to all generators.
100% cost allocation to all loads.
50% - 50% cost allocation to all generators and loads.
33% - 67% cost allocation to all generators and loads.
23% - 77% cost allocation to all generators and loads.
In this paper, only two policies i.e. 100% cost allocation to all generators and 100% cost
allocation to all loads is considered. Table 5. and Table 6. show the LODF and MLODF of the
sample 6 bus system.
Table 5. LODF of the Sample 6 Bus system
Line 1 2 3 4 5 6 7 8 9 10 11
1-2 -1.0 0.7 1.3 -0.1 -0.5 -0.2 -0.1 -0.1 0.1 0.0 0.2
1-4 0.6 -1.2 -0.1 0.0 0.6 0.0 0.0 0.0 0.1 -0.4 0.1
1-5 0.4 0.4 -3.8 0.2 -0.1 0.3 0.1 0.2 0.0 0.3 -0.2
2-3 -0.1 0.0 6.8 -1.0 0.2 0.3 4.6 0.1 0.4 0.2 0.2
2-4 -0.6 0.8 -1.6 0.1 -1.0 0.3 0.1 0.2 0.0 -0.7 -0.1
2-5 -0.2 -0.1 1.7 0.2 0.2 -1.0 0.4 0.3 0.0 0.3 -0.3
2-6 -0.1 0.0 0.1 0.5 0.2 0.3 -1.0 -0.2 0.7 0.2 0.4
3-5 -0.1 0.0 0.7 -0.3 0.2 0.3 -0.2 -1.0 0.4 0.2 -0.3
3-6 0.0 0.0 -1.3 -0.6 0.0 0.0 0.4 0.6 -1.0 0.0 0.6
4-5 0.0 0.0 6.6 0.1 0.2 0.2 0.7 0.2 0.0 -1.0 0.0
5-6 0.1 0.0 4.9 0.1 0.0 0.0 5.4 0.2 0.4 -0.2 -1.0
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Table 6. MLODF of the Sample 6 Bus System
Line 1 2 3 4 5 6 7 8 9 10 11
1-2 -1.3 0.5 0.6 0.0 -0.5 -0.1 -0.1 -0.1 0.1 0.0 0.0
1-4 0.8 -0.7 0.5 0.0 0.7 0.0 0.0 0.0 0.0 0.0 0.0
1-5 0.5 0.3 -0.9 0.0 -0.1 0.1 0.1 0.1 0.0 0.0 0.0
2-3 -0.1 0.0 0.2 -0.1 0.2 0.1 0.3 0.1 0.3 0.0 0.0
2-4 -0.7 0.6 -0.2 0.0 -1.1 0.2 0.1 0.1 0.0 -0.1 0.0
2-5 -0.2 -0.1 0.3 0.0 0.3 -0.6 0.2 0.2 0.0 0.0 0.0
2-6 -0.1 0.0 0.2 0.1 0.2 0.2 -0.6 -0.1 0.5 0.0 0.0
3-5 -0.1 0.0 0.2 0.0 0.2 0.2 -0.1 -0.6 0.3 0.0 0.0
3-6 0.0 0.0 0.0 -0.1 0.0 0.0 0.4 0.3 -0.7 0.0 0.0
4-5 0.0 0.0 0.3 0.0 0.2 0.1 0.1 0.1 0.0 -0.1 0.0
5-6 0.1 0.0 0.1 0.0 0.0 0.0 0.2 0.1 0.3 0.0 0.0
Table 7. and Table 8. show the cost allocation to each generator and load under contingency
condition due to LODF and MLODF respectively. Figure 3. and Figure 4. show the total cost
allocation to generator and load due to both distribution factors respectively. It is clear that the
cost allocation is more in case of MLODF in each line.
Table 7. Analysis of Cost Allocation to Different Generators
Line Cost Allocated due to
LODF ($/hr)
Cost Allocated due to
MLODF ($/hr)
G1 G2 G3 G1 G2 G3
1-2 87.98 0 0 128.07 0 0
1-4 140.4 0 0 135.66 0 0
1-5 204.0 0 0 216.30 0 0
2-3 1.157 1.9844 0 17.197 29.481 0
2-4 20.17 34.663 0 24.021 41.262 0
2-5 23.96 41.164 0 68.485 117.623 0
2-6 37.32 64.100 0 43.057 73.938 0
3-5 2.263 3.9286 122.51 2.8868 5.0094 156.2
3-6 1.285 2.2031 69.366 1.4306 2.4526 77.22
4-5 5.954 2.2727 0 103.9 39.663 0
5-6 1.9173 0.501748 0.7884 22.109 5.7856 9.0917
Total 526.53 150.820 192.67 763.14 315.217 242.53
Figure 3. Total cost allocation to generator due to LODF and MLODF
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Table 8. Analysis of Cost Allocation to Different Loads
Line Cost Allocated due to
LODF ($/hr)
Cost Allocated due to
MLODF ($/hr)
L4 L5 L6 L4 L5 L6
1-2 42.371 36.318 9.080 61.680 52.868 13.217
1-4 67.541 57.892 16.081 65.256 55.934 15.537
1-5 97.566 80.349 22.957 103.40 85.160 24.331
2-3 1.034 1.034 1.034 15.355 15.355 15.355
2-4 21.156 13.019 19.528 25.183 15.497 23.246
2-5 24.923 16.615 24.923 71.216 47.477 71.216
2-6 41.772 22.785 37.975 48.183 26.282 43.803
3-5 0.000 39.952 93.222 0.000 50.944 118.87
3-6 0.000 21.698 51.741 0.000 24.154 57.599
4-5 7.513 0.000 0.000 131.12 0.000 0.000
5-6 0.000 3.584 0.000 0.000 41.327 0.000
Total 303.87 293.24 276.54 521.400 414.999 383.174
Figure 4. Total cost allocation to load due to LODF and MLODF.
Table 9. Analysis of Loss Cost Allocation to Different Generators
Line Loss Cost Allocated
due to LODF ($/hr)
Loss Cost Allocated
due to MLODF ($/hr)
G1 G2 G3 G1 G2 G3
1-2 0.883 0.000 0.000 3.444 0.000 0.000
1-4 0.893 0.000 0.000 3.354 0.000 0.000
1-5 2.457 0.000 0.000 5.105 0.000 0.000
2-3 0.000 0.892 0.000 0.000 0.000 0.000
2-4 0.243 0.417 0.000 0.678 1.162 0.000
2-5 0.922 1.476 0.000 1.826 2.922 0.000
2-6 0.148 0.267 0.000 1.156 2.081 0.000
3-5 0.077 0.077 2.082 0.165 0.165 4.461
3-6 0.000 0.040 0.952 0.000 0.065 1.555
4-5 0.522 0.000 0.000 0.000 0.000 0.000
5-6 0.316 0.000 0.000 2.095 0.000 0.000
Total 6.462 3.169 3.033 17.823 6.395 6.016
13. Electrical & Computer Engineering: An International Journal (ECIJ) Volume 3, Number 2, June 2014
37
Figure 5. Total loss cost allocation to generator due to LOLDF and MLOLDF.
Table 9. shows the loss cost allocation to each generator under contingency condition due to
LOLDF and MLOLDF. Figure 5. shows the total loss cost allocation to generator due to both
distribution factors.
4. CONCLUSION
In this paper, authors have presented a combined methodology for the transmission
usage cost and loss allocation. Modified Matrix methodology [7] is used to trace the
power flow to different loads. MW-Mile method is used to allocate the cost. The
calculation of pline and distribution factors are time taking. Moreover, it is
demonstrated that the proposed method is more accurate and feasible. It is clear that the
transmission usage cost allocation and loss allocation considering MLODF and
MLOLDF is more as compared to LODF and LOLDF as observed from Fig 2, Fig 3 and
Fig 4. Results are shown for the sample 6 bus system.
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Authors
Pawan Rathore was born in Balco Town, Korba City, Chhattisgarh State, India in
1990. He received the B.E. degree in Electrical and Electronics engineering from
Chhattisgarh Swami Vivekananda Technical University, Bhilai in 2012. Currently,
he is pursuing M.Tech from Maulana Azad National Institute of Technology,
Bhopal. His research interests include power system optimization, congestion
management, transmission pricing and application of artificial intelligence
techniques in power system.
Garima Naidu was born in Bhopal, Madhya Pradesh State, India in 1989. She
received her B.Tech degree in Electrical and Electronics engineering from Vellore
Institute of Technology, Vellore, Tamil Nadu in 2012. Currently, she is pursuing
M.Tech from Maulana Azad National Institute of Technology, Bhopal. Her
research interests include power system optimization, FACTS devices, and
application of artificial intelligence techniques in power system.
Ganga Agnihotri received BE degree in Electrical engineering from MACT,
Bhopal (1972), the ME degree (1974) and PhD degree (1989) from University of
Roorkee, India. Since 1976 she is with Maulana Azad College of Technology,
Bhopal in various positions. Currently she is professor. Her research interest
includes Power System Analysis, Power System Optimization and Distribution
Operation.
Baseem Khan was born in Gwalior, India in 1987. He received BE degree (2008)
from Maharana Pratap College of Technology Gwalior and received an M.Tech.
degree (2010) in Power System from MANIT Bhopal. At the moment he is a
research scholar at MANIT Bhopal, India. His research interests include power
system optimization, congestion management, transmission pricing and application
of artificial intelligence techniques in power system.