$Z_{\rm bus}$ Transmission Network Cost Allocation

Conejo, Antonio J.; Contreras, Javier; Lima, Delberis A.; Padilha‐Feltrin, Antonio

doi:10.1109/tpwrs.2006.889138

Cited by 132 publications

(106 citation statements)

References 9 publications

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“…However, the increasing penetration of DER at distribution level forces the need to adapt traditional cost allocation methods used in transmission system to the distribution level. In general, the cost allocation methods for transmission systems may be classified into three distinct categories: nodal marginal methods [3][4][5][6][7]; rolled-in methods [8][9][10][11]; embeddedmethods [12][13][14][15][16][17][18][19][20][21][22][23][24]. The cost allocation based on nodal marginal pricing for transmission systems is presented in [3][4][5], in which are considered the long-term and short-term marginal costs related to energy, reliability, investments and demand side.…”

Section: Literature Review and Specific Contributionsmentioning

confidence: 99%

“…The Zbus method is based on circuit theory and it can determine how an injection of power of a given resource uses the network. Thus, it is possible to allocate the costs of network usage to the energy resources [20]. Others embedded cost allocation methods such as the generalized distribution factors [15], Bialek's [21], and Kirschen's [22] tracing algorithms are based on the definition of distribution factors in order to know the share that each user has in the network.…”

Section: Literature Review and Specific Contributionsmentioning

confidence: 99%

“…Demand reduction (13) and curtailment (14) through direct load control of demand response. Vehicle-to-grid resources will be an important resource in future distribution systems, but it increases the complexity of the problem (15)- (20). In this way, is essential to optimize the amount of energy stored (15) at the end of each period in each V2G.…”

Section: First Step -Energy Resources Scheduling and Locational Margimentioning

confidence: 99%

“…Charge and discharge energy for each V2G cannot occur at same time, so non-simultaneity of charge and discharge (20) is ensured. Technical constraints for energy storage systems (20)- (26) follow the same principle of constraints regarding V2G resources. The main difference between both resources is that energy stored systems does not need reserve energy for travel, since they are not vehicles.…”

Section: First Step -Energy Resources Scheduling and Locational Margimentioning

confidence: 99%

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Cost allocation model for distribution networks considering high penetration of distributed energy resources

Soares

Pereira

Morais

et al. 2015

Electric Power Systems Research

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a b s t r a c tThe high penetration of distributed energy resources (DER) in distribution networks and the competitive environment of electricity markets impose the use of new approaches in several domains. The network cost allocation, traditionally used in transmission networks, should be adapted and used in the distribution networks considering the specifications of the connected resources. The main goal is to develop a fairer methodology trying to distribute the distribution network use costs to all players which are using the network in each period. In this paper, a model considering different type of costs (fixed, losses, and congestion costs) is proposed comprising the use of a large set of DER, namely distributed generation (DG), demand response (DR) of direct load control type, energy storage systems (ESS), and electric vehicles with capability of discharging energy to the network, which is known as vehicle-to-grid (V2G). The proposed model includes three distinct phases of operation. The first phase of the model consists in an economic dispatch based on an AC optimal power flow (AC-OPF); in the second phase Kirschen's and Bialek's tracing algorithms are used and compared to evaluate the impact of each resource in the network. Finally, the MW-mile method is used in the third phase of the proposed model. A distribution network of 33 buses with large penetration of DER is used to illustrate the application of the proposed model.

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Section: Literature Review and Specific Contributionsmentioning

confidence: 99%

Section: Literature Review and Specific Contributionsmentioning

confidence: 99%

Section: First Step -Energy Resources Scheduling and Locational Margimentioning

confidence: 99%

Section: First Step -Energy Resources Scheduling and Locational Margimentioning

confidence: 99%

See 2 more Smart Citations

Cost allocation model for distribution networks considering high penetration of distributed energy resources

Soares

Pereira

Morais

et al. 2015

Electric Power Systems Research

View full text Add to dashboard Cite

show abstract

“…But this method uses dc power flow solution. A methodology based on circuit theory [6] uses thecontributions of the nodal currents to line power flows to apportion the usage of the lines.…”

Section: Iintroductionmentioning

confidence: 99%

Development of TIF for Transaction Cost Allocation in Deregulated Power System

Reddy¹,

Kumar²

2014

International Journal of Innovative Research in Electrical, Ele

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Abstract:In deregulated power system due to the increase of power transactions in transmission open access the transmission cost allocation is one of the major problems. For each transaction the Transaction Impact Factors (TIFs) are developed for the allocation of the transmission transaction costs. The transmission Impact Factor gives the information about the real power flow in the transmission lines with the transacted power. This logical method provides the impact of the line flows without running power flow solutions when the amount of transacted power changes in real time. This proposed method is evaluated by considering bilateral and multilateral transactions. The results coming from the proposed method is compared with Megawatt Modulus (MM) method on sample six bus and IEEE 30 bus system.

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Performance analysis of hybrid techniques for evaluation of power transmission cost and loss allocation based on transmission reliability margin

Shaik

Lalitha

Visali

2021

Int Trans Electr Energ Syst

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Summary The cost allotment of the transmission system is based on reliability, which is a significant problem for efficient transmission cost allotment. In this paper, a hybrid technique is suggested to allocate and minimize the embedded cost of transmission based on the reliability margin by permitting its users for the transactions under the Deregulated power system market. The hybrid technique combines the Elephant Herd Optimization (EHO) algorithm and the Fuzzy Logic Controller (FLC). The Elephant Heard Optimization algorithmic program is impressed by the swarming activities of elephant grouping. The FLC is utilized to boost the performance of the Elephant Heard Optimization Method. Initially, the Optimal Power flow is analyzed using the Newton‐Raphson (N‐R) approach. The objective function is to define and analyze the power loss, capacity cost, Expected Transmission Margin Unit (ETMU), reliability cost, and embedded cost for the base case. After that, the transmission system's contingency and analysis of the embedded cost and power loss are analyzed. The outcomes of the suggested method are analyzed with cases such as contingency, transactions. The suggested technique is tested with the IEEE 5 and IEEE 24 Reliability Test System bus system and analyzed the corresponding capacity cost, reliability cost, ETMU, Embedded cost, and Power loss of the system. The suggested method is implemented in MATLAB software. Results are validated with the traditional methods, namely Bat Algorithm (Bat) and Firefly Algorithm (FA).

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$Z_{\rm bus}$ Transmission Network Cost Allocation

Cited by 132 publications

References 9 publications

Cost allocation model for distribution networks considering high penetration of distributed energy resources

Cost allocation model for distribution networks considering high penetration of distributed energy resources

Development of TIF for Transaction Cost Allocation in Deregulated Power System

Performance analysis of hybrid techniques for evaluation of power transmission cost and loss allocation based on transmission reliability margin

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