Evaluations of bilateral transactions in electricity markets in aspects of optimal dispatch and transmission pricing

Ruangchom, N.; Damrongkulkamjorn, P.

doi:10.1109/ecticon.2008.4600591

Cited by 7 publications

(4 citation statements)

References 14 publications

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“…An approach has been adopted by Gil et al in 2006 to create a nodal price difference by introducing the generation and the nodal injection penalties in economic dispatch for the allocation of the transmission network cost [9]. In another study, it has been evaluated that the transmission pricing for the market participants also deals with the bilateral transaction in electricity market taking into account the optimal dispatch and the transmission pricing using optimal power flow [10]. Reta et al developed a logarithmic function to evaluate the transmission system cost recovery in ideal and real power systems [11].…”

Section: A Nodal Pricing Approachmentioning

confidence: 99%

Power System Transmission Pricing-A Review

Paul¹,

Kumar²

2016

IJERT

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Restructuring in the power supply industries has given rise to a competitive electricity market. The allocation of the transmission cost is a vital issue in this power market. The transmission pricing should be economical, transparent, efficient and ensure the reliable operation of the electricity market. This paper puts forward the review of different transmission pricing techniques and methods. The transmission cost allocation by nodal pricing and power flow tracing techniques along with the congestion management, optimization techniques and the transmission loss allocation constitute the body of this paper.

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Section: A Nodal Pricing Approachmentioning

confidence: 99%

Power System Transmission Pricing-A Review

Paul¹,

Kumar²

2016

IJERT

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“…Locational marginal pricing is a market-pricing approach used to manage the efficient use of the transmission system when congestion occurs on the bulk power grid [2], [4], [6], [8], [16], [17].…”

Section: A Opf -Economic Dispatchmentioning

confidence: 99%

“…In electricity markets, LMP are required because this marginal price may vary at different times and locations based on transmission congestion [4].…”

Section: Introductionmentioning

confidence: 99%

Nodal price simulation in competitive electricity markets

Ferreira

Vale

Puga

2009

2009 6th International Conference on the European Energy Market

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Locational Marginal Prices (LMP) are important pricing signals for the participants of competitive electricity markets, as the effects of transmission losses and binding constraints are embedded in LMPs [1],[2].This paper presents a software tool that evaluates the nodal marginal prices considering losses and congestion. The initial dispatch is based on all the electricity transactions negotiated in the pool and in bilateral contracts. It must be checked if the proposed initial dispatch leads to congestion problems; if a congestion situation is detected, it must be solved.An AC power flow is used to verify if there are congestion situations in the initial dispatch. Whenever congestion situations are detected, they are solved and a feasible dispatch (re-dispatch) is obtained. After solving the congestion problems, the simulator evaluates LMP.The paper presents a case study based on the the 118 IEEE bus test network.

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“…ere are, however, formulations that do not fit exactly into the groups listed in [3]. ese methods are based on nodal impedance matrix [11,12]; bilateral equivalent injections [13][14][15][16][17]; cooperative game theory [18][19][20][21][22][23][24]; Aumann-Shapley theory [25,26]; transmission security margin [27]. Comparative studies are presented in [28][29][30].…”

Section: Introductionmentioning

confidence: 99%

Toward a New Nodal Pricing Policy of the Brazilian Transmission System Considering Multiple Hydrological Scenarios

Dornellas

Silva

Costa

et al. 2022

International Transactions on Electrical Energy Systems

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This paper presents a new method for allocating transmission system costs in hydro prevailing energy markets. The proposed approach is based on nodal pricing, and it considers multiple hydrological scenarios obtained from optimized energy models. These models are much closer to the operational reality of hydro dominant systems and more adequate to the transmission operation planning. The nodal pricing strategy comprises two steps to recover the total costs of the transmission system. The first one calculates the charges corresponding to the utilized network capacity, estimated at a specified operating condition, and it brings the locational signal to the tariff. In the second step, the charges related to the transmission capacity available but not used in the system are assessed by a postage stamp. This latter step accomplishes the task of recovering the total transmission charges and defining the final tariff for specific operating dispatching. On the other hand, the optimized energy models, based on stochastic dual dynamic programming, are used to minimize the operating costs while penalizing possible energy spillages. These models create monthly sequences of hydrothermal coordinated generating scenarios and dispatching conditions, which are used by the nodal pricing strategy to produce the generation/load charges and tariffs and the corresponding statistics. The proposed method, combining the nodal pricing strategy and the optimized energy model, is applied to a Brazilian network configuration and the results are fully discussed. Moreover, probabilistic analyses are also performed to describe the annual costs of transmission of thermoelectric and hydroelectric plants and industrial electrointensive consumers installed in different areas of the network.

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Evaluations of bilateral transactions in electricity markets in aspects of optimal dispatch and transmission pricing

Cited by 7 publications

References 14 publications

Power System Transmission Pricing-A Review

Power System Transmission Pricing-A Review

Nodal price simulation in competitive electricity markets

Toward a New Nodal Pricing Policy of the Brazilian Transmission System Considering Multiple Hydrological Scenarios

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