An optimal pricing scheme in electricity markets by parallelizing security constrained optimal power flow based market-clearing model

Kim, M.K.; Hur, Don

doi:10.1016/j.ijepes.2012.05.047

Cited by 17 publications

(9 citation statements)

References 21 publications

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“…The continuation method is used as a tool for voltage security studies in [25]. In this work, the VSM is applied to measure the voltage stability, and the load is assumed to be of the constant-power type.…”

Section: Stability Marginmentioning

confidence: 99%

“…These should be minimized to relieve the congestion while also keeping their values as low as possible. LMPs are commonly associated with both the bidding costs and the dual variables (Lagrange multipliers) of the power flow equation [25]. The Lagrange multiplier is the shadow price for the load flow constraints of the OPF, and it describes each congested transmission line on the network.…”

Section: Price Analysismentioning

confidence: 99%

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Multi-Objective Optimization of Voltage-Stability Based on Congestion Management for Integrating Wind Power into the Electricity Market

Choi

Kim

2017

Applied Sciences

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This paper proposes voltage-stability based on congestion management (CM) for electricity market environments and considers the incorporation of wind farms into systems as well. A probabilistic voltage-stability constrained optimal power flow (P-VSCOPF) is formulated to maximize both social welfare and voltage stability. To reflect the probabilistic influence of CM in the presence of wind farms on voltage stability, Monte Carlo simulations (MCS) are used to analyze both the system load and the wind speed from their probability distribution functions. A multi-objective particle-swarm optimization (MOPSO) algorithm is implemented to solve the P-VSCOPF problem. A contingency analysis based on the voltage stability index (VSI) for line outages is employed to find the vulnerable line of congestion in power systems. The congestion distribution factor (CDF) is also used to find the optimal location of a wind farm in CM. The optimal pricing expression, which is obtained, with respect to preserving voltage stability, by calculating both the locational marginal prices (LMPs) and the nodal congestion prices (NCPs), is demonstrated in terms of congestion solutions. Simultaneously, the voltage stability margin (VSM) is considered within the CM framework. The proposed approach is implemented on a modified IEEE 24-bus system, and the results obtained are compared with the results of other optimal power flow methods.

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Section: Stability Marginmentioning

confidence: 99%

Section: Price Analysismentioning

confidence: 99%

Multi-Objective Optimization of Voltage-Stability Based on Congestion Management for Integrating Wind Power into the Electricity Market

Choi

Kim

2017

Applied Sciences

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“…For daily seasonality, in addition to can also be considered, and similarly for other periods. In (14), the first four terms consist of information about the trends in the signal. The next six terms contain information about daily seasonality (up to 2 days ago), while the latter twelve terms are related to weekly seasonality (1-4 weeks ago).…”

Section: Lmp Forecastingmentioning

confidence: 99%

“…Price volatility is crucial to calculate average annual prices and to derive bilateral contract prices for them. Obviously, a more accurate forecasting model can be helpful to generating companies in submitting accurate bids with low risk and, if necessary, to make good bilateral contracts [14]. In recent years, several methods have been used to predict prices in electricity markets.…”

Section: Introductionmentioning

confidence: 99%

A New Approach to Short-term Price Forecast Strategy with an Artificial Neural Network Approach: Application to the Nord Pool

Kim¹

2015

Journal of Electrical Engineering and Technology

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-In new deregulated electricity market, short-term price forecasting is key information for all market players. A better forecast of market-clearing price (MCP) helps market participants to strategically set up their bidding strategies for energy markets in the short-term. This paper presents a new prediction strategy to improve the need for more accurate short-term price forecasting tool at spot market using an artificial neural networks (ANNs). To build the forecasting ANN model, a threelayered feedforward neural network trained by the improved Levenberg-marquardt (LM) algorithm is used to forecast the locational marginal prices (LMPs). To accurately predict LMPs, actual power generation and load are considered as the input sets, and then the difference is used to predict price differences in the spot market. The proposed ANN model generalizes the relationship between the LMP in each area and the unconstrained MCP during the same period of time. The LMP calculation is iterated so that the capacity between the areas is maximized and the mechanism itself helps to relieve grid congestion. The addition of flow between the areas gives the LMPs a new equilibrium point, which is balanced when taking the transfer capacity into account, LMP forecasting is then possible.The proposed forecasting strategy is tested on the spot market of the Nord Pool. The validity, the efficiency, and effectiveness of the proposed approach are shown by comparing with time-series models

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“…In [7] has proposed of DC SCOPF approximation to improve iterative AC SCOPF Algorithms. A novel approach to pricing the system security by paralleliz ing the security constrained optimal power flow (SCOPF) based market clearing model is presented in [8].…”

Section: Introductionmentioning

confidence: 99%

Improving the transient stability-constrained optimal power flow with Thyristor Controlled Series Compensators

Duong

Yao

Truong³

2014

Russ. Electr. Engin.

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Due to the rapid increase of electricity demand and the deregulation of electricity markets, power systems tend to operate closer to stability boundaries. The scheme of preventive control should bring in a tradeoff between economics and security, which are often the two major inconsistent requirements for the daily operation of many power systems in the world. Optimal power flow (OPF) is a powerful tool to weaken the conflict between economy and security, but the main obstacle faced is that, the complexity involved for OPF with transient stability constraints is several orders of magnitude higher than that of conventional OPF with merely static constraints. Therefore, consideration of Transient Stability Constraints in Optimal Power Flow (OPF) problems is becoming more and more imperative. FACTS devices such as Thyristor Controlled Series Compensator (TCSC) can be very effective to power system security in case of a contingency. In this paper, we concentrate on the improving transient stability constrained optimal power flow to against single contingencies via the use of TCSC. Study results on IEEE 30 bus system have proved the effectiveness of using TCSC to improve transient stability constrained optimal power flow (TSCOPF).

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An optimal pricing scheme in electricity markets by parallelizing security constrained optimal power flow based market-clearing model

Cited by 17 publications

References 21 publications

Multi-Objective Optimization of Voltage-Stability Based on Congestion Management for Integrating Wind Power into the Electricity Market

Multi-Objective Optimization of Voltage-Stability Based on Congestion Management for Integrating Wind Power into the Electricity Market

A New Approach to Short-term Price Forecast Strategy with an Artificial Neural Network Approach: Application to the Nord Pool

Improving the transient stability-constrained optimal power flow with Thyristor Controlled Series Compensators

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