• 대한전기학회논문지:전력기술부문A
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• 제55권3호
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• pp.128-132
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• 2006

Interstate electric power system, as an alternative for energy cooperation under regional economic bloc, has been hotly debated before progressing the restructure in electric power industry and rapidly expanded in many regions after 1990s. Especially, since northeast asia has strong supplementation in resource, load shape, fuel mix etc., electric power system interconnection in this region may bring considerable economic benefits. Moreover, since Korean electric power system has a great difficulty in a geographical condition to interrupt electricity transaction with other countries, it has been expanded as an independent system to supply all demand domestically. As a result, Korean electric power system makes considerable payment for maintaining system security and reliability and expands costly facilities to supply a temporary summer peak demand. Under this inefficiency, if there are electricity transactions with Russia via the North Korea route then economic electric power system operation nay be achieved using seasonal and hourly differences in electricity price and/or load pattern among these countries. In this paper, we estimate price cap of transacted electricity via interstate electric power system in northeast asia. For this study, we perform quantitative economic analysis on various system interconnection scenarios.

• KIEE International Transactions on Power Engineering
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• 제5A권4호
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• pp.403-411
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• 2005

At present, the Cournot model is one of the most commonly used theories to analyze the gaming situation in an oligopoly type market. However, several problems exist in the successful application of this model to the electricity market. The representative one is obtaining the inverse demand curve able to be induced from the relationship between market price and demand response. In the Cournot model, each player offers their generation quantity to obtain maximum profit, which is accomplished by reducing their quantity compared with available total capacity. As stated above, to obtain the probable Cournot equilibrium to reflect the real market situation, we have to induce the correct demand function first of all. Usually the correlation between price and demand appears over the long-term through statistical data analysis (for example, regression analysis) or by investigating consumer utility functions of several consumer groups classified as residential, industrial, and commercial. However, the elasticity has a tendency to change continuously according to the total market demand size or the level of market price. Therefore it should be updated as the trading period passes by. In this paper we propose a method for inducing and updating this price elasticity of demand function for more realistic market equilibrium.

• 설비공학논문집
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• 제20권5호
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• pp.321-326
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• 2008

This paper presents and analyzes the effects of on-grid electricity cost, fuel price and initial capital cost of a CHP system, on the optimum DG and AC capacity and NPV, by using the ORNL CHP Capacity Optimizer, which was applied to a library in a university. By considering the current domestic energy cost and initial capital cost, it is shown that the installation and operation of the CHP system is not economical. However, with the current domestic CHP installation cost and fuel price, the NPV achieved by the installation of CHP system is greater when the on-grid electricity price is a factor of ${\times}1.5$ the present value. Regarding the initial capital cost of the CHP system, the reduction of the DG cost is much more economical than that of the AC cost, with respect to NPV. Electricity cost and fuel price have opposite effects on NPV, and NPV is more sensitive to an increase of the electricity cost than an increase of the fuel price.

• 대한전기학회논문지:전력기술부문A
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• 제52권6호
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• pp.333-339
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• 2003

Competition among electric generation companies is a major goal of restructuring in the electricity industry. In electricity market, a huge volume of commodities will be traded through competitive bidding. The choice between uniform and pay-as-bid pricing for electricity auction has been one of most important issues in deregulated electricity market. This paper proposes a constrained Bertrand model for analyzing the electricity auction market of price competition model. The issue of the two pricing rules of uniform and pay-as-bid is studied from the viewpoint of consumer's benefit. This paper also shows that transmission congestion depends on the pricing mechanism. Pay-as-bid pricing gives less possibility of transmission congestion by price competition, and less burden to consumers in the simulation results.

• 자원ㆍ환경경제연구
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• 제23권1호
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• pp.43-65
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• 2014

본 논문에서는 국내 제조업 가운데 전력 사용량이 상대적으로 많은 화합물 및 화학제품 산업을 대상으로 암묵 (shadow) 비용함수를 사용하여 전력 등의 투입요소 간 효율적 배분 여부를 검증하고 전력의 적정수준 대비 과잉 투입 규모를 조사한다. 기업의 비용최소화 달성을 전제로 각 투입요소에 대한 수요의 가격탄력성을 추정하여 전력요금 인상에 대한 각 요소 수요의 파급효과를 모의실험을 통하여 분석한다. 또한 공급관계식을 비용함수의 방정식체계에 추가하여 동시 추정함으로써 전력요금 10% 인상 시 물가지수에 미치는 영향을 분석한다. 실증분석 결과, 1982-2006년 기간 동안 '투입요소 간 효율적 배분 달성'의 귀무가설은 기각되었으며, 전력은 적정수준 대비 평균적으로 매년 약 98% 과잉 사용되고 있는 것으로 나타났다. 다른 요인들이 불변하다면 전력요금이 10% 인상될 경우 전력 수요는 약 11.4% 감소하였으며, 공급가격은 평균적으로 0.08% 하락하는 것으로 나타났다.

• Journal of Electrical Engineering and Technology
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• 제8권6호
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• pp.1251-1260
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• 2013

This paper presents the optimal scheduling of hourly consumption in a residential community (community, neighborhood, etc.) based on real-time electricity price. The residential community encompasses individual residential loads, communal (shared) loads, and local generation. Community-aggregated loads, which include residential and communal loads, are modeled as fixed, adjustable, shiftable, and storage loads. The objective of the optimal load scheduling problem is to minimize the community-aggregated electricity payment considering the convenience of individual residents and hourly community load characteristics. Limitations are included on the hourly utility load (defined as community-aggregated load minus the local generation) that is imported from the utility grid. Lagrangian relaxation (LR) is applied to decouple the utility constraint and provide tractable subproblems. The decomposed subproblems are formulated as mixed-integer programming (MIP) problems. The proposed model would be used by community master controllers to optimize the utility load schedule and minimize the community-aggregated electricity payment. Illustrative optimal load scheduling examples of a single resident as well as an aggregated community including 200 residents are presented to show the efficiency of the proposed method based on real-time electricity price.

• 전기학회논문지
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• 제58권3호
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• pp.455-461
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• 2009

This paper proposes Direct Load Control(DLC) operation scheme using a bidding system and the methodology to value proper quantity decided by the DLC program, which is a kind of resources for stabilization of electricity market price during peak times by managing consumer electricity demand. Since DLC program in Korea is based on the contract with the customers participating in this program, it is difficult to anticipate voluntary participation. That is, incentive for participants in DLC program is insufficient. To cope with this point, it is necessary to develop a new market mechanism and market compatible operation scheme for DLC programs. DLC market mechanism is deemed to be equipped with iterative bidding system, independent operation from energy market, and interactive with bidding information on energy market. With this market mechanism, it is important to find the optimal operation point of DLC allowing for the factors of stabilizing the electricity market price and compensating DLC implementation. This paper focuses on the mathematical approaches for the bid-based DLC operation scheme and examines several scenarios for the following technical justifications: 1) stabilization of electricity market price during peak times, 2) elasticity of demand.

• KIEE International Transactions on Power Engineering
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• 제5A권4호
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• pp.331-338
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• 2005

In this paper, an improved maintenance scheduling approach suitable for the competitive environment is proposed by taking account of profits and costs of generation companies and the formulated combinatorial optimization problem is solved by using Reactive Tabu search (RTS). In competitive power markets, electricity prices are determined by the balance between demand and supply through electric power exchanges or by bilateral contracts. Therefore, in decision makings, it is essential for system operation planners and market participants to take the volatility of electricity price into consideration. In the proposed maintenance scheduling approach, firstly, electricity prices over the targeted period are forecasted based on Artificial Neural Network (ANN) and also a newly proposed aggregated bidding curve. Secondary, the maintenance scheduling is formulated as a combinatorial optimization problem with a novel objective function by which the most profitable maintenance schedule would be attained. As an objective function, Opportunity Loss by Maintenance (OLM) is adopted to maximize the profit of generation companies (GENCOS). Thirdly, the combinatorial optimization maintenance scheduling problem is solved by using Reactive Tabu Search in the light of the objective functions and forecasted electricity prices. Finally, the proposed maintenance scheduling is applied to a practical test power system to verify the advantages and practicability of the proposed method.

• 대한산업공학회지
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• 제39권6호
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• pp.562-576
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• 2013

Power TAC (Power Trading Agent Competition) is an agent-based simulation for competitions between electricity brokering agents on the smart grid. To win the competition, agents obtain electricity from the electricity wholesale market among the power plants. In this operation, a key to success is balancing the demand of the customer and the supply from the plants because any imbalance results in a significant penalty to the brokering agent. Given the bidding on the wholesale market requires the price and the quantity on the electricity, this paper proposes four different price estimation strategies: exponentially moving average, linear regression, fuzzy logic, and support vector regression. Our evaluations with the competition simulation show which strategy is better than which, and which strategy wins in the free-for-all situations. This result is a crucial component in designing an electricity brokering agent in both Power TAC and the real world.

• 청정기술
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• 제28권2호
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• pp.138-146
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• 2022

Electricity has become a factor that dramatically affects the market economy. The day-ahead system marginal price determines electricity prices, and system marginal price forecasting is critical in maintaining energy management systems. There have been several studies using mathematics and machine learning models to forecast the system marginal price, but few studies have been conducted to develop, compare, and analyze various machine learning and deep learning models based on a data-driven framework. Therefore, in this study, different machine learning algorithms (i.e., autoregressive-based models such as the autoregressive integrated moving average model) and deep learning networks (i.e., recurrent neural network-based models such as the long short-term memory and gated recurrent unit model) are considered and integrated evaluation metrics including a forecasting test and information criteria are proposed to discern the optimal forecasting model. A case study of South Korea using long-term time-series system marginal price data from 2016 to 2021 was applied to the developed framework. The results of the study indicate that the autoregressive integrated moving average model (R-squared score: 0.97) and the gated recurrent unit model (R-squared score: 0.94) are appropriate for system marginal price forecasting. This study is expected to contribute significantly to energy management systems and the suggested framework can be explicitly applied for renewable energy networks.