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Many countries are increasing their investments in smart grid technology to enhance energy efficiency, address climate change, and trigger a green energy revolution. In addition to these goals, Korea also seeks to promote national competitiveness, prepare for the growth of the renewable energy industry, and export industrialization through its strategic promotion of the smart grid. Given its inherent representativeness for Korean implementation of the smart grid and its growth potential, Jeju Island was selected by the Korean government as the site for smart grid testing in June 2009. This paper presents a new design for the electricity market and an operational scheme for testing Smart Electricity Services in the Jeju smart grid demonstration project. The Jeju smart grid test-bed electricity market is constructed on the basis of day-ahead and real-time markets to provide two-way electricity transaction environments. The experience of the test-bed market operation shows that the competitive electricity market can facilitate the smart grid deployment in Korea by allowing various demand side resources to be active market players.

This paper tries to elicit an optimal generation mix of Korea. Two approaches, using the screening curve method and taking advantage of a generation expansion planning tool, WASP-IV, are applied in getting the mix. The data used in this study is based on the 5th basic plan for long-term electricity supply and demand. The Load Duration Curve, that is needed for applying Screening Curve Method(SCM), is made based on the load profile in 2010. In our using SCM, the nuclear plant’s operation characteristic, carbon emission cost and spinning reserve are considered. In using WASP-IV to get the adequate generation mix, the base and target demand forecasts in the 5th basic plan are used and the carbon emission cost is also considered. In this paper, It introduces the domestic adequacy generation mix in 2024 though SCM and WASP-IV. Key Words : Generation Mix, Carbon Emission Cost, Screening Curve Method, WASP-IV*정 회 원 : 건국대 공대 전기공학과 박사과정**정 회 원 : 건국대 공대 전기공학과 교수†교신저자, 정회원 : 건국대 전기공학과 교수E-mail : jhroh@konkuk.ac.kr 접수일자 : 2012년 2월 13일 최종완료 : 2012년 3월 15일

When the RPS(Renewable Portfolio Standards) becomes effective in 2012, the use of renewable energy will be dramatically increased. However, there are no production simulations and demand supply programs that reflect the characteristics of the renewable energy. This paper analyzes correlations of the domestic wind power and solar power generation pattern in different areas and those of these sources` output and load pattern. Based on the regional correlation analysis, an appropriate method that uses a average output of the renewable energy or another modeling that takes account of uncertainty could be selected. Because it`s output is dependent on weather condition, we can not control the generation of renewable energy, that is the reason why the correlation between the load and output pattern of sources can be helpful to determine whether the renewable energy is modeled as a generator or load modifier. Through this analysis, a basis will be provided in order to properly model the renewable energy source.

In the power system with an electric storage system that can increase utilization rate of the source of such new renewable energy, this paper introduces the approach on the daily unit commitment scheduling that determines simultaneously optimum operational condition and output of thermal generators and electric storage device. The unit commitment is one of the most important issues in economic operation and security of short-term operational plan of the power system. It is to determine on/off status of generator to minimize operational cost during the given period. The committed generator should satisfy various operational limitation such as estimated demand by system, spinning reserve condition within minimum operational cost. In order to determine on/off or charge/discharge/idle condition and output level of units and electric storage system, the MILP(Mixed Integer Linear Programming) is suggested. The proposed approach is the mixed method between LP(Linear Programming) and IP(integer programming) which seeks the value of real number and integer that maximize or minimize function objective within given condition. The daily unit commitment problem with the electric storage system is applied to MILP algorithm through linearization and formulation process. The proposed approach is applied to the test system.

This paper proposes a novel binary ant colony optimization (NBACO) method. The proposed NBACO is based on the concept and principles of ant colony optimization (ACO), and developed to solve the binary and combinatorial optimization problems. The concept of conventional ACO is similar to Heuristic Dynamic Programming. Thereby ACO has the merit that it can consider all possible solution sets, but also has the demerit that it may need a big memory space and a long execution time to solve a large problem. To reduce this demerit, the NBACO adopts the state probability matrix and the pheromone intensity matrix. And the NBACO presents new updating rule for local and global search. The proposed NBACO is applied to test power systems of up to 100-unit along with 24-hour load demands.