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The capacity of battery energy storage systems (BESS) is expected to increase for power system applications. However, as the cost of BESS is high, economic feasibility must be considered when using BESS in grid applications. Load leveling with BESS is one such application for which the economic implications have been analyzed in the literature. However, these studies do not sufficiently consider the fact that the leveled loads will lead to a change in electricity prices, thereby modifying charging/discharging operations of BESS. Additionally, in a competitive electricity market, electricity prices are not determined by the generator cost functions. Market participants’ strategic decisions also affect prices. Therefore, we conducted an economic analysis of load leveling with BESS in an electricity market from the perspective of a utility company and/or a government agency. In our analysis of the Korean market, we examine whether the leveled loads necessarily lead to economic benefits. Load leveling performance and the associated economic benefit are quantitatively analyzed for varying sizes of BESS. Further, the policy implications related to using BESS are derived from the analysis results.

A microgrid is a group of many small-scale distributed energy resources, such as solar/wind energy sources, diesel generators, energy storage units, and electric loads. As a small-scale power grid, it can be operated independently or within an existing power grid(s). The microgrid energy management system is a system that controls these components to achieve optimized operation in terms of price by reducing costs and maximizing efficiency in energy consumption. A post-Industry-4.0 consumer requires an optimal design and control of energy storage based on a demand forecast, using big data to stably supply clean, new, and renewable energy when necessary while maintaining a consistent level of quality. Thus, this study focused on software technology through which an optimized operation schedule for energy storage in a microgrid is derived. This energy storage operation schedule minimizes the costs involved in electricity use. For this, an optimization technique is used that sets an objective function representing the information and costs pertaining to electricity use, while minimizing its value by using Mixed Integer Linear Programming or a Genetic Algorithm. The main feature of the software is that an optimal operation schedule derivation function has been implemented with MATLAB for the following circumstances: when the basic operation rules are applied, when operating with another grid, when the external operating conditions are applied, and when the internal operating conditions are applied.

In a deregulated power system, the independent system operator (ISO) becomes the central entity which is responsible for the reliable system operation and the real-time balancing. ISO can provide necessary functions through the market mechanism. However, the possibility of a price-based operation is suggested as well, in which time-varying price coordinates non-cooperative players' actions. In the price-based operation, the main objectives of operation are also to keep the system frequency to the nominal value and to manage the line congestion. In terms of the frequency, the price-based operation should at least assist the frequency regulation functions by reducing the frequency deviation. For this purpose, this paper tries to present a method to reduce the frequency deviation and proposes the application of PID tuning rule to the design of price-based operation. In addition, a modified asymmetric control structure is proposed to obtain a further reduction of the frequency deviation. The performance and suitability of the designing rule are verified through simulations using the IEEE 39-bus network.

Wind power producers face many regulation costs in deregulated environment, which remarkably lowers the value of wind power in comparison with conventional sources. One of these costs is associated with the real-time variation of power output and being paid in frequency control market according to the variation band. This paper presents a new approach to coordination of battery energy storage in wind generation system for reducing the payment in frequency control market. The approach depends on the statistic data of wind generation and the prediction of frequency control market price to determine the optimal variation band which is then kept by the real-time charging and discharging of batteries, ultimately the minimum cost of frequency regulation can be obtained. The optimization problem is formulated as trade-off between the decrease in the regulation payment and the increase in the cost of using battery, and vice versus. The approach is applied to a study case and the results of simulation show its effectiveness.

Wind power producers face many regulation costs in deregulated environment, which remarkably lowers the value of wind power in comparison with the conventional sources. One of these costs is associated with the real-time variation of power output and being paid in frequency control market according to the variation band. In this regard, this paper presents a new approach to the scheduling and operation of battery energy storage installed in wind generation system. This approach depends on the statistic data of wind generation and the prediction of frequency control market prices to determine the optimal charging and discharging of batteries in real-time, which ultimately gives the minimum cost of frequency regulation for wind power producers. The optimization problem is formulated as the trade-off between the decrease in regulation payment and the increase in the cost of using battery energy storage. The approach is illustrated in the case study and the results of simulation show its effectiveness.

Recently, Korean system operating conditions have gradually approached an upper limit. When a contingency occurs, the power system may have no solutions. Different from the cases of bad initial guesses or the solutions are too close to the solvability boundary in which numerical methods can be applied, for unsolvable cases, the only way to restore solvability would be structure modifications. In this paper, a new approach for corrective and preventive control to such cases is proposed in two steps: (i) finding any solution regardless its feasibility; (ii) for the infeasible solution, make it feasible with additional modifications at load buses having Distributed Energy Resources. The test case built based on the peak load profile of 2008 by KEPCO including 1336 buses is analyzed. Since reactive power compensation is optimized to restore solvability, all demands are met, therefore no blackouts happen. The proposed method was integrated in the LP program designed by power21 Corporation.

The use of a demand response controller is necessary for electric devices to effectively respond to time varying price signals and to achieve the benefits of cost reduction. This paper describes a new formulation with the form of constrained optimization for designing an optimal demand response controller. It is demonstrated that constrained optimization is a better approach for the demand response controller, in terms of the ambiguity of device operation and the practicality of implementation of the optimal control law. This paper also proposes a design scheme to construct a demand response controller that is useful when a system controller is already adapted or optimized for the system. The design separates the demand response function from the original system control function while leaving the system control law unchanged. The proposed formulation is simulated and compared to the system with simple dynamics. The effects of the constraints, the system characteristics and the electricity price are examined further.

– This paper presents the temperature impacts on daily peak load of commercial load in KOREA. This research focuses on the overall summer and winter peak load characteristics and the impact of temperature change on the commercial load. Load data of the last five years are used to analyze the temperature sensitivity of commercial load sensitivity. Keywords : Temperature sensitivity, Commercial load, Peak load, Regression analysis 1. Introduction In the market environment it is becoming increasingly more important to obtain a more accurate model of the usage pattern of electricity consumers for establishing related policies. For example, the amount of generation investment to be made, the appropriate tariff for electricity, the proper level of demand-side management (DSM), etc. are all heavily dependent on the load pattern. In the past, only limited representative consumer load data were available due to the insufficient infrastructure for taking such measurement [2]. However, with the Automatic Meter Reading (AMR) widely deployed it became relatively easier to gather data about many consumers. The electricity load characteristics are being considered in many areas: for example, in performing demand forecast [2,3,8], in computing price elasticity [5], and in designing of DSM and electricity tariffs [6], and in managing various assets [8]. In [4] the temperature sensitivity of load is studied for sample consumers who are selected considering the population of commercial, industrial and residential consumers in Taiwan. In [7] the temperature sensitivity of industry representative load pattern in United States is derived. The temperature sensitivity of electricity load is considered critical with the expansion of electricity-based cooling and heating equipment. In this paper the temperature sensitivity of the commercial load is derived using the Korea’s recent winter and summer power consumptions. In Section 2 the percentage of the sample data is compared. In section 3 summer/winter load pattern and composition are described. Section 4 presents the results of investigating winter and summer temperature sensitivity.

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This paper proposes a new method for monitoring local voltage stability using the saddle node bifurcation set or loadability boundary in two dimensional power parameter space. The method includes three main steps. First step is to determine the critical buses and the second step is building the static voltage stability boundary or the saddle node bifurcation set. Final step is monitoring the voltage stability through the distance from current operating point to the boundary. Critical buses are defined through the right eigenvector by direct method. The boundary of the static voltage stability region is a quadratic curve that can be obtained by the proposed method that is combining a variation of standard direct method and Thevenin equivalent model of electric power system. And finally the distance is computed through the Euclid norm of normal vector of the boundary at the closest saddle node bifurcation point. The advantage of the proposed method is that it gets the advantages of both methods, the accuracy of the direct method and simple of Thevenin Equivalent model. Thus, the proposed method holds some promises in terms of performing the real-time voltage stability monitoring of power system. Test results of New England 39 bus system are presented to show the effectiveness of the proposed method.

Island operation of a microgrid increases operation survivability and reliability when there is a large accident in a main grid. However, because a microgrid typically has limited generation capability, a microgrid operator (MGO) has to take the risk of island operation into account in its market participation and generation scheduling to ensure efficient operation. In this paper, a microgrid islanding event is interpreted as a trade suspension of a contract, and a set of islanding rules is presented in the form of a market rule. The risk of island operation is evaluated by modeling the microgrid islanding stochastically using an islanding probability function, which is defined in the form of a conditional probability to reflect the influence of outside conditions. An optimal bidding strategy is obtained for the MGO by formulating and solving an optimization problem to minimize the expected operating cost. The effectiveness of the proposed method was investigated by numerical simulations in which the proposed method and two other methods were applied to the same microgrid. Numerical sensitivity analyses of the coefficients of the islanding probability function were conducted to determine how an MGO copes with changes in outside conditions.

For developing a large-scale combined system with a number of distributed resources, an appropriate compensation strategy based on the system components and changeable condition must be configured to handle the characteristics of the internal systems. Since renewable sources generate various fluctuations, the compensation plans for the storage device connected along with the sources should be supported by a precise expectation method. A cooperative strategy involving the sharing of the DC section with environmentally sensitive generators, like photovoltaic system (PVs) or waves, demands appropriate ESS compensation solutions, owing to its complexity. An active power-control algorithm with voltage-expectation based on the DC power flow is introduced in this paper and is applied in the designed case studies performed on the electromagnetic transient simulation. DC based multi-generation system is composed by applying tidal generator and super capacitor. To utilize wind energy, an offshore wind–wave generation system was utilized in the verification process.

The optimal planning and operation of integrated energy systems have more economic and environmental advantages than individually optimized systems because of the increasing interdependency between different energy systems. A combined heat and power generation system (CHP) generates electricity and heat simultaneously and is expected to play a key role in both power systems and heat supply systems. An average variable cost (AVC) has been used in planning problems to determine the optimal capacity of generators, boilers, and CHPs. The AVC is calculated from historical data without considering operating points which are affected by demand characteristics. In addition, in the process of calculating AVCs, the heat output of CHPs is neglected and only the power output is considered. In this paper, an AVC calculation method is proposed for the planning problem of a cogeneration system. We suggest a two-dimensional linearized variable cost model to calculate the AVCs simpler and formulate a scheduling problem including the suggested model as mixed integer linear programming (MILP). The problem is solved by general algebraic modeling system (GAMS) and the results are used for calculating AVCs not only in power but also in heat part. Demand patterns in Korea are used to find the operation points of CHP and AVCs.

To address the environmental concerns throughout the world, many new power sources, such as renewable energy, are being introduced. In order to maintain the reliability and stability of the system while integrating these inputs, many systems have started integrating battery energy storage systems. However, the introduction of such system has been very slow due to its high capital costs. Therefore, the economic benefit of a lithium ion battery energy storage system used for frequency regulation in a utility company is analyzed. The profit of a utility is calculated in terms of reduced amount of power purchase cost, and the results verify that the utility is able to recover their investments within the life cycle of the storage system in all cases.

The increasing penetration of plug-in electric vehicles (PEVs) may cause a low-voltage problem in the distribution network. In particular, the introduction of charging stations where multiple PEVs are simultaneously charged at the same bus can aggravate the low-voltage problem. Unlike a distribution network operator (DNO) who has the overall responsibility for stable and reliable network operation, a charging station operator (CSO) may schedule PEV charging without consideration for the resulting severe voltage drop. Therefore, there is a need for the DNO to impose a coordination measure to induce the CSO to adjust its charging schedule to help mitigate the voltage problem. Although the current time-of-use (TOU) tariff is an indirect coordination measure that can motivate the CSO to shift its charging demand to off-peak time by imposing a high rate at the peak time, it is limited by its rigidity in that the network voltage condition cannot be flexibly reflected in the tariff. Therefore, a flexible penalty contract (FPC) for voltage security to be used as a direct coordination measure is proposed. In addition, the optimal coordinated management is formulated. Using the Pacific Gas and Electric Company (PG&E) 69-bus test distribution network, the effectiveness of the coordination was verified by comparison with the current TOU tariff.

Under a deregulated environment, wind power producers are subject to many regulation costs due to the intermittence of natural resources and the accuracy limits of existing prediction tools. This paper addresses the operation (charging/discharging) problem of battery energy storage installed in a wind generation system in order to improve the value of wind power in the real-time market. Depending on the prediction of market prices and the probabilistic information of wind generation, wind power producers can schedule the battery energy storage for the next day in order to maximize the profit. In addition, by taking into account the expenses of using batteries, the proposed charging/discharging scheme is able to avoid the detrimental operation of battery energy storage which can lead to a significant reduction of battery lifetime, i.e. , uneconomical operation. The problem is formulated in a dynamic programming framework and solved by a dynamic programming backward algorithm. The proposed scheme is then applied to the study cases, and the results of simulation show its effectiveness.

The present study examines an efficient congestion management system compatible with the evolving environment. The key is to build an information model shared and exchanged for marketbased solutions to alleviate congestion. Traditional methods for congestion management can be classified into two categories, i.e., the centralized scheme and the decentralized scheme, depending on the extent to which the independent system operator (ISO) is involved in market participants’ (MPs) activities. Although the centralized scheme is more appropriate for providing reliable system operation and relieving congestion in near real-time, the decentralized scheme is preferred for supporting efficient market operation. The minimum set of information between the ISO and MPs for decentralized scheme is identified: ⅰ) congestion-based zone, ⅱ) Power Transfer Distribution Factors, and ⅲ) transmission congestion cost. The mathematical modeling of the proposed information is expressed, considering its process of making effective use of information. Numerical analysis is conducted to demonstrate both cost minimization from the MP perspective and the reliability enhancement from the ISO perspective based on the proposed information exchange scheme.

This paper presents a new and efficient approach to determine security-constrained generation scheduling (SCGS) in large-scale power systems, taking into account dispatch, network, and security constraints in pre and post-contingency states. A novel ramp rate limit is also modeled as a piecewise linear function in the SCGS problem to reflect more practical characteristics of the generating units. Benders decomposition is applied to this constrained solution process to obtain an optimal SCGS problem based on mixed-integer nonlinear programming (MINLP). The formulation can be embedded in two stages. First, a MIP is formulated in the master problem to solve a unit commitment (UC) problem. This stage determines appropriate on/off states of the units. The second stage, the subproblem, is formulated as a NLP to solve a security-constrained economic dispatch (SCED) problem. This stage is used to determine the feasibility of the master problem solution. It provides information to formulate the benders cuts that connect both problems. The proposed approach is tested in the IEEE 118-bus system to show its effectiveness. The simulation results are more realistic and feasible, whilst assuring an acceptable computation time.

Electric power transmission utilities try to maximize profit by reducing electricity supply costs and operation costs while maintaining their reliability. Developing maintenance strategies is one of the effective ways to achieve these profitable goals. The reliability-centered maintenance approach is a key method in providing optimal maintenance strategies. It considers the tradeoffs between the upfront maintenance costs and the potential costs of reliability losses. Since a transmission system is a group of different kinds of equipment and the reliability of the electric facilities varies with time, an equipment state model using a modified semi-Markov chain is proposed. In addition, a genetic algorithm is used to find the optimal maintenance strategies from a large class of possible maintenance scenarios. These optimal maintenance strategies have been tested on an IEEE 9-bus system and an IEEE 118-bus system; the results show that the proposed method minimizes the total expected costs.

DR(Demand response) is a rising issue in electricity power market by reducing load quantity instead of increasing generation for balancing demand and supply. DR resources are regarded as an extra tool of balancing supply and demand in emergency condition. DR resources usage in normal condition is also possible and used for the purpose of reliability and economic effect. For determining incentive for DR resources in PJM, fixed incentive level was used to reward the effect of market price reduction by DR program. However, since the fixed level of incentive is obtained by historical data, it cannot reflect the continuous change of market well. Furthermore, traditional method only concentrates to economic effect and it hardly concerns about the effect of preventing price variation by DR resources. In this paper, method of evaluating the market price reduction and prevention of price variation by DR is described under reliability considered situation. New mechanism for determining extra incentive is provided. From comparing the situation that DR is not implemented and the situation DR is implemented, novel mechanism can give more rewards to participants who contribute the stabilization of price and the reduction of load. Reward is exponentially increased as the DR resource stabilizes the price variation. On the other hand, reward is exponentially decreased as the DR resource increases price variation. Several cases are showed for checking effects and calculating the extra incentive.

In many countries, the electric power system and market interconnection is undergoing. To facilitate an efficient interconnection power market, transparent congestion management methodology is essential. In this paper, the explicit auction of transmission rights in the interconnection power market is simulated. An algorithm for evaluating values and Value-At-Risk(VAR) and for long-term transmission rights using Monte-Carlo Simulation(MCS) and Probabilistic Optimal Power Flow(POPF) is proposed to give information to transmission right providers and market participants

show similar coordination tendencies to metal ions and form corres-ponding metal complexes, the chemical and structural properties of metal complexes are greatly influenced by the stereochemistry of cyclohexane rings fused on the 14-membered tetraazamacro-cycle. Thus, the axial coordination of solvent molecules to the nickel(II) ion in [Ni(

In these days energy demand is dramatically increasing on the developed and developing countries. Even though the electric power efficiency is gradually improved, the limited energy resources and the shortage of land to construct generations have been existed for long time ago and the environmental limitation like the Kyoto-Protocol is originated. To overcome these obstacles, there is one solution through the cooperation on the national-wide. That is, we should meet the energy problem with having strong relationship among nations. The technological and systemic cooperation on electric power system is much more important than before. It is sure that there are economical and systemic advantages over the limitations when inter-regional power systems are operated well. Simply, power system interconnection gives the eco-friendly energy' applications and the flexible operating power system. In this paper, the first is focused on the algorithms on the power system and the other is based on the economic side. It is mainly to discuss the tertiary control illustrated over each first and secondary controls existing on two control areas.

Electricity customers can achieve economic benefits from cost reduction and/or revenue increase using battery energy storage system (BESS). However, different conditions of each customer require different methods to determine the suitable size of BESS. Additionally, different operation strategies of BESS result in the different cost/benefit analysis. Thus, in this study, authors have identified and focused on the electricity customers with TOU rate, varying operation mode with the seasons, and charging scheme based on both energy consumption and the peak demand. The procedures to find the optimal power and energy capacities for the selected customer are formulated. The optimal operation strategy with priority, that is, peak shaving–DR–scheduling modes in summer/winter and DR–scheduling mode–peak shaving modes in spring/autumn, is also proposed. The proposed method is applied to a specific type of customer in Korea in the case study. The results showed that an optimal capacity can be found and the proposed operation strategy with priority is optimal. Moreover, it has been found out that, for this type of customer, the large energy capacity of BESS mostly leads to large economic benefit; in contrast, the small power capacity mostly leads to small economic benefit.

Related to global efforts to reduce greenhouse gases, numerous electric vehicles (EVs) are expected to be integrated to the power grid. However, the introduction of EVs, particularly in Korea, is still marginal due to the lack of EV charging infrastructure, even though various supportive policies exist. To address this shortage of EV charging stations, the EV charging business needs to be profitable. As with any business, the profitability of the EV charging business is significantly affected by the initial capital investment related to EV chargers and auxiliary equipment such as power conditioning system (PCS), battery energy storage system (BESS), and on-site photovoltaic (PV) generation system. Thus, we propose a formulation to determine the number of EV chargers and the capacity of auxiliary equipment with the objective of a charging station operator (CSO) maximizing profit under regulatory, economic, and physical constraints. The effectiveness of the proposed method is verified with simulations considering various EV charging patterns. The study results will help improve the EV charging infrastructure by encouraging individuals and companies to participate in EV charging business.

A new silver(II) complex, {[Ag( L1 )](NO 3 ) 2 ·4H 2 O} n ( 1 ) ( L = 3,14-dimethyl-2,6,13,17-tetraazatricyclo[14,4,0 1.18 ,0 7.12 ] docosane) has been synthesized and structurally characterized by a combination of analytical, spectroscopic, electrochemical and X-ray diffraction methods. The complex 1 exhibits a 1D supramolecular polymer with the silver(II) macrocycle L1 and nitrate ions, where 1D chain is formed by hydrogen bonds between the two sets of pre-organized N–H groups of the macrocycle and nitrate ions. The lattice water molecules mediate to interconnect each 1D chain to form the 2D supramolecular sheet. In 1 the unusual high oxidation state of Ag(II) is stabilized by the tetraazamacrocyclic ligand L1 . The cyclic voltammogram for 1 indicates that the electrochemical oxidation of [Ag( L1 )] 2+ is an irreversible process.

The market share of electric vehicles is growing and the interest in these vehicles is rapidly increasing in industrialized countries. In the light of these circumstances, this study provides an integrated policy-making package, which includes key features for electric vehicle diffusion and its impact on the Korean power market. This research is based on a quantitative analysis with the following steps: (1) it analyzes drivers&rsquo, preferences for electric or traditional internal combustion engine (ICE) vehicles with respect to key automobile attributes and these key attributes indicate what policy makers should focus on, (2) it forecasts the achievable level of market share of electric vehicles in relation to improvements in their key attributes, and (3) it evaluates the impact of electric vehicle diffusion on the Korean power market based on an achievable level of market share with different charging demand profiles. Our results reveal the market share of electric vehicles can increase to around 40% of the total market share if the key features of electric vehicles reach a similar level to those of traditional vehicles. In this estimation, an increase in the power market&rsquo, s system generation costs will reach around 10% of the cost in the baseline scenario, which differs slightly depending on charging demand profiles.

This paper presents a decentralized adaptive backstepping controller to dampen oscillations and improve the transient stability to parametric uncertainties in multimachine power systems. The proposed design on the i th synchronous generator uses only local information and operates without the need for remote signals from the other generators. The design of the nonlinear controller is based on a modified fourth-order nonlinear model of a synchronous generator, and the automatic voltage regulator model is considered so as to decrease the steady state voltage error. The construction of both the control law and the associated Lyapunov function is systematically designed within the design methodology. A 3-machine power system is used to demonstrate the effectiveness of the proposed controller over two other controllers, namely a conventional damping controller (power system stabilizer) and one designed using the feedback linearization techniques.

The purpose of this paper is to examine the economic and technical perspectives of dynamically administered critical peak pricing (DA-CPP) program as an active demand response (DR) program. To implement a good DR program, there are three perspectives to be considered: regulatory, economic, and technical perspectives. We propose a special DA-CPP program as an effective DR program, which is administered by an energy service provider (ESP). ESP has control on when to call critical peaks on this program. This gives both the administrator and the end-use customers incentives to reduce loads on critical moments. We will assume that the regulatory perspective of DR is determined as a DA-CPP program and examine the other two. The economic perspective of DA-CPP program is the incentive of the program administrator, or the profit of an ESP. The technical perspective is a method to maximize the incentive of DA-CPP program, or an ESP's profit. An ESP should decide when to call critical peaks within certain constraints to maximize her profit. This is done by predicting the market prices and following a similar method as evaluating a swing option. The numerical example will show the optimal critical peak decisions. Copyright © 2008 John Wiley & Sons, Ltd.

The market power by large suppliers remains to be problematic in establishing an efficient competitive market for electricity. The exercise of market power is often facilitated due to a few notable properties of electricity as a tradable commodity. The pivotal supplier whose capacity exceeds the market's surplus of capacity above inelastic demand can strategically withhold its capacity and cause an undesirable price spike. This paper presents a methodology for determining an adequate amount of mandatory long-term contract to be used to mitigate the market power of the pivotal supplier and to eliminate the undesirable price spike. Using the Cournot model, the effect of mandatory long-term contracts is measured with respect to market equilibrium for the pivotal monopoly in which there is only one pivotal supplier and for the pivotal duopoly in which two suppliers join together and become pivotal. Applying the methodology described in the paper, the market efficiency is assured as the pivotal supplier that no longer has the incentive to cause the undesirable price spike. Copyright © 2007 John Wiley & Sons, Ltd.

In trying to determine the available transfer capability (ATC), this paper primarily sets out to develop a fuzzy logic approach to parallelizing contingency-constrained optimal power flow (CCOPF). This algorithm may be used by utilities to optimize economy interchange for severe contingencies analyzed without disclosing details of their operating costs to competitors. In fact, the ultimate objective of fuzzy multi-objective CCOPF (FMCCOPF) is to carry out the minimization of both the base case (pre-contingency) operating cost and the post-contingency correction times as conflicting but fuzzy goals. Besides, the Benders decomposition is applied to partition the fuzzy formulation with contingency constraints, which allows for post-contingency corrective rescheduling, motivated by the improvement of computational efficiency using parallel processing. The feasibility of the proposed method is comprehensively realized by a comparison with the conventional optimal power flow (OPF) and the CCOPF with respect to the same array of transactions, base case, and generator/line outages for the IEEE-30 bus system and the IEEE-118 bus system.

The operation of electric power network at any given time can be classified into one of the following states: normal, warning, alert, emergency and restoration, through reliability assessment. Typically, the classification into these states based on present method is useful for providing qualitative description of how reliably the network is being operated but lacks the quantitative valuation. In this paper we propose a new method for classifying operating states appropriate in Cost Based Pool (CBP) market in Korea. By taking the cost of control actions with respect to various plausible contingencies into consideration, the proposed method properly values the trade-off between technical reliability and economic efficiency. In applying the method the operational limits, such as maximum transfer capabilities and maximum voltages, are established at the planning stage. Established limits are then used to assess the reliability, and the control actions are applied by the system operator as needed at the operation stage. Several flowcharts are presented for showing how the proposed method is applied, and a case study is given for illustration purposes. It is shown that the proposed method properly incorporates the rational decision process by the system operator in detecting and responding to threats to system stability. In addition, it is shown that the classification by the proposed method is particularly useful for compensating network users participating in network control in the market environment.

The variability and uncontrollability of wind power increases the difficulty for a power system operator to implement a wind power system with a high penetration rate. These are more serious factors to consider in small and isolated power systems since the system has small operating reserves and inertia to secure frequency and voltage. Typically, this difficulty can be reduced by interconnection with another robust power system using a controllable transmission system such as a high-voltage direct current (HVDC) system. However, the reliability and stability constraints of a power system has to be performed according to the HVDC system implementation. In this paper, the method for calculation of maximum wind power penetration in an island supplied by a HVDC power system is presented, and the operational strategy of a HVDC system is proposed to secure the power system reliability and stability. The case study is performed for the Jeju Island power system in the Korean smart grid demonstration area.

Within active distribution network management, distributed generations, which are contracted by the non-firm connection method, can be directly controlled by the distribution network operator to adjust their power factor and the active power output level. This is called an output curtailment of distributed generation. Although the purpose of the output curtailment is to stably operate the distribution network, it inevitably limits the revenue of distributed generations. Therefore, the need for suitable compensation to the output curtailment is often discussed. As an extension to the discussion, this study proposes the method to determine the suitable bounds of the compensation price for output curtailment. In the proposed method, the suitable bounds of compensation price are obtained from the profit analysis of stakeholders in accordance with the level of the compensation price through optimal power flow technique.

Introduction of the smart grid circumstance encourages more demand-side participation in the power system operation. Accordingly, many kinds of the demand response (DR) programs are implemented by electric utilities. Among the DR programs, real-time pricing (RTP) is considered as a good option to utilities because it can directly reflect time-varying production cost to retail price; however, an implementation of RTP requires an automated scheme in customer side especially for the residential customers who have hard time to respond to time-varying price signal manually. This study suggests a customer-side automated scheme result from modifying legacy type appliances into smart appliances. The objective of the modification is minimization of customer's energy cost. In addition, it also reduces the peak-to-average ratio (PAR) on utility perspective. Two types of the SAs are modeled which are do more type SA and store type SA. In design process, the most important philosophy is that customer is not aware of the control. Through the design methodologies presented in this study, customers get financial benefit under RTP while their utility is not reduced. Furthermore, electric utilities can benefit from lowered PAR.

This paper scrutinized the damping effects of installing the prototype PSSs by a transient analysis for eight buses of faults in the South Korean power system. The PSSs used have the ω-PSS blocks for IEEEST model with a single input and the ω+power PSS blocks for PSS2A model with dual inputs. The simulation tool was a TSAT (Transient Security Assessment Tool) developed by Powertech Labs Inc. The voltages of the transmission line for simulations were 765㎸ and 345㎸, and the faults for eight cases were sequenced by considering the open state and the close state of the lines. In the simulations, the three-phase line to ground (L-G) fault generated different points for each region. The simulations were compared to the cases of no PSS, partial IEEEST and PSS2A, absolute IEEEST, and absolute PSS2A to show that the power system oscillation can be effectively damped by PSS modules. Simulations were conducted to confirm the effectiveness for the KEPCO (Korea Electric Power Corporation) power system.

Strictly engineering aspects of available transmission capacity (ATC) are analyzed first. Nonlinear network theory is used to provide several key conditions under which one could define a notion of ATC and specific novel algorithms for its evaluation. Next, the fundamental problem which prevents one from developing an economically efficient distributed transmission market based on the ATC is identified. It is suggested that for an electric power network of an arbitrary topology it is not possible to map the computed ATC onto its market value. All findings are illustrated using examples of small power systems.

This paper presents a power system operation optimization algorithm including VSC-HVDC (Voltage Source Converter - High-Voltage Direct Current) lines using PD-IP (primal-dual interior point) Newton-type OPF (optimal power flow). The VSC-HVDC links have the ability to exert instantaneous power control in neighboring AC systems. Moreover, the VSC-HVDC technology is fit for meeting the growing needs of the DER (distributed energy resource) connection, such as with wind power generation in power systems. The output results for the voltage and the angle are shown by the simulation for the insertion of VSC-HVDC line in the IEEE 30-bus power system. Simulations are executed by the MATPOWER (MATLAB power system simulation) tool for the optimal power flow.

This paper describes the smart grid operation strategies based on nuclear load following to improve the power system reliability in order to prepare preparations for the increasing use of renewable resources and real-time demand response. Load following operation in a nuclear power plant is a method of regulating the power supply and keeping the demand stable in the allowed range of nuclear power generation to relieve the effects of power interconnections for generation sources with renewable generations or very large variations of generation output in the case of power interconnection. In this simulation, we performed an inter-area power flow simulation for the variation of the power generation/load using the Korea Electric Power Corporation (KEPCO) 2020 power system planning data in South Korea. We used the PSS/E 32 version tool for the inter-area flow simulation.

In this paper, we present a smart grid (SG)-based substation testing simulator (STS) design for the South Korean power distribution system. The presented STS can serve as both a test bed for new devices and as a training facility for education. It features closed-loop testing, and reflects both control/protection functions within the substation and interaction with the Web or a telecontrol system (IEC61850, DNP, IEC60870-5, Modbus, etc). This STS can save certification time for the domestic/international standard fitness required for developed devices before a field test. The constituted algorithms have substation topology processing, relay action sequence, and state estimation. The substation data can be stored in a database management system (DBMS) after the effective analysis for the results of the SG-based STS. For the development of a new system and an educational environment, the concept of open systems is applied to a substation testing system. The proposed STS will be designed on a substation structure in the Korea Electric Power Corporation (KEPCO).

This paper presents the generator's internal fault modeling and analysis based on the one-machine infinite-bus power system for the simulation of internal faults in a synchronous generator. The model applied is a low-order synchronous generator model, and is based on the so-called fourth-order representation with the mechanical mode from the second-order system and the electrical mode from the second-order system. The test cases for internal faults demonstrates the output waveforms for id, iq, vd, vq, ω, Efd, Vt, Te, ia, ib, ic, va, vb, and vc using the MATLAB tool. Furthermore, the fault perturbations for internal windings and for an exciter terminal are also carried out and are compared by the results of four cases of simulations.

This paper presents smart grid operation strategies based on the Northeast Asia power system interconnection (smart power grid, smart place, smart transport, smart renewable, and smart electric service) in the South Korean power system. Future smart control centers should be flexible to include energy resources into the unit dispatch to increase efficiency in utilizing renewable energy, and controllable load to meet future demand. Future market operation should also have interaction with the electricity market, which is not currently possible in the present market operation functions in the South Korean power system. In this paper, we suggest how to design smart grid operation strategies for the Northeast Asia power system interconnection, smart power grids, smart places, smart transport, smart renewables, and smart electric services in the South Korean power system.

Active Network Management (ANM) enables a microgrid to optimally dispatch the active/reactive power of its Renewable Distributed Generation (RDG) and Battery Energy Storage System (BESS) units in real time. Thus, a microgrid with high penetration of RDGs can handle their uncertainties and variabilities to achieve the stable operation using ANM. However, the actual power flow in the line connecting the main grid and microgrid may deviate significantly from the day-ahead bids if the bids are determined without consideration of the real-time adjustment through ANM, which will lead to a substantial imbalance cost. Therefore, this study proposes a formulation for obtaining an optimal bidding which reflects the change of power flow in the connecting line by real-time adjustment using ANM. The proposed formulation maximizes the expected profit of the microgrid considering various network and physical constraints. The effectiveness of the proposed bidding strategy is verified through the simulations with a 33-bus test microgrid. The simulation results show that the proposed bidding strategy improves the expected operating profit by reducing the imbalance cost to a greater degree compared to the basic bidding strategy without consideration of ANM.

This paper proposes a new method for assessing static voltage stability based on the local loadability boundary or P- Q curve in two dimensional power parameter space. The proposed method includes three main steps. The first step is to determine the critical buses and the second step is building the local loadability boundary or the saddle node bifurcation set for those critical buses. The final step is assessing the static voltage stability through the distance from current operating point to the boundary. The critical buses are defined through the right eigenvector by direct method. The boundary obtained by the proposed method that is combining a variation of standard direct method and Thevenin equivalent model of electric power system is a quadratic curve. And finally the distance is computed through the Euclid norm of normal vector of the boundary at the closest saddle node bifurcation point. The advantage of the proposed method is that it keeps the advantages of both efficient methods, the accuracy of the direct method and simple of Thevenin Equivalent based method. Thus, the proposed method holds some promise in terms of performing the real time voltage stability assessment of power system. Test results of New England 39 bus system are presented to show the effectiveness of the proposed method.

In this paper, we suggest the operation, market structure, and regulation strategies with distributed generation (DG), demand response (DR), smart grid (SM) in the Korean power distribution system. The strategic business unit (SBU) in the Korea Electric Power Corporation (KEPCO) was introduced as an alternative strategy because of the interruptions in the steps of distribution separation in the power generation sector. The SBU is a system which retains responsibility for its own costs through self-regulation by each unit, thus providing incentives for competition, innovation and learning. In the regulatory perspective data envelopment analysis (DEA), the retail price index (RPI-X) regulation algorithm can be used to evaluate the relative efficiency of each unit in incentive based regulation. A distributed distribution power flow analysis can be performed for the calculation of the boundary values of each SBU's information. In this paper, we will consider diverse strategies involving DG, SM, DR, and market regulation strategies in the South Korean power system.

In this paper, a new method for solving the divergence of power flow is proposed. The salient feature of the new method is that instead of focusing on computation techniques as in prevalent methods, physical conditions of networks are changed to overcome problem of divergence, i.e. reallocating reactive power compensations. Since incongruous distribution of reactive power may lead to divergence of load flow, switched shunts are controlled to re-appropriate reactive power in power systems. As a result, mismatch decreases over iterations of Newton-Raphson method and power flow quickly converges. The most important contribution of the proposed method is ability to prevent voltage collapse. Numerical test on a large scale electric power system is analyzed. Moreover, an approach to derive a simple formula to control voltage at some heavy load bus is presented. The reactive power source used in this research is the distributed generator which is adjacent to the heavy load. Linearizing the power network using Power Transfer Distribution Factors is a simple method with accepted errors. A new value of voltage at the distributed generator terminal is computed in terms of the voltage deviation of load buses. In this approach, solving the entire system is unnecessary.

This paper, based on the Northeast Asia (NEA) power system interconnection, presents an integration of renewable generation (RG), demand response (DR) or distributed generation (DG), high-voltage direct-current (HVDC), and nuclear power plant load-following operation under Smart Grid (SM) in the South Korean power system. The reliable power system depends on considering the reliability that affect after the system is connected or disconnected. The land-to-land power system interconnection in NEA countries will use as the back to back (BTB) technique for power transmission lines; whereas the point-to-point (PTP) will be used for over-sea interconnection, such as a Jeju Island and South Korea-Japan submarine transmission. In this paper, we will suggest how to design and analyze the operation mechanism/algorithm of the reliability side for the NEA, and an integration of RG, DR, HVDC, and nuclear power plant load-following operation under SM in the South Korean power system. Also, we present an inter-area power flow map for a power flow analysis for NEA countries to relieve the possible future power imbalances within the metropolitan areas or the southeastern area of Korea.

Two new methods for real time computing critical clearing time based on clustering identification are proposed. This article is covering three main sections: (i) clustering generators and recognizing critical group; (ii) replacing the multi-machine system by a two-machine dynamic equivalent and eventually, to a one-machine-infinite-bus system; (iii) presenting a new method to predict post-fault trajectory and two simple algorithms for calculating critical clearing time, respectively established upon two different transient stability criterions, which are fast enough for real time purposes. The prediction method is developed to tackle with the problem of predicting post-fault trajectory on the basis of merely measured data in the first few centiseconds immediately after the system is perturbed. The performance is expected to figure out critical clearing time within 100ms-150ms and with an acceptable accuracy.