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The 20^th Power and Energy Society Annual Conference was held on August 18-20, 2009 at Shibaura Institute of Technology. The total number of technical papers was 352, and technical sessions were 47 (46 oral sessions and 1 poster session). An invited lecture, a panel discussion, technical exhibitions and two technical tours were organized. All events were very well attended and the final enrollment attained to 881 registrations. The conference was successfully closed by the great contribution of all participants. The outline of the conference is reported in this article.

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We have proposed the new surge type FL using hybrid detection type fault recorder to measure the location of a line fault precisely in the power system. This new recorder has a feature that the starting detection of the recorder is not a instantanceous value of a high speed data but a effective value of low sampling data. This new recorder has a high speed sampling part and a low speed sampling part. A high speed sampling part works a recording of surge data. On the other hand, a low speed sampling part works a detecting of trasmission line fault. The authors carried out field tests with this new recorder installed at plants and substation in the 275kV power transmission system of TEPCO (Tokyo Electric Power Company). And we obtained good results. This paper presents these results.

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In order to effectively monitor and control the interarea oscillations in a power system, it is crucial to obtain the full knowledge about the oscillation mode, such as participation level, mode distribution, frequency and damping. The paper presents an approach to estimate the participation weight of a generator in an oscillation mode based on synchronized phasor measurements and auto-spectrum analysis. The participation weight is a quantity defined in this paper to indicate the relative participation of one generator in one oscillation mode of interest. Compared to traditional participation factor computed from model-based modal analysis, the participation weight is directly defined and estimated based on the measurements of system output signals. The input-output relationship for a constant-parameter linear system when subjected to a stationary white noise disturbance is introduced to establish connection between measureable power system response quantities and participation weight. The auto-spectrum analysis is adopted to estimate participation weight with demonstrative examples, which include simulation examples as well as practical examples using measured phasor data from the CampusWAMS.

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Our study aims at minimization of power not supplied (PNS) under the severe fault condition such as tripping of double circuits of transmission lines. In this paper, we propose a new static control method which can minimize PNS by coordinately controlling multiple unified power flow controllers (UPFCs), generators and loads. The proposed method is based on multiple optimal power flow (OPF) calculations, and determines not only control variables of UPFCs but also which and how much generators and loads should be shed after the fault. Digital simulations are carried out with the IEEE RTS-24 system. Three simulation cases, with and without UPFCs, and with uncontrollable UPFCs, are compared and the results shows that reduction of PNS can be accomplished by UPFCs with the proposed control method. Furthermore, it is made clear that the multiple OPFs, which consider the priority loads to be shed, are very effective on reduction of total PNS.

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A clear criterion for evaluating the degree of contribution to a power system by microgrids is needed to facilitate the spread of microgrids. This requires clarifying the composition and scale of distributed generators (DGs) in the microgrid. Once the criterion has been identified, the control system characteristics needed to meet the criterion must be determined.
To evaluate how differences in the control characteristics of the DGs in a microgrid affect the power flow at the grid-connection point, we conducted tests for the four cases. The goal was to control the energy so as to keep the difference between supply and demand within ±3% over 30 min. In our experiments, the goal was met for each case. However, there was a distinctive trend in the variation in power flow at the grid-connection point and in the imbalance between supply and demand over 30 min. There was superiority or inferiority from the viewpoint of control accuracy. Moreover, there were significant differences among the four cases in terms of the amount of the change and the cycle of power flow fluctuation at the grid-connection point that can be controlled. It is thus important to clarify how the composition and scale of the DGs in a microgrid and the characteristics of the control system affect the contribution of the microgrid to the power system.

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This paper presents a daily load curve forecasting method using hourly regressions. Electric load varies significantly during the day. Many factors, such as weather conditions, hours and day-types, relate to the load behavior. We formulate a daily load curve in set of independent 24-h regression equations that split hourly load into four parts: weather related load (WE), weekday's day-types (DTW), non-weekday's day-types (DTH), and yearly trends (TR). We incorporate temperature, humidity and insolation into the WE part. Non-linear relationships of weather factors and loads are formulated by polynomial functions. Another approach, based on Gaussian functions, is also applied to the modeling for the weather and load relationships. In order to estimate regression coefficients properly, we should consider seasonal load change and estimate the coefficients with statistically enough amounts of data. The proposed method estimates the equations with data from both forecasting year and past years. TR compensates yearly load difference among the data. As TR representations, we propose ‘additive trends model’ and ‘multiple trends model’. Experimental studies on the next day load forecasting are carried out with TEPCO system load. The results indicate effectiveness of (1) combination of ‘polynomial function’ and ‘multiple trends model’ and (2) ‘Day-types’ and ‘Insolation’; in the next day load curve forecasting. Performance of less than 1% MAPE is also observed on the next day weekdays' peak load forecasting.

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This paper discusses investment strategies in distributed energy system consisting of cogeneration system and renewable power generation, under uncertainty in the natural gas and the electricity prices as well as related risk assessment of investment strategies. Although incentives for introducing distributed energy system increase these days, volatile natural gas prices make its investment risky. Therefore, it is important to evaluate the risk under uncertainty and find strategies which reduce the exposure to volatility. We take the real option approach to analyze investment decision. By varying the parameters of prices volatility and correlation between uncertainty of natural gas price with that of electricity price, we find that the optimal investment strategy depends on the level of uncertainty and correlation. When volatility is large and correlation is small, strategies with installation option of small renewable power generation, here, photovoltaic generation, and small cogeneration system become attractive in terms of risk reduction.

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This paper proposes a new efficient Multi-objective Memetic Algorithm (MOMA) for probabilistic distribution network expansion planning (DNEP). Recently, the deregulated and competitive power market brings about uncertainty, i.e., random output of distributed generation (DG) such as wind and photovoltaic power, load growths, etc. DG plays a key role to smooth distribution network planning. However, system planners are faced with new uncertain environment. This paper makes use of Monte-Carlo simulation to consider these uncertainties efficiently. Furthermore, a new method is proposed for multi-objective DNEP problems with MOMA that combines Multi-objective meta-heuristics with local search to obtain better solution sets. This paper proposes SPEA2 with Random Multi-start Variable neighborhood LS (RMSVLS) to consider the diversity and accuracy of solution sets. The proposed method is successfully applied to a sample system.

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Low Harmonic Components Elimination Method is effective to suppress the Harmonics of self-commutated converter. But this method can't control the harmonic voltage. Recently the technique have been proposed to control self-commutated converter as shunt active filter to suppress the harmonics voltage of power system, but this method can't be used for this purpose. In this paper, a new PWM method is proposed to control specific low harmonic component. The proposed method uses the approximate equation that was led from theoretical value. The proposed method turned out decreasing the total harmonic distortion of the power system more than conventional Low Harmonic Component Elimination Method by some experimental results employing STATCOM.

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Recently, photovoltaic generation (PV) attracts great attentions as a countermeasure against the global warming and the depletion problem of fossil energy resources in the world. However, it is known that a PV output fluctuates due to the insolation variation. Unstable power from a PV power station may cause some negative impact to the power system. Therefore, to utilize a PV power station in substitution for an existing power supply, improvement in controllability and adjustability of generation output is very important factor. In this paper, a new method for scheduling and rescheduling the PV power station output based on the solar radiation forecast are proposed. The scheduling and rescheduling method using NAS battery and solar radiation forecast from the economic perspective are proposed and the validity of the proposed method is ascertained through case studies using the data measured in the Wakkanai PV power station.

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Total Transfer Capability (TTC) was defined to provide information for energy trading management and transmission system planning in a deregulated environment. Although TTC calculation has been well researched and conducted, a new method is still required to take into account the presence of generation from renewable energy sources. Among the renewable energy sources used nowadays, wind and solar energies have received the most attention. The increasingly widespread use of wind and solar power generation is expected to have an impact on the TTC due to the fluctuating output strongly depending on the wind speed and climate. This paper primarily investigates such impact on the system TTC. The uncertainty from wind and solar power generation outputs is integrated into the calculation by using the Monte Carlo simulation. Based on the risk concept, the TTC at risk is selected. The validity of the proposed method is illustrated through the numerical simulation conducted on the modified IEEE 30-bus test system.

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It is of prime importance to introduce distributed generators which can utilize new energy in order to improve the energy and environment issues. When a distribution network has a large amount of distributed generators, voltage maintenance becomes one of serious problems. To solve this problem, the authors have proposed “voltage profile control method” using reactive power control of inverters in previous works. However, in the previous papers, it is supposed that active power of distributed generators must be decreased when the reactive power of inverter increases because the case in which the inverter has no reserve capacity for reactive power control is treated. In reality, it is natural that the inverter has reserve capacity because the inverter capacity is determined in order to satisfy the maximum output of distributed generator. Therefore, in this paper, we define the reactive power control using the reserve capacity has high priority because the reduction of active power is not caused by the reactive power control. Hence, we develop a new control method which can consider the control priority. The proposed method is tested in 5-node and 24-node model system.

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In this paper, a hybrid intelligent system is proposed for estimating a load margin to the saddle node bifurcation point of voltage stability. It is based on the integration of Regression Tree (RT) and Artificial Neural Network (ANN). Voltage stability analysis is one of the main concerns in power system operating and planning. The objective of voltage stability analysis is to evaluate the saddle node bifurcation point on PV or QV curves. Thus, it is necessary to estimate a load margin to the saddle node bifurcation point of voltage stability efficiently. This paper proposes a new method for estimating the load margin with the hybrid method of RT and ANN. RT is used to classify data into terminal nodes and extract rules from each terminal node. ANN is constructed to estimate the load margin to the bifurcation points at each terminal node. Also, a new method for generating power system conditions is presented to consider the correlation of the nodal specified values. The effectiveness of proposed method is demonstrated in the IEEE 30-bus system in terms of computational accuracy and computational time.

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The micro-grid has been operating at institute of technology of Shimizu Corporation since July, 2006. Main generators are two gas engine CHP systems which capacity are 350kW and 90kW. Two power storage devices, secondary battery and electric double layer capacitor, are also installed to compensate rapid load fluctuation. In this paper, load demand is analyzed by using frequency analysis and this sampling interval is decided by probability distribution of power transition. DG systems' characteristics such as frequency response, fuel efficiency and frequency stabilization capability are also assessed. Capacity of DG Systems in the Micro-grid is evaluated by results of load demand analysis and DG systems' characteristics assessment.

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When a microgrid is operated in the islanding mode, the operator must satisfy the power quality demand by compensating the active and reactive power using several types of distributed power generation (DG) systems. In this paper, a method to stabilize the system frequency fluctuations and voltage fluctuations of the islanding microgrid is suggested. Extending the suggested “combined cascade control method” which can realize the power compensation without interferences between several types of DGs, “hybrid control” strucuture is proposed and negative effects of control and measurement signal delays on a control are reduced. Moreover, a control of the state of charge (SoC) of energy storage devices is added. For the stabilization of the system voltage, the energy storage is driven by “STATCOM model control”. Experiments have been carried out to confirm the effects of these methods by use of the model microgrid system, and satisfying results were received.

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In this paper, a new improved hybrid meta-heuristic method is proposed to solve the unit commitment problem effectively. The objective is to minimize operation cost while satisfying the power balance constraints and so on. It may be formulated as a nonlinear mixed-integer problem. In other words, the unit commitment problem is hard to solve. Therefore, this paper makes use of a hybrid meta-heuristic method with two layers. Layer 1 determines the on/off conditions of generators with tabu search (TS) while Layer 2 evaluates output of generators with evolutionary particle swarm optimization (EPSO). The construction phase of Greedy Randomized Adaptive Search Procedure (GRASP) is used to create initial feasible solutions efficiently. Three kinds of meta-heuristic methods such as TS, EPSO and GRASP are combined to solve the problem. In addition, a parallel scheme of EPSO is developed to improve the computational efficient as well as the accuracy. The effectiveness of the proposed method is tested in sample systems.

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In this paper a method to stabilize total output of PV systems by controlling on/off of each PV system is proposed. In the proposed method, the total output of PV systems is controlled so as to fit the output target value by determining off status of each PV system at each time interval when the amount of total power generation exceeds the output target value. Based on measured output of each PV system in instantaneos value, on/off status of each PV system is determined taking into account delay time of control. In order to check the validity of the proposed stabilization control method, the numerical simulations are carried out for a 100PV systems model. The effect of output fluctuation reduction is verified by changing the delay time of control. Furthermore, the utilization ratio and 30 minutes output deviation of PV systems are evaluated for various output target value.

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Lightning faults on transmission lines often cause instantaneous voltage drops in power systems. Influences of instantaneous voltage drops become increasingly serious in high technology industries etc. As countermeasures of instantaneous voltage drops, uninterruptible power supplies (UPS) are employed. On the other hand, line surge arresters are installed on transmission lines increasingly as one of the effective countermeasures of double-circuit faults caused by lightning strokes. Additionally, the arresters are effective as one of the reduction methods for the frequency of instantaneous voltage drops. In this paper, the frequency of instantaneous voltage drops reduced by installation of line surge arresters on transmission lines is estimated by employing EMTP analysis. Also, the accuracy of the method in estimating the frequency of instantaneous voltage drops in power systems is evaluated through comparison with experience.

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To investigate a stripe-shaped destruction mechanism of a ZnO element used for a surge arrester, some breakdown tests were carried out. Applying a large impulse current to a ZnO element, a flashover trace was confirmed at the lateral face of the element. It was found that a trace of a stripe-shaped destruction was formed by a fact that AC current flew through the trace due to the flashover caused by a large impulse current.

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