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A demand and supply simulator is developed to evaluate the effectiveness of various countermeasures against the balancing problems caused by the large integration of variable renewable energy sources (VRES). In our study, photovoltaic and wind power generation output pattern is modeled based on the actual data obtained at physical sites and forecast data from Japanese Meteorological Agency (JMA), to realistically reflect their fluctuation characteristics. One of the benefits of our digital simulator is that it reflects the typical Japanese central dispatching control center's methodologies including week-ahead, day-ahead, and hour-ahead scheduling process based on the latest forecast data available on each time horizon. Above all, not only PV output curtailment but also demand shifting and utilization of battery storages are taken into consideration. In conclusion, PV output curtailment is found to be the most cost-effective in many cases, still there is a room for batteries to be economical when CO 2 emission cost spikes.

We have developed an innovative power generation scheduling method using quadratic programming (QP). The advantage of using our method is that it simultaneously solves unit commitment and economic load dispatch. We relax the binary variables of the unit state into continuous variables to apply QP to this problem. We also add a penalty term to converge the value of those variables to 0 or 1 to the objective function: the sum of the fuel costs and the start-up costs. This penalty term depends on the per-unit fuel cost. The possibility of its variable converging to zero increases as the cost increases. This method was applied to a test system of daily generation scheduling that consisted of 29 thermal units, two pumped-storage units, four cascaded hydro units, and one transmission. The schedule satisfied all constraints, that is, load-power balance, operation reserve, power flow, minimum up/down-times, and fuel consumption. This result shows that the proposed method is effective. © 2011 Wiley Periodicals, Inc. Electr Eng Jpn, 175(1): 25–34, 2011; Published online in Wiley Online Library (wileyonlinelibrary.com). DOI 10.1002/eej.21014

A fast, innovative matching method for the spot power market, considering network constraints, has been developed. In this method, buy and sell order bids are respectively divided into the aggregated volume of several band prices. Then, the aggregated volume and the center of each band price are used to calculate an index band clearing price, which contains the real clearing price. The division and calculation process is iterated until the band price is less than the tick size of the bidding price. This method is applied to a real problem in the Japan power market, with 9 bidding areas, 10 area-connecting lines, and 9000 orders (volume/price pairs). Numerical simulation results show that the new method is ten times faster than conventional linear programming, demonstrating the effectiveness of this method. © 2008 Wiley Periodicals, Inc. Electr Eng Jpn, 165(4): 21–29, 2008; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/eej.20694

We have developed a fast, innovative matching method for the spot power market, considering network constraints. In this method, buy and sell order bids are respectively divided into the aggregated volume of several band prices. Then the aggregated volume and the center of each band price are used to calculate a band clearing price, which contains the real clearing price. The dividing and calculating process is iterated until the band price is less than the tick size of the bidding price. We applied this method to a real problem in the Japanese power market with 9 areas, 10 area-connecting lines, and 9000 orders (volume/price pairs). Our simulation results show that the new method is ten times faster than conventional linear programming. This demonstrates the effectiveness of the developed method.

To reduce boiler fuel cost, a fuel cost model is developed and applied to economic load dispatch (ELD). The purpose of ELD is to determine the power demands of individual generators so that total fuel cost of those generators may be minimized. In evaluating the fuel cost of each generator, an approximate model, which describes the fuel cost as a function of the generation, is used. Therefore, the accuracy of the model has a great influence on the preciseness of the minimization. So far, one of the most prevailing models has been a quadratic model, which describes the fuel cost as a quadratic function of the generation. However, this model often deviates from the actual data, especially during the time while the generation is dynamically varying. This fact implies that, if a model, which is accurate even when the generation dynamically varies, is developed and the model is applied to ELD, the total fuel cost can be reduced. First, taking into account that the deviation might be due to the dynamics of the automatic boiler controller (ABC), we employed as a supplementary model the autoregressive moving average (ARMA) model, which is capable of describing dynamics and is suitable for an on-line ELD calculation. Second, the ELD problem based on the ARMA-model-supplemented quadratic model is formulated as a quadratic programming (QP) problem, which can be solved by the standard QP method. Finally, the cost reduction effect is evaluated by computer simulations on Kansai Electric Power System.

This paper presents an economic dispatching method, BEST method , where BEST is short for Boiler-dynamics-based Economic load diSpaTch. Because this method is based on dynamics models more accurate than the conventional quadratic ones, it can reduce boiler fuel cost. First, to reduce the model deviations from the actual data, the autoregressive moving average (ARMA) model is employed. Second, an economic dispatching problem based on this model is formulated as a quadratic programming (QP) problem. Finally, the cost reduction is evaluated by computer simulations.