Low Carbon Economy Under Considering Block Bidding Algorithm Of Pumped Storage Power Station

Right now because of our economic’s development, peak and valley loads becomes larger and larger. The pumped storage plants can reduce the peak loads and increase the valleys loads. Now it becomes the important peaking power, phase modulation, frequency modulation and backup source. But in the power market, pumped—storage plants will decide the electricity price to maximize their profits. So how to chose a proper bidding algorithm and operation mode to make sure both the power plant and electric network’s benefit is worth to do some research.The thesis introduce the low-carbon economy and the electricity market. And then the paper presents the theory of the hourly bidding rule and the block bidding rule. The two bidding rules are compared in detail. The thesis analysis the shortcoming of the hourly bidding rule, and the block bidding rule fit the low-carbon economy in our country. The third section in this thesis focus on the effect which the pumped storage plant can reduce the consumption of the coal based on the theory of the pumped storage. And it points out it Necessary to build the pumped storage plant in our country.On the base of these theories the thesis electricity market algorithm considering pumped-storage plant based on block bidding model is presented. Block bidding model not only conform the feature of the electricity, but also has a higher efficiency. In this algorithm, the system use the principle that the pumped storage units coordinate the thermal power units and arrange the operation mode of the pumped storage at the daily load curve firstly. The pumped storage plants use the cheap valleys electricity to store the water into the upper reservoir, and then at the peak loads the plant release the water to make electricity. The thermal power plant operate the new daily load curve. The pumped storage can get its benefit by the difference between sale incomes at peak blocks and purchase costs at valley time blocks. And its reducing the peak loads and increasing the valleys loads help the thermal power plant to reduce the energy consumption. At last, the test examples suggest that this algorithm could assure cheaper prices of electric power, and could show the rationality of the proposed method.