In the competitive power market environment, the power grid company considers how to reduce the cost of power grid operation, maintenance, upgrade and addition as much as possible while providing safe, reliable and high-quality power services, so as to provide users with “high-quality and low-cost” power electrical energy. Energy storage technology is a means to achieve this goal. It can improve power quality, improve power supply reliability, and reduce costs by reducing transmission and distribution network capacity requirements, reducing system congestion, and delaying grid upgrades and additions.
When the load of a certain line exceeds its capacity, the distribution network needs to be upgraded or added. The traditional measures include upgrading or adding substation transformers, transmission and distribution lines, etc. With the development of energy storage technology and the decline of the unit cost of energy storage devices, energy storage devices are increasingly used in the power grid to improve the reliability of power supply and improve power quality. The advantage is being realized that the energy storage device can replace the aforementioned traditional grid upgrade measures to delay the investment in lines and transformers and realize a “wireless solution”. It is foreseeable that energy storage technology will be widely used in grid planning that pays more and more attention to profitability, which is considered on the basis of the continuous reduction of the cost of energy storage devices. Although economics play an important role in the widespread adoption of energy storage technology, other factors such as environment, technology, and policy are also important, and in some cases even decisive.
Traditional grid planning or grid upgrades and expansions are costly, especially in congested urban areas. If the load growth will exceed the load capacity of the distribution line, the grid company can use the smaller capacity energy storage device installed at the overload node to delay the larger capital investment brought by the upgrade of the transmission and distribution network. Consider a simple example. Suppose a 15MW distribution feeder is operating at 3% of the rated capacity, and the annual growth rate of the load is 2%. According to the traditional planning method, the feeder is planned to expand the capacity of 5MVA after one year. Now, planners can consider energy storage to balance load growth over the next year. Taking into account the uncertainty of load growth, a 25% capacity margin was added when determining the capacity of the energy storage device, and finally the energy storage device capacity that can delay the upgrade of the distribution network for one year is 375kW. In this example, it is also assumed that the energy storage device can guarantee a continuous discharge time of more than 2h. It can be seen that a smaller capacity (375kW) energy storage device can delay the larger distribution network investment (feeder capacity increase by 5MVA). This is beneficial to grid companies to reduce total costs, improve equipment utilization, allow funds to flow to other important engineering projects, and reduce the risk of large capacity expansion investments. May never be used.
Usually the following situations are suitable to use the method of building battery energy storage devices to reduce the expansion capacity of the power grid:
1) Overload situations are rare and only occur within a few hours of a day;
2) Slow load growth;
3) The upgrade of distribution network is expensive, and small-capacity energy storage can delay relatively large investment, and the “leverage” effect is obvious;
4) The traditional upgrade method does not work, such as wireless road corridors, and lines cannot be laid considering environmental and aesthetic factors.
The daily load peak-to-valley difference in Shanghai is relatively large, and the peak load duration is much longer than the load trough duration. Figure 1 shows the load curve of a typical day in Shanghai. The average daily load is 17 035MW. We can see that the load trough period is from 22:00 pm to 6:00 the next day, and the duration is about 7h. The average load during this period is 15 903MW; while the load changes very fast from the trough to the peak, the load peak period lasts for a long time, from 8:00 am to 21:00 pm, the duration is about 13h, the average load during this period reaches 17 707MW, the difference between the two It is 1804MW, and there are two peaks during the peak period: one is from 8:00 to 11:00 in the morning, and the other is from 13:00 to 18:00 in the afternoon.
During seasonal peak periods, the peak-to-valley difference in the grid is especially large, and the overall load is much higher than on a typical day. Figure 2 shows the load curve of the summer peak days in Shanghai, and the average daily load is 22 425Mw, which is 31.6% higher than that of typical days. The average load during the load trough period is 20 856MW, which is 31.2% higher than the typical day; the average load during the load peak period is 23 313MW, which is 31.6% higher than the typical day. The difference between the two is 2457MW, and the peak-valley difference is higher than the typical day. out 36.2%.
The power transmission and distribution capacity of the power grid generally needs to be planned according to the maximum load demand of the region. Therefore, when the power consumption is low, the load power is much lower than the capacity of the power grid, and when the extreme power consumption peaks, the load power will be close to the rated capacity of the power grid, or even part of the power grid. Substations and lines are overloaded. By installing BESS in the distribution network, the energy storage station can charge the battery when the power consumption is low, and the load rate of the power grid can be increased, and when the power consumption peaks, the stored electric energy can be released to the power grid, so that the partial load can be realized. It reduces the power transmitted in the transmission and distribution network, thereby reducing the planned capacity of the transmission and distribution network.
BESS can be equivalent to a peak-shaving power supply installed on the load side during its life cycle, but the maximum charging and discharging power of the energy storage device and the charging and discharging time under the maximum power affect its peak-shaving effect, because the peak load duration is longer than the valley Therefore, in terms of the operation of the energy storage device, it is necessary to charge the energy storage device with a larger current during the trough period to make full use of the shorter trough period; and during peak regulation, the discharge time needs to be extended to avoid To match the peak period with a longer duration, the discharge current is selected to be lower than the charging current. When the capacity of the energy storage device is too large and exceeds the critical value P. (the capacity required to completely adjust and straighten the load curve), the peak will be cut into a valley, and the valley will be filled into a peak. weaken. So its benefit E in reducing the capacity of grid expansion, (converted to the present value of each year according to its life cycle) can be expressed as
E1={λt&dCt&dηPmax Pmax ≤Pc
{λt&dCt&dη(2Pc-Pmax) Pmax>Pc
where Pc-critical power required to flatten the load curve, Pc=Pimax-Pa;
Ct&d – the unit cost of the user’s power distribution system (ten thousand yuan/MW);
λt&d – the fixed asset depreciation rate of the user’s power distribution equipment;
Pmax – the long-term maximum charge and discharge power of the battery pack (MW), that is, the rated power, Pmax =kP1;
P1 – average power at valley load;
k—-coefficient;
Pimax – maximum load (MW);
η–the energy storage efficiency of the energy storage device, including the loss of the grid-connected equipment and the charge and discharge loss of the battery;
Pa is the daily average power of a load.
The above formula shows that when the energy storage capacity achieves complete peak shaving and valley filling, the capacity of the energy storage system will continue to increase, and the peak will be shaving to the valley, and the valley filling will be the peak. , as shown in Figure 3, but in practical applications, the total capacity of the battery energy storage system will not exceed the critical value.
For the convenience of analysis, the above formula can be approximately equivalent to a quadratic function formula, as shown in the formula:
E1=(λt&dCt&dη/Pc)(-P²max+2PcPmax)