Calculation of load aggregator potential and peak regulation strategy based on longitudinal modified ARIMA

Abstract

In response to the exist problems such as the lack of accuracy in load forecasting leading to large errors in contracted power purchases, and the ambiguous market boundaries leading to duplication in assessment and settlement when load aggregators organize demand-side resources to participate in the peaking market and the electricity energy market, a load aggregator potential calculation and peaking strategy based on the longitudinal modified autoregressive integrated moving average (ARIMA) model is proposed. Firstly, the longitudinal modified ARIMA forecasting algorithm is applied to forecast the load baseline for obtaining the model of peak regulation potential of load aggregators, thus exploring the adjustable capacity of demand-sideresources to provide a database for power market trading. Secondly, the load deviation assessment method of electric energy market and peak shaving market is formulated, and the load aggregator peak shaving model considering the deviation assessment is constructed with the goal of maximizing the monthly rolling time domain comprehensive settlement income. Finally, the proposed method is analyzed based on the monthly historical load data of load aggregators in a typical region. The results show that the proposed load aggregator peak shaving strategy considering load deviation assessment can improve the peak shaving revenue of aggregators by about 23.7% and reduce the load aggregator peak-to-valley difference of about 10%, which verifies the rationality and effectiveness of the method.

Keywords

• adjustable potential
• longitudinal correction
• autoregressive integrated moving average (arima) model
• rolling optimization
• peak shaving strategy
• deviation assessment