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- W4239949396 abstract "This chapter discusses the autoregressive moving average with exogenous inputs (ARMAX) model which is selected as the forecasting model and the parameter identification algorithm for combined cooling, heating, and power (CCHP) Systems, including instrument variable (IV), two-stage recursive least squares (TSRLS), and ordinary least squares (OLS)-TSRLS. It briefly introduces load forecasting. The chapter explains two steps of the operation strategy design, including the optimal operation strategy for forecasted loads and the post-strategy. It presents a case study to verify the feasibility and effectiveness of the proposed forecasting method and post-strategy. IV is introduced into the identification procedure to solve the problem of inconsistent OLS identification results caused by omitted variables or the correlation between explanatory variables and error terms. The chapter provides derivations of the closed-form solutions of quadratic autoregressive moving average (ARMA) and ARMAX model identifications." @default.
- W4239949396 created "2022-05-12" @default.
- W4239949396 date "2017-07-07" @default.
- W4239949396 modified "2023-10-12" @default.
- W4239949396 title "Short‐Term Load Forecasting and Post‐Strategy Design for<scp>CCHP</scp>Systems" @default.
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- W4239949396 doi "https://doi.org/10.1002/9781119283362.ch5" @default.
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