A market characterized by economic uncertainty and increased competition has led industrial enterprises to find ways to improve operational efficiency and reduce energy costs. In this context, the Demand Response (DR) has drawn ever greater attention from industries, allowing the shift of the electricity usage from their normal consumption patterns in response to changes in the price of electricity over time. This study proposes an innovative control strategy for renewable-based Load Shifting (LS) system designed on, at the same time, energy, economic, and environmental performance to realize an effective DR for industrial enterprises. The proposed techno-economic model is based on power flow management, economic indicators, such as NPV, IRR, and DPP, and associated CO2 emissions, adopting both deterministic and stochastic approaches. A realistic government incentive program framed in a potential carbon-based market is also assessed and validated. The resulting solution is obtained through a sensitivity analysis of several parameters, including the operating conditions of 15%, 20%, 30%, 35%, and 45% LS. MATLAB-Simulink simulations provide the following sizes for both storage and photovoltaic systems of 38, 68, 87, 115, 153 kWh and 18, 18, 32, 43, 61 kWp, respectively. Results show the profitability of the proposed DR, with a payback period that ranges from 6 to 10 years and within 3 years when incentives are considered. NPV and IRR range from 34,261 to 101,428 € and from 7% to 15.9%, respectively. The amount of CO2 emissions is reduced up to 47.7% for the highest LS percentage. Finally, the investigated incentive program led to CO2 prices between 18.2 and 551.9 €/tonCO2. Finally, results from the stochastic analysis show a good consistence with deterministic results.

Renewable-based load shifting system for demand response to enhance energy-economic-environmental performance of industrial enterprises

Michele De Santis
2024

Abstract

A market characterized by economic uncertainty and increased competition has led industrial enterprises to find ways to improve operational efficiency and reduce energy costs. In this context, the Demand Response (DR) has drawn ever greater attention from industries, allowing the shift of the electricity usage from their normal consumption patterns in response to changes in the price of electricity over time. This study proposes an innovative control strategy for renewable-based Load Shifting (LS) system designed on, at the same time, energy, economic, and environmental performance to realize an effective DR for industrial enterprises. The proposed techno-economic model is based on power flow management, economic indicators, such as NPV, IRR, and DPP, and associated CO2 emissions, adopting both deterministic and stochastic approaches. A realistic government incentive program framed in a potential carbon-based market is also assessed and validated. The resulting solution is obtained through a sensitivity analysis of several parameters, including the operating conditions of 15%, 20%, 30%, 35%, and 45% LS. MATLAB-Simulink simulations provide the following sizes for both storage and photovoltaic systems of 38, 68, 87, 115, 153 kWh and 18, 18, 32, 43, 61 kWp, respectively. Results show the profitability of the proposed DR, with a payback period that ranges from 6 to 10 years and within 3 years when incentives are considered. NPV and IRR range from 34,261 to 101,428 € and from 7% to 15.9%, respectively. The amount of CO2 emissions is reduced up to 47.7% for the highest LS percentage. Finally, the investigated incentive program led to CO2 prices between 18.2 and 551.9 €/tonCO2. Finally, results from the stochastic analysis show a good consistence with deterministic results.
File in questo prodotto:
Non ci sono file associati a questo prodotto.

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11591/516828
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 3
  • ???jsp.display-item.citation.isi??? 1
social impact