Expansion Planning Method of the Industrial Park Integrated Energy System Considering Regret Aversion

Abstract

Industrial parks have various sources and conversion forms of energy. The many uncertainties in the planning of industrial park integrated energy systems (IPIES) pose a great risk of regret in planning schemes; thus, an expansion planning method for an IPIES, considering regret aversion, is proposed. Based on comprehensive regret value consisting of min–max regret aversion and the min average regret value, the method optimizes the comprehensive cost of the expansion planning scheme in IPIES under different natural gas price fluctuation scenarios, including costs of construction, operation and maintenance, and environmental protection. A multi-stage expansion planning scheme and typical daily operation plans under multiple natural gas price fluctuation scenarios of the IPIES in an economic and technological development zone in southeast China are used to demonstrate the validity of the method. The results show that, compared with a traditional planning method based on expectation, the proposed expansion planning method could reduce the maximum regret value by 14% on average, and greatly reduces the risk of decision-making regret by up to 18%. At the same time, the influence of natural gas price on expansion planning of the IPIES is discussed.

Multi‐scene upgrade and renovation method of existing park‐level integrated energy system based on comprehensive analysis

“…A universal energy-storage model [13] is used to describe the energy-storage mechanism of ES and HS, as shown in ( 4): Energy-storage equipment cannot store more energy than its capacity, whose charging and discharging power should be within the upper and lower limits. Its charging and discharging processes cannot be performed simultaneously, and its state of charge at the beginning and the end of the dispatch period is equal.…”

“…However, there are also many uncertainties to consider, which make the planning of PIES more difficult. The authors of [13] considered future gas price fluctuations and introduced the concept of regret aversion in the PIES planning model, which can effectively reduce the risk of decision making. The uncertainty set was constructed and analysed through machine learning, and a robust planning model was established in [14], which could reduce the operating cost of PIES and improve its robustness.…”

“…The structure of the existing PIES adopted by the case is shown in Figure 1. The equipment in the initial planning of the existing PIES (the existing equipment) includes CHP, HP, ES, and HS, and their capacities, and parameters are listed in Table A1 of the Appendix [13,31]. The time-of-use electricity price is adopted in the park [32], as shown in Table A2 of the Appendix, and the natural gas price is 0.24 Yuan/kWh.…”