Assessing the Effects of Uncertain Energy and Carbon Prices on the Operational Patterns and Economic Results of CHP Systems

Abstract

In the power and heat sectors, the uncertainty of energy and carbon prices plays a decisive role in the rationale for decommissioning/repurposing coal-fired CHP (combined heat and power) systems and on investment decisions of energy storage units. Therefore, there is a growing need for advanced methods that incorporate the stochastic disturbances of energy and carbon emission prices into the optimization process of an energy system. In this context, this paper proposes an integrated method for investigating the effects of uncertain energy and carbon prices on the operational patterns and financial results of CHP systems with thermal energy storage units. The approach combines mathematical programming and Monte Carlo simulation. The computational process generates feasible solutions for profit maximization considering the technical constraints of the CHP system and the variation of energy and carbon emission prices. Four scenarios are established to compare the operational patterns and economic performance of a CHP system in 2020 and 2030. Results show that in 2020, there is an 80% probability that the system’s annual profit will be less than or equal to €30.98 M. However, at the same probability level, the annual profit in 2030 could fall below €11.88 M. Furthermore, the scenarios indicate that the incorporation of a thermal energy storage unit leads to higher expected profits (€0.74 M in 2020 and €0.71 M in 2030). This research shows that coal-fired CHP plant operators will face costly risks and potentially greater challenges in the upcoming years with the increasing regulatory and financial pressure on CO2 emissions and the EU’s plan of phasing out fossil fuels from electricity and heat generation.

Models of Electricity Price Forecasting: Bibliometric Research

“…The transformation processes have been challenging the "traditionally monopolistic and government-controlled power sectors" [9]. This change also influences energy prices [10,11] and Electricity Price Forecasting (EPF) procedures [9,12] and models [13,14]. On the other hand, the mathematical models that predict what electricity prices will be in the future are important not only for the electricity produces [15,16] but also for their clients [17,18].…”