A two-phase stochastic programming approach to biomass supply planning for combined heat and power plants

TL;DR

This paper introduces a two-phase stochastic programming method to optimize biomass supply planning for combined heat and power plants, accounting for uncertainties in demand, prices, and supply contracts to improve profitability and feasibility.

Contribution

It presents a novel two-phase stochastic optimization approach that jointly plans biomass contracts and plant operations under uncertainty.

Findings

Effective in handling multiple uncertainties in biomass supply and demand.

Improves profitability and operational feasibility of CHP plants.

Validated on two realistic case studies.

Abstract

Due to the new carbon neutral policies, many district heating operators start operating their combined heat and power (CHP) plants using different types of biomass instead of fossil fuel. The contracts with the biomass suppliers are negotiated months in advance and involve many uncertainties from the energy producer's side. The demand for biomass is uncertain at that time, and heat demand and electricity prices vary drastically during the planning period. Furthermore, the optimal operation of combined heat and power plants has to consider the existing synergies between the power and heating systems. We propose a solution method using stochastic optimization to support the biomass supply planning for combined heat and power plants. Our two-phase approach determines mid-term decisions about biomass supply contracts as well as short-term decisions regarding the optimal production of the producer to ensure profitability and feasibility. We present results based on two realistic test cases.