Now showing 1 - 2 of 2
  • Publication
    Modelling demand response with process models and energy systems models: Potential applications for wastewater treatment within the energy-water nexus
    A promising tool to achieve more flexibility within power systems is demand response (DR). End users in many strands of industry have been subject to research regarding the opportunities for implementing DR programmes. We review recent DR modelling approaches in the realm of energy systems models and industrial process models. We find that existing models over- or underestimate the available DR potential from an industrial end user for two main reasons. First, the interaction between power system operation and industrial process operation caused by DR is not taken into account. Second, models abstract from critical physical process constraints affecting the DR potential. To illustrate this, we discuss the wastewater treatment process as one industrial end user within the energy-water nexus, for which the lack of suitable modelling tools is affecting the accurate assessment of the DR potential. Case studies indicate the potential for wastewater treatment plants to provide DR, but no study acknowledges the endogeneity of energy prices which arises from a large-scale utilisation of DR. Therefore, we propose an integrated modelling approach, combining energy system optimisation with the level of operational detail in process simulation models. This will yield a higher level of accuracy regarding the assessment of DR potential from a specific process, such as wastewater treatment.
      35Scopus© Citations 47
  • Publication
    The role of power-to-gas in the future energy system: Market and portfolio effects
    Electricity systems based on renewables have an increasing demand for flexibility. This paper considers the potential of power-to-gas to provide flexibility and enhance system integration of renewables. Existing research on power-to-gas typically analyses the system effects of a predetermined power-to-gas unit without endogenising the investment decision. Moreover, insights related to market and portfolio effects of power-to-gas are rare. To this end this work presents a stochastic electricity market model. Market players considered include generating firms with different generation portfolios and different consumer groups. Firms earn revenues from an energy market, a capacity market and a feed-in premium for renewable generation. They maximise their profits by optimising the operation of existing assets and investing in new generation assets and power-to-gas. Firms with renewable generation benefit from investing in power-to-gas. While the technology itself is loss-making, power-to-gas particularly increases demand and hence prices in low-load hours. Therefore, renewable generation becomes more profitable, which justifies the investment. Metrics such as LCOE, which consider each technology in isolation, fail to capture this effect. The increase in the electricity price results in higher costs to consumers and so the overall transfer from consumers to wind generators increases in the presence of power-to-gas.
      466Scopus© Citations 34