Strategic Capacity Planning in the Energy Sector
Lead Research Organisation:
University College London
Department Name: Chemical Engineering
Abstract
The proposed research will lead to the development of an optimization-based framework for the strategic planning of energy production. The novelty of the proposed approach lies in: (i) the simultaneous consideration of aspects such as technology change, distributed potential of renewable resources, infrastructure constraints, and environmental regulations; and (ii) the modeling of multiple sources of uncertainty. While the methods we will develop will be general, our initial efforts will focus on the production of liquid fuels from renewable resources.
Planned Impact
In this project, optimisation-based methods will be developed that can potentially increase the ability of the energy industry to generate alternative capacity plans subject to techno-economic uncertainty thus resulting in reduced capital/infrastructure and operating costs. In addition, the proposed research has the potential to lower the environmental impact of power and fuel generation.
Knowledge
The proposed framework will identify limitations of existing energy technologies and thus point towards promising directions where additional developments in basic sciences are needed. For example, our systems-level studies will offer insights into the bottlenecks of biomass-to-fuels conversion technologies. Therefore, experimental researchers in chemical and biological catalysis working in the area of biofuels will benefit from this research. Prof Maravelias has multiple collaborations with researchers in these fields.
Furthermore, this project will lead to the development of methods for the effective modeling and solution of a broad class of optimization problems, namely, optimisation problems under endogenous observation of uncertainty. This class of problems appears in a wide range of strategic planning applications, ranging from oilfield exploration to planning of research and development activities. Thus, the theory and methods developed in this research will benefit multiple industrial sectors, as well as the mathematical programming community (researchers in the area of optimization under uncertainty).
Economy
The work described in this proposal has the potential to lead to better planning methods for energy generation planning, which in turn will result in better infrastructure decisions (in terms of technology selection), as well as reduced capital and operating costs. Thus, it will benefit the energy sector and the (energy intensive) process industries, as well as the economy as a whole through the lower energy cost.
People
Optimisation has emerged as a key enabling technology in chemical engineering. Optimization methods originally developed in academia during the last 20-25 years have gradually been introduced in the chemical and process industry and are having a significant impact, while optimization methods have been successfully applied in new areas such as computational biology and molecular design. Thus, the students that will work on the research projects that will arise from this collaboration will be trained to model, analyse and solve complex problems related to capacity planning in energy and process sectors.
Society
The proposed research can potentially address the increasing gap between energy consumption and domestic production. Thus, it has the potential to benefit not only the energy sector and the process industries, but also the overall economy via the macroeconomic impact of inflation and interest rates, the standard of living via reductions in energy costs, and the national security because the oil imports used to cover this shortfall come from unstable regions of the world.
Knowledge
The proposed framework will identify limitations of existing energy technologies and thus point towards promising directions where additional developments in basic sciences are needed. For example, our systems-level studies will offer insights into the bottlenecks of biomass-to-fuels conversion technologies. Therefore, experimental researchers in chemical and biological catalysis working in the area of biofuels will benefit from this research. Prof Maravelias has multiple collaborations with researchers in these fields.
Furthermore, this project will lead to the development of methods for the effective modeling and solution of a broad class of optimization problems, namely, optimisation problems under endogenous observation of uncertainty. This class of problems appears in a wide range of strategic planning applications, ranging from oilfield exploration to planning of research and development activities. Thus, the theory and methods developed in this research will benefit multiple industrial sectors, as well as the mathematical programming community (researchers in the area of optimization under uncertainty).
Economy
The work described in this proposal has the potential to lead to better planning methods for energy generation planning, which in turn will result in better infrastructure decisions (in terms of technology selection), as well as reduced capital and operating costs. Thus, it will benefit the energy sector and the (energy intensive) process industries, as well as the economy as a whole through the lower energy cost.
People
Optimisation has emerged as a key enabling technology in chemical engineering. Optimization methods originally developed in academia during the last 20-25 years have gradually been introduced in the chemical and process industry and are having a significant impact, while optimization methods have been successfully applied in new areas such as computational biology and molecular design. Thus, the students that will work on the research projects that will arise from this collaboration will be trained to model, analyse and solve complex problems related to capacity planning in energy and process sectors.
Society
The proposed research can potentially address the increasing gap between energy consumption and domestic production. Thus, it has the potential to benefit not only the energy sector and the process industries, but also the overall economy via the macroeconomic impact of inflation and interest rates, the standard of living via reductions in energy costs, and the national security because the oil imports used to cover this shortfall come from unstable regions of the world.
Organisations
People |
ORCID iD |
| Lazaros Papageorgiou (Principal Investigator) |