Multi-objective pinch analysis for power system planning

Highlights: •Formulation of Multiple Objectives Pinch Analysis (MOPA) problems proposed. •Analysis of multiple objectives prioritised cost to identify prioritising sequence. •Development of a graphical solution space for three objective optimisation problems. •Minimising cost, land footprint and water footprint for Indian power sector planning. •Generation of solution space and Pareto optimal front for the Indian power sector. -- Abstract: Given the rising levels of greenhouse gases and the dependence of power generation on fossil fuels, power system planning with emission constraint is of crucial importance. The objective of emission constrained power sector planning is to identify an optimal energy mix, capable of supplying the required amount of electrical energy while simultaneously keeping emissions within a predefined limit. Cost minimisation is the common objective in power sector planning. Additionally, the choice of one power plant over another involves considering a large number of social, environmental, and economic factors. A multi-objective approach is better suited to address such a complex problem. In this paper, Pinch Analysis, a single objective optimisation method, is modified to address multi-objective problems. It is then applied to simultaneously minimise the land footprint, water footprint, and capital cost associated with energy generation for the Indian power sector. A graphical solution space containing all Pareto optimal solutions for a three-objective problem is also presented. It is seen that for India, the energy mix is dominated by photovoltaic and carbon capture enabled coal power plants. The energy mix for least water footprint contains only photovoltaic power plants while that for least land footprint has a mix of wind, nuclear, small hydel, photovoltaic and biomass. Capital investment is the minimum when biomass and nuclear power plants, along with carbon capture enabled coal plants supply the demand, making biomass the only renewable to feature in the cost optimal mix. Existing coal power plants continue to supply over 35% of the energy requirements for the entire solution space. The overall results highlight the importance of solar PV and carbon capture technology.