Farnaz Sohrabi

Farnaz Sohrabi

Thesis title: Optimal planning of Power-to-Gas with high renewable energy penetration

M.Sc. period: 2016-2019

Supervisor: Dr. Behnam Mohammadi-Ivatloo

Advisor: Dr. Kazem Zare

Problems of traditional electricity energy sources, like pollution, global warming and climate change, as well as increases in energy demand and price, cause the substitution of conventional energy sources with renewable energy sources. The large fluctuation in the output power of renewable energy sources dependent on climate change may cause a mismatch between the generation and the consumption of electrical energy in peak time. Hence, energy storages play an important role in adjusting renewable energy generation by storing the excess energy in off-peak hours and releasing it in peak hours. So, determining the optimal size of energy storage is an important issue. In this thesis, optimal planning of power to gas with high renewable energy penetration is proposed from the perspective of the investor who seeks the maximization of the profit through determining the number of the electrolyzers and hydrogen tanks. The capability of storing energy for a long period with large capacity is the reason for selecting this kind of storage. Also, the produced gas can be distributed and stored in the existing natural gas system, which leads to a decrease in the investment cost by using existing infrastructure. Natural gas and electricity networks are coupled via gas-fired generation units and power to gas energy storage system. Coupled natural gas and electricity markets are used to carry out precise modeling where the power to gas facilities are considered as a strategic producer in the gas market and as a non-strategic demand in the electricity market. To make the planning problem linear and computationally tractable in the coupled gas and electricity markets, an iterative model is implemented using GAMS software, which decomposes the problem into a complementarity bilevel model and linear programming. In the bilevel model, the upper-level problem determines both the optimal investment and the offering price curves of the power to gas investors for increasing its profit, and the lower level problem describes the gas market clearing process with the goal of maximizing the social welfare. Replacing the lower level by their optimality conditions renders mathematical problems with equilibrium constraints. The strong duality theorem and Karush-Kuhn-Tucker (KKT) conditions are used to transfer the mathematical problem with equilibrium constraints into the mixed-integer linear programming. Linear programming models the electricity market clearing process where the electricity market operator seeks the maximization of the social welfare considering the submitted stepwise function offers by the coal, gas and wind generators. The simulation results for a 6-bus power system with a 7-node gas grid as well as an IEEE 118-bus power system with a Belgian high-calorific 20-node gas grid are demonstrated comprehensively.

Publications in journals and conference papers may be found at Publications Page or Google Scholar.