Modelling of Battery Storage for Future Power Production

The results of this study will assist policy makers on installing battery storage system to capture the unused renewable energy at low demand times for future use under various carbon tax scenarios, fuel prices, and so on.

IMPACT OF BATTERY STORAGE ON GHG EMISSIONS AND NATURAL GAS TRANSMISSION AND CONSUMPTION FOR POWER PRODUCTION IN 2030

Parties to the Paris Agreement has agreed on capping the global temperature increase at 1.5°C via rapid and deep decarbonization based on science and equity. Intergovernmental Panel on Climate Change (IPCC) Assessment Report 5 (AR5) has articulated a robust outcome that the main determinant of multi-century global warming is the total cumulative net quantity of further CO2 that is released leading to a finite cumulative limit or Global Carbon Budget (GCB) on CO2 emissions. So, before that limit is surpassed, net CO2 emissions should fall to zero; or, if overruns, net CO2 removal will be essential. The main technological options for climate change mitigation are energy efficiency, deployment of clean and renewables and carbon capture, storage, and utilization (CCSU).

The large use of renewable energy resource needs energy storage at low demand times for future use. The variability of wind and solar power affects the natural gas demand of gas-fired power plants. The objective of this project is to model a national electricity network with energy storage. The argument is mainly around the economics of energy storage (close to generation sites) in batteries and whether it results in lower GHG emissions and cheap electricity for the public. For this purpose, a fine time resolution (e.g. hourly) will be used. The objective function of the optimization problem minimizes the summation of hourly operating costs for energy storage and generators as well as unserved energy penalty and CO2 emission price (with and without storage) for various CO2 tax prices for the period of 2021-2030. The constraints of the optimization problem are ramp-up and ramp-down, power balance constraints, lines power transmission limit, startup and shut down cost, minimum uptime and downtime, the input-output balance of storage system, etc. The whole energy system optimization problem will be solved for the given time period.

Given: a planning horizon, available G generators and S storage options, the network topology and capacity constraints, in addition to the electricity demand and weather.

We will determine: The power outturn of generators, the transmitted power profile over each transmission line, thermal units’ start-up and shutdown times, marginal cost of each generator and storage system, energy storage, and the variability of wind and solar power on natural gas demand of gas-fired power plants and GHG emissions. We will perform a sensitivity analysis of several parameters including fuel price, storage system size, time resolution, carbon tax, several levels of electrification of heat sector, etc. on: the security of power supply, GHG emissions, cost of delivered electricity, natural gas demand for power generation, power trade between Germany and the neighbors, and other performance indicators of the system.

The results of this study will assist policy makers on installing battery storage system to capture the unused renewable energy at low demand times for future use under various carbon tax scenarios, fuel prices, and so on. With the future addition of wind/solar generators, the impact of storage will be further improved.