The task of designing a cost-effective future Net-Zero energy system for the UK or any other country/region is a complex one for multiple reasons. Many parties are addressing this problem and there are many different perspectives. Any proposed solution should appear satisfactory from all of those perspectives. Renewables (mainly wind turbines and photovoltaic panels) are now able to produce zero-carbon electrical energy at costs lower than any other source and it is becoming obvious that electricity will be the main energy carrier of the future. Thus, at the highest level, a country/region should be able to account for how it will balance the demand for electricity with the availability of resources to supply electricity over that entire country/region. The challenges of how to distribute electrical power within the country/region are not insignificant but it is sensible only to think about these distribution challenges after a clear view is in place for how to solve the top-level problem.
[NStore_sim] is a suite of MATLAB code-units (scripts and functions) whose primary function is to support the user in finding cost-effective solutions for the top-level problem. The user defines the expected future profiles of demand and supply. The user also inputs costs for the various options for generation and storage. The user can then find what multiplier of the preferred mix of inflexible generation is necessary with a particular set of storage and flexible generation assets to produce a system that is “acceptable”. The costs for that system are then calculated. Building on that functionality, [NStore_sim] then enables the user to discover what combination of parameters describing the storage and flexible generation assets will provide the lowest cost system that is “acceptable”.
[NStore_sim] is intended to bring transparency and clarity to the problem of energy system design. Overall system cost is highly important but it may not be the only consideration in the recommendation of any one system design. The ability to realise the solution quickly, the ability to protect the system once it is built and the resilience of the system operation to external events are each important. Policy-makers and policy-proponents should be able to explain their recommendations in terms of time-series data, cost assumptions and enumeration of the other considerations. [NStore_sim] provides both a tool for the policy-makers/proponents and for the energy-consumer/taxpayer/voter alike.
DISCLAIMER: [NStore_sim] is a gift to the Energy Storage community that may potentially be helpful in decision-making.
Users must take full responsibility for all aspects of their own decision making and for checking both results and input data.