Purpose: The intermittence of renewable energy sources is a substantial barrier to investments. This issue has conventionally been addressed by governmental policies such as feed-in tariffs (FiT). The purpose of this paper is to assess the effectiveness of these policies and the implications for investments in renewable energy systems, with a specific focus on systems where hydrogen storage systems are emerging as a viable option. Design/methodology/approach: A quantitative modelling approach is used to analyse a real-life case study considering renewable energy investments staging options versus an upfront investment. Findings: The main finding of the paper is that FiT policy is of little importance when storage is used, as the storage hedges weather related risk for customers. If the microgrid does not have local storage, or still exports substantial amounts of power, then FiTs are still needed. This implies that policies need updating as the energy sector evolves and the type of support needed becomes more sensitive to microgrid design. Research limitations/implications: Simplifications were made when modelling weather. Normal weather volatility is accounted for, but not large-scale unusual weather patterns. Originality/value: The paper provides new insights about using real options theory in a context of increasing uncertainty when complementarity between assets exist. It also argues that the historical “one size fits all” design of FiTs policies is ineffective for the future.

Substantial breakthroughs in renewable energy have been made in order to reduce energy-induced climate change. Yet our reliance on these sources is still insufficient. The UK’s objective of attaining net-zero emissions by 2050 is highly dependent on shifting to an electrical system that exclusively relies on zero-carbon generation. This entails integrating renewable energy sources, along with other low-carbon sources such as nuclear power, into the energy mix. However, the primary barrier to incorporating additional renewable energy sources into the grid is their intermittent and volatile nature. Therefore, there is a pressing need to stabilise the generation of renewables and manage this volatility by enhancing the balancing mechanism between microgrids and the national grid. This paper examines previous research on microgrids and smart grids, specifically from a supply chain perspective. It has been observed that the majority of the current literature focuses on documenting selfish microgrids that strive to optimise performance at the microgrid level. However, there is an alternative approach that draws inspiration from the field of supply chain management. Consequently, it is possible to enhance a microgrid’s performance within the broader system that it belongs to by reconsidering the timing and location of storage utilisation.

The United Kingdom seeks to achieve net-zero emissions by 2050, mostly via the shift to an electrical system exclusively powered by zero-carbon sources. Microgrids (MGs) can be seen as an effective system for integrating renewables into the energy portfolio. Nonetheless, MGs face the acknowledged obstacle of backup power generation due to the intermittent nature of renewable energy sources, necessitating the establishment of backup power generation capacity. This paper contrasts selfish power generation, where the MG pursues complete energy autonomy, with an alternative influenced by lean principles (Heijunka production), which seeks to stabilise power transactions within the national electricity supply chain, reduce emissions, and tackle the backup generation challenge. This study proposes a pre-contractual order update (COU) strategy for the operation of hybrid collaborative MG where a forward order update to the utility grid is placed, in contrast to selfish MG, which uses a spot order update strategy. The COU strategy was defined, and two simulation models (for selfish and collaborative MG) were developed, each incorporating four backup generation scenarios to illustrate the method’s efficacy by assessing the system’s critical performance metrics. It has been found that the collaborative MG model reduced the carbon emissions by 62% and the volatility of unplanned orders to the grid by 61% compared to the selfish model in the first scenario (grid-dependent MG). Furthermore, the MG achieved zero volatility and a 33% reduction in carbon content in the collaborative MG when using the H₂ burner as backup generation compared to the first scenario. Indicating that sustainability encompasses not only the use of renewable resources but also the stability of their outputs through the implementation of collaborative MGs.

This paper explores the integration of microgrids within utility networks and distinguishes selfish from collaborative microgrids. Research has shown that selfish microgrids tend to increase volatility of order updates to power generators, whereas collaborative microgrids decrease that volatility, resulting in smoother, more controllable operations of networks. This paper proposes an analytical formula linking power volatility to power quality, i.e., to issues such as voltage dips, surges, and transients. These are known risks for disrupting the operation of utility grids, causing instability and jeopardising efficiency and reliability. As collaborative microgrids reduce volatility, they improve power quality. That argument is extended to propose that collaborative microgrids can act as quality improvements agents within wider networks.

The volatility of renewable energy outputs is a well-known obstacle that has hindered the integration of more renewables in the UK’s energy mix, as the current network was not designed to handle such swings. Microgrids (MGs) may function as an effective means of integrating more renewables, particularly if they can effectively control the volatility of renewables at a smaller scale (the MG level) through a collaborative operational strategy. This paper focuses on the management of renewable energy fluctuations in MGs, proposing a pre-contract order update (COU) strategy based on the lean balancing (Heijunka) concept. The study compares the performance of collaborative and selfish MGs in terms of levelized cost of electricity (LCOE), order volatility, and carbon emissions. Two simulations models for the collaborative and selfish MGs were implemented, while considering two distinct backup generation scenarios within the MG system. The findings indicate a two-dimensional trade-off between the collaborative MG models, which are 61% more sustainable and reduce order volatility to the utility grid by 55%, and the selfish MGs, which incur lower energy consumption costs reduced by only 19%. These findings highlight the potential of collaborative MGs in enhancing grid stability and supporting broader renewable energy integration goals.