Regulatory capital and social trade-offs in planning of smart distribution networks with application to demand response solutions

• An approach for distribution network reinforcement planning is proposed.
• The approach models and regulates trade-offs between capital and social costs.
• Under current practices, significant expenses may be incurred to mitigate emissions.
• More efficient investments can be achieved if trade-offs are explicitly modelled.

Under the current UK regulatory framework for electricity distribution networks, asset upgrades are planned with the objectives of minimising both capital costs (and thus customer fees) and social costs such as those associated with carbon emissions and customer interruptions. This approach naturally results in economic trade-offs as network solutions meant to reduce social costs typically increase (sometimes significantly) capital costs, and vice versa. This can become an issue in a smart grid context where new operational solutions such as Demand Response (DR) may emerge. More specifically, even though there is a general belief that smart solutions will only provide benefits due to their potential to displace investments in costly assets (e.g., lines and substations), they may also introduce trade-offs associated with increased operational expenditure, power losses and emissions compared with networks with upgraded assets. On the other hand, the flexibility inherent in smart solutions could be used to balance the different types of costs, leading to attractive cost trade-offs if properly modelled, quantified and regulated. However, given the fundamental “non-asset” nature of DR, properly quantifying the resulting trade-offs so as to perform a like-for-like comparison with traditional planning strategies is a grand challenge. In this light, this article proposes a methodology to explicitly model and quantify capital and social cost trade-offs in distribution network planning, which can be incorporated into the existing regulatory framework. The results, based on real UK distribution networks, show that our proposed methodology can be used to explicitly model and regulate cost trade-offs. By doing so, it is possible to encourage more efficient levels of capital expenditure and social benefits by deploying the right mix of traditional asset-based and smart DR-based solutions.