As PV Tech Storage reported at the end of July, Consolidated Edison, one of the largest investor owned utilities in the US, is seeking to stave off the need to invest US$1 billion in infrastructure spending on a substation, using a request for demand side measures that are likely to include storage. Dean Frankel of Lux Research explains Con Edison's plan in depth.
One of the U.S.'s largest investor-owned energy utilities, Consolidated Edison (Con Edison), is planning to spend US$200 million on demand reduction technologies. Con Edison has filed a proposal with the New York Public Utilities Commission for a Brooklyn/Queens Demand Management Program (BQDM) that it hopes can defer the US$1 billion cost of building a new substation and expanding two existing ones. The demand reduction program is projected to cost US$200 million, and will include 52 MW of demand reduction technologies across utility-owned distribution assets and customer-side resources. Con Edison is seeking to implement 41 MW of customer-side demand reduction by 2018 for a total cost of $150 million, and 11 MW of utility-owned demand reduction for US$50 million.
Con Edison, one of the largest investor-owned utilities in the US, has filed the request for the Brooklyn/Queens Demand Management Program. Image: wikimedia user: Dr G.Schmitz.
If it does nothing, Con Edison expects that by 2018 the aforementioned region's electric demand will grow to 69 MW above the system's current capabilities, overloading the grid for 40 hours to 48 hours per year. The BQDM program aims to address a 12-hour peak lasting from noon to midnight targeted to reduce base demand of buildings. Unlike previous demand response initiatives from Con Edison, the BQDM program will focus on traditional efficiency and demand measures in addition to increasing the use of controllable distributed energy resources such as distributed generation and storage. Included in the offerings will be incentives to encourage greater use of controls, storage, distributed generation, and microgrids. Con Edison included two utility-owned energy storage systems with a collective 3 MW / 36 MWh capacity. The utility recognizes that its energy requirement is onerous for battery developers, and believes it may need three battery banks, each with four hours of storage capacity. The long duration requirement extends beyond the typical capabilities of battery architectures, even flow batteries, but developers who believe they can cost-effectively meet the 12-hour charge and discharge capacity should engage.
The Con Edison programme seeks to defer huge amounts of required investment in ageing electrical infrastructure. Image: wikimedia commons user: Vivan755
If successful, the Con Edison BQDM program will defer transmission capital investments until at least 2024, and will set an industry example of how two-way distributed demand management resources can be a grid reliability asset. This proposal comes after Con Edison has already announced its intention to double the price paid for demand response resources, and the utility is currently implementing a 125 MW demand reduction program in Manhattan to meet capacity concerns (see the February 18, 2014 LRESJ). However, despite proposing to defer US$1 billion in infrastructure improvement costs, the program is still relatively expensive at US$200 million for just 51 MW of demand resources (that is, US$3.85/W of demand reduction). This high cost is partly due to the customer distribution in the proposed region, which has a low average load. In turn, Con Edison must sign up a large number of customers to meet its 41 MW customer-side resource quota.
The relatively short duration of over-demand risk - just 40 hours to 48 hours per year - highlights the folly of building expensive generation and transmission infrastructure to just meet peak demand. Con Edison correctly recognizes that flexible resources can help mitigate this, further buttressing Lux Research's take that transmission and distribution deferral remains one of the strongest incentives for stationary energy storage and demand-side resource deployment.