Economic analysis of using excess renewable electricity to displace heating fuels

AbstractRecent work has shown that for high-penetration renewable electricity systems, it is less expensive to install higher capacity of renewables and to allow generation to exceed load during some hours, rather than to build so much storage that all electricity can be used to meet electrical load. Because excess electricity appears to be cost-optimum, this raises the question as to whether the excess electricity, which in the case of wind power is predominately produced in colder weather, might displace other fuels for purposes such as heat. This study models using excess electricity for heating, based on an analysis of electricity and heat use in a TSO in the North-Eastern part of the United States (PJM Interconnection). The heating system was modeled as heat pump based district heating (HPDH) with thermal energy storage (TES). Thus, excess electricity is transformed into heat, which is easy and cheap to store near the point of use. As an alternative to HPDH, the use of distributed electrical resistive heating coupled with high temperature thermal storage (HTS) was also assessed. In both cases, a natural gas fired boiler (NGB) was modeled to be installed in the building for back-up heat. An algorithm that calculates the total cost of a unit of heat was used to determine the economically optimal size of the system’s main components and the influence that natural gas (NG) and electricity prices have on this optimum. It was found that a system based on heat pumps (HP) and centralized thermal storage supplies building heat at a lower or similar cost than conventional systems. In most cases electric resistive heating with HTS was found to be less cost-effective than HPDH. The consumption of natural gas can be reduced to as little as 3% of that used by an entirely NG-based heater. Also, thermal energy storage was found to be crucial when it comes to reducing the need for fossil fuels for heating (in this model, as backup heat)

Assessment of grid-friendly collective optimization framework for distributed energy resources

Distributed energy resources have the potential to provide services to facilities and buildings at lower cost and environmental impact in comparison to traditional electric-gridonly services. The reduced cost could result from a combination of higher system efficiency and exploitation of electricity tariff structures. Traditionally, electricity tariffs are designed to encourage the use of ‘off peak’ power and discourage the use of ‘onpeak’ power, although recent developments in renewable energy resources and distributed generation systems (such as their increasing levels of penetration and their increased controllability) are resulting in pressures to adopt tariffs of increasing complexity. Independently of the tariff structure, more or less sophisticated methods exist that allow distributed energy resources to take advantage of such tariffs, ranging from simple pre-planned schedules to Software-as-a-Service schedule optimization tools. However, as the penetration of distributed energy resources increases, there is an increasing chance of a ‘tragedy of the commons’ mechanism taking place, where taking advantage of tariffs for local benefit can ultimately result in degradation of service and higher energy costs for all. In this work, we use a scheduling optimization tool, in combination with a power distribution system simulator, to investigate techniques that could mitigate the deleterious effect of ‘selfish’ optimization, so that the high-penetration use of distributed energy resources to reduce operating costs remains advantageous while the quality of service and overall energy cost to the community is not affected