Effects of Carbon Tax on Microgrid Combined Heat and Power Adoption

Abstract

This paper describes the economically optimal adoption and operation of distributed energy resources (DER) by a hypothetical California microgrid consisting of a group of commercial buildings over an historic test year, 1999. The optimisation is conducted using a customer adoption model (DER-CAM) developed at Berkeley Lab and implemented in the General Algebraic Modeling System (GAMS). A microgrid is a semiautonomous grouping of electricity and heat loads interconnected to the existing utility grid (macrogrid) but able to island from it. The microgrid minimises the cost of meeting its energy requirements (consisting of both electricity and heat loads) by optimising the installation and operation of DER technologies while purchasing residual energy from the local combined natural gas and electricity utility. The available DER technologies are small-scale generators (< 500 kW), such as reciprocating engines, microturbines, and fuel cells, with or without combined heat and power (CHP) equipment, such as water and space heating and/or absorption cooling. By introducing a tax on carbon emissions, it is shown that if the microgrid is allowed to install CHP-enabled DER technologies, its carbon emissions are mitigated more than without CHP, demonstrating the potential benefits of small-scale CHP technology for climate change mitigation. Reciprocating engines with heat recovery and/or absorption cooling tend to be attractive technologies for the mild southern California climate, but the carbon mitigation tends to be modest compared to purchasing utility electricity because of the predominance of relatively clean central station generation in California.

Modeling of thermal storage systems in MILP distributed energy resource models

“…Along with HOMER [24], formerly developed by the National Renewable Energy Laboratory, it is one of the few tools of its kind available for public use. DER-CAM has been continuously improved to incorporate new technologies and features, as reported in several peer-reviewed publications [25,26]. Recently, it has also been updated to incorporate cold storage [27], stochastic EV modeling [28], as well as stochastic reliability issues [29].…”

Optimal operation of combined heat and power under uncertainty and risk aversion

“…[8] compare the economic benefit of installing different types of DG at a hypothetical microgrid via the Distributed Energy Resources Customer Adoption Model (DER-CAM). Using mixed-integer linear programming (MILP), they find that investing in gas-fired CHP turbines leads to the lowest energy cost and also reduces CO 2 emissions.…”

“…As electricity is produced close to consumers, DG reduces transmission losses and allows for waste heat recovery. Thus, even though the electricity conversion rate for DG is lower than that of large power plants, the overall energy efficiency of DG system with a CHP is significantly higher [7,8]. For the aforementioned reasons, Germany has adopted three CHP laws to support investment into small-and large-scale CHP [9,10,11].…”

Distributed Generation with Heat Recovery and Storage

“…While this model has been used extensively by Berkeley Lab researchers and results have been previously reported (see Marnay et al (2001) and Rubio et al (2001)), the current version additionally incorporates CHP-enabled technologies and carbon taxation (see Siddiqui et al (2005a) and Siddiqui et al (2005b)). All versions of the model have been programmed in the commercial optimisation software, GAMS (General Algebraic Modeling System).…”

“…4 We do not consider PV cells in this paper, but have done so in other work (see Siddiqui et al (2005a) or Siddiqui et al (2005b), for example). In general, such technologies have high turnkey costs that prevent their adoption unless either the carbon tax is very high or a substantial subsidy is available.…”