Control of greenhouse gas emissions by optimal DER technology investment and energy management in zero‐net‐energy buildings

Abstract

The U.S. Department of Energy has launched the commercial building initiative (CBI) in pursuit of its research goal of achieving zero-net-energy commercial buildings (ZNEB), i.e. ones that produce as much energy as they use. Its objective is to make these buildings marketable by 2025 such that they minimize their energy use through cutting-edge, energy-efficiency technologies and meet their remaining energy needs through on-site renewable energy generation. This paper examines how such buildings may be implemented within the context of a cost-or CO 2 -minimizing microgrid that is able to adopt and operate various technologies: photovoltaic modules (PV) and other on-site generation, heat exchangers, solar thermal collectors, absorption chillers, and passive/demand-response technologies. A mixed-integer linear program (MILP) that has a multi-criteria objective function is used. The objective is minimization of a weighted average of the building's annual energy costs and CO 2 emissions. The MILP's constraints ensure energy balance and capacity limits. In addition, constraining the building's energy consumed to equal its energy exports enables us to explore how energy sales and demand-response measures may enable compliance with the ZNEB objective. Using a commercial test site in northern California with existing tariff rates and technology data, we find that a ZNEB requires ample PV capacity installed to ensure electricity sales during the day. This is complemented by investment in energy-efficient combined heat and power (CHP) equipment, while occasional demand response shaves energy consumption. A large amount of storage is also adopted, which may be impractical. Nevertheless, it shows the nature of the solutions and costs necessary to achieve a ZNEB. Additionally, the ZNEB approach does not necessary lead to zero-carbon (ZC) buildings as is frequently argued. We also show a multi-objective frontier for the CA example, which allows us to estimate the needed technologies and costs for achieving a ZC building or microgrid.

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].…”

“…Reduced on-peak usage also has a disproportionate benefit on bills because of demand charges and time-of-use (TOU) energy rates. For a more detailed description of the DER-CAM model see [22,25,31,32]. Figure 1 shows a high-level schematic of building energy flows as modeled in DER-CAM.…”

Stochastic programming of vehicle to building interactions with uncertainty in PEVs driving for a medium office building

“…Since the focus of this work is stochastic programming of the new aggregated EV interconnection model for the DER-CAM to consider uncertainty in driving schedules, only the most relevant mathematical models are presented and the full mathematical model implemented in DER-CAM can be found in [1], [15][16][17].…”

“…Along with HOMER [14], formerly developed by the National Renewable Energy Laboratory, it is one of the few optimization tools of its kind that is available for public use. It has been continuously improved to incorporate new technologies and features, and used in several peer-reviewed publications [1], [15][16][17]. Recently, it has also been updated to incorporate EVs [11].…”

Optimal Scheduling of Industrial Task-Continuous Load Management for Smart Power Utilization

“…Among them, demand side management [4,5] and demand response technology are the main focus [6,7]. References [8][9][10][11][12] explore the method of improving energy efficiency with the assistance of demand response technology, aimed at water heaters, air conditioners, fridges, and washing machines. Reference [13] keeps the balance between economy and comfort by introducing comfort constraints in energy strategies that include distributed generation.…”