Evaluating How Demand Side Resources Affect the Environmental and.pdf (5.12 MB)
Download file

Evaluating How Demand Side Resources Affect the Environmental and Economic Performance of Energy Systems

Download (5.12 MB)
posted on 01.12.2015, 00:00 by Nathaniel Gilbraith

The recent history of energy systems is succinctly summarized as building enough energy extraction, conversion, and delivery infrastructure to meet growing energy demand. Among the benefits of this energy systems framework, we observe that access to modern energy services helps to improve peoples’ standards of living and energy consumption has been positively correlated with gross domestic product. Among the draw backs of focusing solely on the supply side of energy extraction, conversion, delivery, and consumption are concerns regarding inefficient energy consumption (i.e. over-consumption of energy) and the growing evidence of large energy-related human, environmental, and climate impacts. As governments begin to recognize the economic and environmental costs of additional supply side infrastructure, governments, academic institutions, and advocacy groups highlight the “low hanging” nature of demand side interventions. On the surface, demand side interventions offer a win-win situation: use technology or data to identify energy consuming processes that can be optimized (i.e. reduced) or incur very large energy system costs. The energy system becomes more “cost effective” when incentives or regulations can decrease the energy consumption of those processes at a lower cost than actually meeting the baseline energy demand of those processes. This Dissertation goes further and evaluates how these energy saving policies, incentives, and regulations interact with our existing energy systems in ways that are not immediately apparent. In the second chapter, I assess how mandatory commercial building energy codes can reduce air pollutant emissions and provide social benefits. The U.S. government currently does not use estimates of the benefits of codes to determine the appropriate level of policy stringency 5 or set adoption incentives and thus systematic estimates of social benefits are necessary. Quantitative estimates of code benefits at the state level that can inform the size and allocation of these incentives are not available. We estimate the state-level climate, environmental, and health benefits (i.e., social benefits) and reductions in energy bills (private benefits) of a more stringent code (ASHRAE 90.1-2010) relative to a baseline code (ASHRAE 90.1-2007). We find that reductions in site energy use intensity range from 93 MJ/m2 of new construction per year (California) to 270 MJ/m2 of new construction per year (North Dakota). Total annual benefits from more stringent codes total $506 million for all states, where $372 is from reductions in energy bills, and $134 is from social benefits. These total benefits ranges from $0.6 million in Wyoming to $49 million in Texas. Private benefits range from $0.38 per square meter in Washington State to $1.06 per square meter in New Hampshire. Social benefits range from $0.04 per square meter annually in California to $0.50 per meter foot in Ohio. Reductions in human/environmental damages and future climate damages account for nearly equal shares of social benefits. In the third chapter, I explore how improvements in building natural gas energy efficiency can help natural gas utilities avoid capital intensive natural gas system infrastructure investments. Recent periods of pipeline congestion, high natural gas and electricity prices, and controversial infrastructure proposals have increased the public and policymaker scrutiny of the existing natural gas system infrastructure and investment process. In order to help inform the debate of New England’s energy system options, we estimate the benefits of natural gas end-use efficiency programs for utilities in New England. In particular, we model how efficiency programs affect utility firm pipeline capacity purchases and the excess capacity that utilities resell in the short-term capacity markets (i.e. the “capacity value” of the efficiency program). We 6 find that when the utility currently owns sufficient pipeline capacity to meet demand projections, the capacity value of natural gas energy efficiency measures is high because implementing an efficiency program allows the utility to resell additional excess capacity in the high-value, shortterm resale market: $4 to $5 per thousand cubic feet (MCF) of natural gas savings over the life of the space heating efficiency program and $3 per MCF for water heating efficiency programs. When the utility needs to purchase additional firm pipeline capacity to meet projected demand growth, the efficiency program may avoid part of the planned purchase but also resells less excess capacity. For this scenario, the capacity value of space heating efficiency programs is approximately -$2 to -$3 per MCF of natural gas savings, and $1 per MCF for water heating efficiency programs. Given the current capacity situation of utilities across New England, our findings suggest that some existing natural gas efficiency programs in southern New England (CT, MA, RI) may not be cost effective while a greater number of natural gas efficiency programs in northern New England (ME, NH) may be cost effective. The capacity value of natural gas efficiency programs, and thus the cost effectiveness of these programs, is sensitive to the revenue that utilities receive when they sell excess capacity in the short-term market. We recommend that public utility commissions consider including the revenue that utilities receive from reselling excess capacity in the cost effectiveness testing framework for efficiency programs. PUCs could accomplish this by valuing excess pipeline capacity at the basis differential between New England and production areas or by working with utilities and other stakeholders to identify a mutually agreeable value. In the fourth chapter, I quantify how allowing residential consumer to self-provide electric energy using distributed solar photovoltaic (PV) arrays will change overall electricity 7 system costs in Portugal. Further, I quantify the distribution of the benefits of solar PV among solar panel owning and non-solar panel owning ratepayers. In 2008, the European Parliament adopted the European Commission’s (EC) “20-20-20” goals in order to address global climate change concerns and to tap the potential economic and energy security benefits of energy systems based on renewable energy resources. Under the 20-20-20 package, Portugal needs to produce 60% of total electricity using renewable energy sources (or RES) by 2020. However, the total cost of subsidy policies that lead this transition now account for approximately 33% of residential consumers electricity bills. In light of both the 20-20-20 climate goals and the increasing need to achieve these goals in a cost effective manner, we quantifying the benefits and costs of distributed solar PV in Portugal for panel owners, ratepayers as a whole, and the specific group of ratepayers that does not own solar panels. We measure the benefits and costs of distributed solar PV from these perspectives by computing and comparing the present value of the cost of a distributed solar PV array, the present value of grid electricity purchases that solar panel owners avoid, and the present value of grid generation and delivery costs that the grid avoids when panel owners consume less electricity. We find that solar PV is net present value positive for the average Portuguese electricity ratepayer that owns a solar array. The most attractive option for an average consumer is a 500W array, with a net present value of 700-800€ relative to a present cost of about 1500€. On the other hand, distributed solar PV generation has a higher cost than using the grid to produce and deliver a marginal unit of electricity during periods that solar PV arrays generate electricity. Ratepayers as a whole pay 900-2600€ more in total costs for each kilowatt of distributed solar PV capacity that panel owners install; the 500 W solar array increases total system costs by 1600€. Further, panel owners also avoid paying sunk grid costs, such as revenue guarantees to other renewable 8 generators and the costs of grid infrastructure. In order to recover these sunk costs from ratepayers, retail prices will increase for all consumers. As a result, non-panel owners will pay an additional 1600€ in bills (total across all non-panel owners) for each 500W array that panel owners install. This is equivalent to a 140€/MWh subsidy to panel owners, which is larger than the subsidy that many other Portuguese generators receive but smaller than the subsidy for existing solar PV arrays. Portuguese policy-makers could reduce this subsidy by instituting some type of solar PV fee (more straightforward) or changing the rate structure such that retail prices more closely reflect underlying costs (more complex). Alternatively, Portuguese policy makers could maintain the existing policy. The subsidy per unit of installed solar PV will not change; however, the large number of consumers that live in multi-family housing (and may not be able to install solar PV) suggests that the total value of the subsidy from panel owners to non-panel owners will remain limited.




Degree Type



Engineering and Public Policy

Degree Name

Doctor of Philosophy (PhD)


Ines M. Lima de Azevedo

Usage metrics