An economic comparison of two different storage technologies is difficult because of the unique characteristics of each technology. Another hurdle is obtaining CAPEX costs for each technology, since this information is considered confidential among suppliers and integrators [60].
The model developed in this work can be used to evaluate the economic viability of behind-the-meter BES with just an additional constraint to account for the maximum allowable depth of discharge (DoD), which is ignored for the CAES model since the CAES facility can discharge its full capacity. To prolong the life of the BES, the maximum DoD of the battery is usually set to be less than 100%, in most cases, between 50% to 90% depending on application [61]. The maximum discharge power from the BES is therefore limited by its DoD which reduces the amount of power the BES can shave at a given time. Since the realizable reduction in GA is dependent on the maximum discharge power capacity of the storage, the limit imposed by the BES DoD will shrink the savings from such investments. On the other hand, since CAES can utilize the full range of charge on the system more cost reduction for the customer can be expected.
A unit capital cost range of $1500/kW - $3000/kW [7] is considered for CAES in the present work, whereas the unit capital cost of BES depending on the battery technology ranges from $1500/kW to $4000/kW [7,61]. Thus, CAES can be considered a low cost technology when compared with BES particularly where existing infrastructure such as a cavern can be repurposed.
CAES has unlimited cycle stability and can be discharged from 100% to 0% without compromising the longevity of the system [7,61]. On the other hand, BES suffers from degradation, and when constantly cycled the lifespan is reduced, which has a negative impact on the economics of the project. As can be observed from the IRR results of the SS-CAES economic analysis, projects with longer lifespan achieved higher IRR values. The lifetime of CAES systemS given by most authors and technology developers is between 25 to 40 years; BES technologies, on the other hand, have a relatively limited lifetime, with
manufacturers claiming 8 to 15 years of operating life for the popular Li-Ion battery; however, this figure varies significantly with battery usage [61].
Another added advantage of CAES over BES is that it can be designed to charge and discharge simultaneously. Although this is not considered is the present work, it would increase the customer’s return on CAES investment, as the owner would have the flexibility to use the CAES facility for multiple services at the same time.
In conclusion, CAES technology presents advantages over BES for customer’s load management where high discharge power is required from the storage unit to defray the high-peak power prices. In addition, the longer life cycle and unlimited cycling capability of CAES is advantageous with respect to BES systems.
4.4
Summary
This chapter examined the economic valuation of behind-the-meter SS-CAES systems on an industrial customer’s facility for load management, using the historical load data of a real Class A customer participating in the ICI program.
First, a simplified basic analysis was carried out to gain insight into the possible lower bound of achievable IRR, and the results showed a close similarity with the detailed eco- nomic analysis. Sensitivity analyses were then carried out to estimate the effects of CAES capacity, GAC, and CAP EX on the economics of behind-the-meter SS-CAES systems for customer load management, concluding that the driving factors for the economic viability were the GAC and the CAP EX of the CAES system.
A comparison on the economics of CAES versus BES for customer’s load management is discussed as well and CAES presents more advantages than BES for electricity cost reduction of an industrial customer.
It can be concluded that SS-CAES for load management applications to reduce elec- tricity costs is economically attractive in the current Ontario market structure. However, depending on the company’s MARR and budget constraints, plus the facility’s demand profile, SS-CAES with higher capacity yielded better economic values in all the cases con- sidered.
Chapter 5
Conclusions, Contributions and
Future Work
5.1
Summary and Conclusions
ESS has been identified as one of the viable solutions to managing the load of C&I cus- tomers to keep electricity costs at a minimum. The research presented in this thesis fo- cused on the optimal operation and economic analysis of using behind-the-meter SS-CAES to manage the load of an industrial customer in Ontario that is participating in the ICI program. The customer has been assumed to have abandoned wells/caverns that can be re-purposed for air storage.
In Chapter 1, the motivations of this research, a brief review of the literature related to CAES applications and customer’s load management schemes, together with the research objectives were presented. In Chapter 2, background material relevant for the development of the research work was presented. Thus, an overview of ESS technologies, focusing on their classification and applications at different levels in power systems was presented. A review of CAES systems was given, outlining the basic components, operating principles, types and potential use cases. Finally, the electricity pricing structure in Ontario was presented with a focus on the Class A customers, including the GA which is the major driver for the increasing electricity costs in the province.
In Chapter 3, an operations model of SS-CAES to manage the customer’s load during the system peak hours, was formulated as an optimization problem. The one-year hourly load data of a real industrial customer participating in the ICI program, and the HOEP
data obtained from the IESO website, alongside CAES performance parameters obtained from different related research works, constituted the input parameters into the model. The results of the developed MILP model, which was solved using CPLEX in GAMS, were presented and discussed.
In Chapter 4, the financial plausibility of behind-the-meter SS-CAES for a facility load management was investigated through an economic analysis taking into account the investment cost of behind-the-meter SS-CAES. Simplified basic analysis alongside detailed analysis were carried out for different CAES sizes and life cycles. The effects of some parameters that can influence a behind-the-meter SS-CAES investment were evaluated through a sensitivity analysis, and the IRR results were presented and discussed.
The main conclusions and findings of this thesis are as follows:
• SS-CAES installed behind-the-meter on the facility’s premise for reducing the elec- tricity cost of the customer provides a viable economical solution for the current Ontario’s electricity market structure, or jurisdiction with similar high capacity costs. • A larger discharge power capacity (kW) of the SS-CAES makes more economic sense than energy capacity (kWh) since the GAC of such customers are based on their load contribution during the top peak hours. Furthermore, the customer should consider cost reductions with higher capacity due to economies of scale to make investment decisions.
• In the current Ontario’s electricity rate structure, the costs of the CAES project and GA are the most influential parameters for economic deployment of SS-CAES, as observed from the sensitivity analysis.