A simulation-based decision model for designing contract period in building energy performance contracting
Introduction
Performance-based contracting, which buys performance through an integrated acquisition and logistics process delivering improved capability to a range of products and services, is growing in popularity around the world. Industrial sectors, such as commercial shipping, public transport, health services, and energy generation, adopt the performance-based contracting frameworks commonly. Following the general performance-based contracting mode, Energy Performance Contracting (EPC) emerged in North America in the 1970s after the first oil crisis [1], and shows a remarkable growth trend in recent years [2], [3]. EPC utilizes the future energy savings revenues to repay the initial energy efficiency investment. During the contract period, the Energy Service Companies (ESCOs) get shared profits from the regular savings of utility bills, and the facility owners upgrade the aging and inefficient assets without capital investment [4].
Since EPC has encouraged the ESCO to develop more desirable energy efficient solutions, the well-designed provisions, such as the contract period, would go a step further to unite the owner and the ESCO for a shared profit goal [5]. Within the contract period, the ESCO takes care of the operation and maintenance (O&M) activities for the energy conservation measures and, at the same time, holds the major part of the energy cost savings as return. After the contract period, the ESCO leaves and both the O&M cost and the savings revenue would be held by the owner. Due to the complexity in dynamic project environments, the length of the contract period has a significant impact on the risks allocation and benefits sharing. The energy cost savings produced by the energy project must be sufficient to cover all project related costs over the contract period from both the owner's and the ESCO's perspectives. Thus, the length of the contract period determined is critical for both the owners and the ESCOs concerning the EPC success.
However, tradeoffs exist in the contract period decision-making of EPC. In general, the ESCOs prefer to sign a contract with a longer contracting term as more profit can be made over time. But the owners are likely to shorten the contract period to a reasonable length, so as to guarantee their project rights and interests after the well-equipped facility transferred. Also, the ESCOs need to make competitive offer concerning the shorter contract period to win the bidding. How to determine the contracting term becomes a critical issue in the negotiations between the owners and the ESCOs. Besides, there are other limits. According to the Energy Policy Act [6], the whole contract period of EPC shall not exceed 20 years to allow longer payback periods for retrofits, including windows, heating system replacements, wall insulation, site-based generation, advanced energy savings technologies, and other retrofits. States and local authorities have also issued legislation on the EPC duration. For instance, the maximum energy performance contract period for New Jersey is 10 years, North Carolina, 12 years, Maryland, 15 years, and Florida, 20 years. Therefore, the contract period in EPC should be neither too long nor too short according to the estimation.
Owing to the absence of a universally accepted standard, how to determine the length of the contract period on a win–win basis has not been agreed upon in the EPC market. To a large extent, the future O&M cost, the unknown energy conservation measure performance, and the fluctuated energy price, are considered as the main uncertainties that affect the project success in EPC. As a result, mismatches between the estimated and the observed project performance commonly arise in industrial practice [5]. In this paper, the uncertainties within the energy performance during the contract period of EPC are modeled in two separate stochastic processes, namely the annual energy savings amount and the energy price. A framework concerning the shared energy savings revenues is proposed, and the owners' and the ESCOs' profits are then derived respectively during the contract period. An optimization model for the contract period design in EPC is structured to address the potential risks on a win–win basis. A simulation-based decision approach with quantitative analysis is then developed to determine how long the contract period should be in order to balance the profit expectations for both the owners and the ESCOs.
This paper is organized as follows: the related studies on the determination of the contract length are reviewed in Section 2. Section 3 models the uncertainties in energy savings performance on a simulation basis, with the energy efficiency investment, the energy savings instability and the energy price fluctuation taken into account. In Section 4, a decision model with quantitative analysis is developed to determine how long the contract period should exactly be. In Section 5, a campus case is used to verify the applicability of the proposed approach for the contract period determination. Finally, the conclusions are drawn in Section 6.
Section snippets
Literature review
In recent years, performance-based contracting frameworks have become more and more popular in social welfare programs [7], public health [8], public-private partnership (PPP) [9], [10], and energy sectors [11]. As an alternative financing mechanism authorized by the United States Congress, EPC is classified as one of the performance-based contracting forms which focuses on developing strategic performance metrics and directly relating contracting payment through incentivized, long-term
Energy performance simulation
Energy performance estimation plays an essential role in the success of an EPC project for either the owner or the ESCO. Several factors are involved which affect the real energy performance, including the energy efficiency investment, energy savings amount, as well as the energy market prices. In current industrial practices, most energy performance estimations are deterministic on the basis of experience, regardless of the influence of the potential uncertainties within the aforementioned
A decision model for contract period determination
Based on the energy performance estimation, how to obtain a reasonable and desirable contract length has been raised as a tradeoff question. During the period, the generated NPV is needed to satisfy the requirements of both the owners and the ESCOs. The ESCOs prefer to sign a contract with a longer contract period, while the owners are more likely to shorten the contract length so as to guarantee their own interest. Thus, the developed contract period determination model is not meant to achieve
Case application
The case study is conducted in order to verify the applicability of the proposed framework for the contract period design. According to Hopper et al. [4], municipals, universities, schools, hospitals (MUSH) and the federal government account for about 80% of the total EPC market, since these organizations are typically starved for capital and maintenance budgets. As one of the major entities using EPC to obtain energy efficiency facility improvements, in this study, a university case is chosen
Conclusions
For a typical EPC, the length of the contract period is one of the most critical factors that are tight to both the owners and the ESCOs' project profitableness. However, tradeoff exists in the contract period determination that would go neither too long to lose bidding competitiveness nor too short to incur large loan risks. Since the contract period is mostly determined by empirical estimation, rather than quantitative analysis, mismatches between the estimated energy savings and the actual
Acknowledgment
The authors would like to thank the capital projects department of University of Maryland for their support and sharing of the project information. All results and conclusions presented here are that of the authors alone.
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Ph.D. Candidate at Huazhong University of Science and Technology, and Visiting Scholar at University of Maryland, College Park, USA.