Appendix: Green Leasing

Transcription

1 Appendix: Green Leasing Overview Green Leases are one policy tool that has been implemented to overcome the split incentive problem discussed above. The term refers to a standard rental lease that includes a mechanism to finance energy efficiency improvements in a home. Typically, a Green Lease includes language stating that if a landlord makes improvements of a certain type, he may raise the rent immediately to begin to recoup the cost. If structured properly, a Green Lease benefits both landlords because repayment on capital improvements is guaranteed and tenants whose increases in rent will be more than offset by decreases in utility bills. As part of defining a scope for the Cambridge Multifamily Energy Program, we have investigated the viability of utilizing Green Leases and related policy tools that target the split incentive problem. Previous Use While Green Leases are not uncommon in the commercial sector, 30 the practice has not yet gained a foothold in the residential rental market. Late last decade, the Cambridge Energy Alliance began to consider advocating for their use locally, but the initiative lost steam and has not been restarted. 31 Applicability to Cambridge Previous use of Green Leases in the residential housing market have generally been restricted to rent controlled areas. In these situations, Green Leasing provides a convenient and mutually beneficial mechanism that allows landlords to be compensated for making improvements to the home without causing an increase in total living costs to the tenant. This benefit is not as clear in a rental market without rent control, where there is no legal barrier to a landlord who wishes to raise rent upon expiration of a lease. Cambridge currently has an uncontrolled rental housing market. Rent control had previously been established in the 1970s, but the market was deregulated by a statewide ballot initiative in Predictably, opening the market has led to both increased average rents 32 and greater investment in rental housing 33 in Cambridge. Green Leases are structured to confront a formal barrier in the rental housing market, where landlords may be unable to guarantee a revenue stream (in the form of increased rents) to recover the cost of capital investments. However, because of the lack of rent control, the barriers to rent increases in Cambridge are informal rather than formal. Landlords are hesitant to increase rents because of the extralegal protests raised by tenants. The key barrier is the willingness of tenants to accept rent increases on principle. Green Leases are not intended to confront this barrier, but instead present a legal mechanism for certainty and transparency once parties have already agreed to the general concept. Potential Practicum Work Items 30 See: and- leasing/green- leasing, practices.html, _Energy_and_Sustainable_Development/BEES2011FINALfullWeb.pdf 31 Beth Williams thesis, Jason Jay thesis. 32 New York Times, rent- control- just- vanishes- both- sides- of- debate- cite- boston- s- example.html?pagewanted=all&src=pm 33 Henry Pollakowski, MIT Center for Real Estate Page 34

2 While Green Leases may be useful in providing a formalized mechanism of implementing efficiency improvements in rental housing, we do not believe that they confront the most fundamental barriers to efficiency in multifamily housing in Cambridge that is, the agreement by all parties that efficiency improvements and resulting rent increases are mutually beneficial for both landlord and tenant. In light of this, we believe that a focus on Green Leases would a misallocation of this effort s limited resources and political capital. Instead, we believe that our efforts should focus on the informal barriers preventing energy efficiency in the multifamily housing market and must entail a comprehensive outreach and educational campaign to the small landlord and tenant communities. Appendix: Stakeholder Analysis Approach Overview There is a wide range of groups that must be consulted in as part of a stakeholder analysis. Because there is little centralized representation within the city of Cambridge for the major stakeholder categories (landlords, tenants, condominium owners), it would be prohibitively difficult to reach every individual with a stake in multifamily energy efficiency. However, there are several existing groups that represent varying interest groups. Our stakeholder analysis process should include conversations both with these formal organizations and with individuals chosen to represent broad and unorganized groups. Existing Groups On the landlord side, there are several state and regional organizations of small property owners to conduct outreach to. These include the Small Property Ownership Association, 34 the Massachusetts Rental Housing Association, 35 the Greater Boston Real Estate Board, 36 and the Boston chapter of the Institute for Real Estate Management. 37 There are also a number of condominium associations that represent property owner interests as well. While less organized, there are also established mechanisms that can be used to reach tenant groups. The focus of tenant advocacy groups is typically on eviction and poverty, though it clear that energy savings has relevance to this mission. The nonprofit Cambridge Economic Opportunity Committee 38 serves as the local Community Action Program. On the city side, the Environmental and Transportation Planning Division 39 within the Cambridge Community Development Department is also an important actor in this space. Unfortunately, the majority of tenant- engagement activities are restricted to subsidized housing, and there are few existing means of organization among market- rate tenants. This is made more difficult by the transitory nature of Cambridge s rental population, particularly its students. One final group of interest that may advocate tenants interests in stakeholder discussions are Heating Assistance Organizations that provide resources to support residents that are unable to pay their energy bills during the winter. Beyond landlords and tenants, there are a number of related industries with an interest in energy efficiency in multifamily housing. These include, but are not limited to, property management firms, energy contractors, and realtors Page 35

3 Another relevant actor is Just- A- Start, 40 a local organization dedicated to mediating landlord- tenant disputes in the Boston area, with a heavy focus on Cambridge. Just- A- Start s mediators have valuable experience navigating the institutional context of landlord- tenant relationships, and it is likely that they will be able to act as an important resource in conducting outreach and information to these groups. Finally, NSTAR s current multifamily housing program includes an outreach component conducted in partnership with local community organizations and likely has established inroads into local communities that can be leveraged for this project. Potential Practicum Work Items One approach to stakeholder analysis would take a three- tiered approach to gathering input. These steps would include: Interviews with Formal Organizations. Representatives could be easily identified through publicly available information. Interviews with these representatives would be valuable both in determining their interests and concerns relating to multifamily energy efficiency and their views on stakeholder groups that should be consulted in the process. Focus Groups with Representative Individuals of Stakeholder Groups. Ideally, this would be a random sample of landlords, tenants, condominium owners, property managers, and other interested parties. It is likely, however, that we will have to resort to less random methods of selection, relying either on open marketing, personal relationships, or referrals from formal groups. Interviews with Previous Program Participants. Previous program participants could be identified by NSTAR and interviewed to understand both the factors that weighed on the decision to invest in efficiency upgrades as well as the categories of actor that were involved in the process. Case Study - WegoWise Monitors energy consumption primarily in multifamily buildings. Building Type: multifamily/residential Tweaked application so it could comply with NY Law 84 and function for commercial buildings Developing commercial and single- family residential platform. Asset Data: Basic building characteristics that can be discovered in about 27 questions. Do not actively use Tax Assessor data, but are exploring possibilities. Operational Data: Accesses E- bill online payment systems most utilities have Monthly reports of energy data WegoWise is not as concerned right now about smart meters and receiving 15- minute interval data. Visualization Tool: Online dashboard WegoWise is an online platform designed to monitor energy and water use of multi- family homes. Primarily targeted at property managers, clients pay $5/building/month to have their electric, gas, and water consumption automatically tracked each month Page 36

4 As part of the energy assessment for each building, property managers respond to approximately 27 questions regarding the physical characteristics of each property. WegoWise s main value- add is in automatically tracking monthly energy consumption and payments. Property managers share e- Bill account numbers and passwords with WegoWise. WegoWise then screen scrapes data every 20 days to update energy consumption. WegoWise offers their clients comprehensive analysis of building energy information. Users can build custom reports to compare specific buildings and specific energy consumption. Generated charts show how the client s buildings perform compared to physically similar buildings in the same climate zone and with the same type of heating system in WegoWise s database. Users can also specify a geographic location for comparison. For example, perhaps they only want to know how their buildings compare to buildings in Massachusetts, or even more specifically in Boston. They are showed how their buildings compare to efficient buildings. This efficiency threshold is based upon performance information of the top 25% of similar buildings in WegoWise s database. WegoWise also offers the option to compare the energy performance developments, not just single buildings, which may be valuable to expansive property owners. WegoWise offers a simple, easy- to- use energy monitoring tool to property managers. Automatically capturing utility bill information saves the time of users having to enter information manually. Moreover, graphs and charts help property managers understand which are their low- and high- performing buildings. WegoWise has been used to show changes in building performance after retrofits, to help qualify a building for other energy funding, and to verify LEED performance criteria. A main obstacle with WegoWise is getting utility data if building tenants pay their own utility bills. Property managers must have tenants sign releases of information and acquire their individual utility account numbers and passwords. This can slow the process and some tenants do not want to release their information. However, if property managers are able to obtain the permission of 50 to 60% of tenants, WegoWise can calculate an average consumption pattern for units and then create a building estimate. Some buildings overcome this obstacle by including a data release provision in leases. WegoWise has developed and extensive network within Massachusetts, but is working nationally with presences in New York, California, and other areas as well. WegoWise is looking to expand its market by developing a similar online platform for commercial buildings and single- family homes. Online energy management is a young market and WegoWise is one of only a few companies in the arena [EnergyScoreCards is a potential competitor]. Case Study - EnergyView PDF Report Community map of building energy performance and individual ratepayer comparison calculator. Page 37

5 Building Type: Multifamily/residential/commercial Asset Data: Tax assessor records and geographic survey information 35 features were collected from these data sets Operational Data Monthly electric and gas data from NSTAR Visualization Tool: Color- coded map which ranks building performance. This tool was only ever hypothetical and never launched live. Online calculator for an individual to enter household data outputs graphs on: Monthly electricity use compared to similar homes Electricity usage distribution Monthly gas use compared to similar homes Gas usage distribution EnergyView was developed by an MIT PhD student and faculty member to model energy consumption in residential and commercial buildings. Their approach used exclusively remotely available data, meaning no home visit was necessary, nor did anyone need to collect descriptive information from building owners or tenants. Using tax assessor records, geographic survey information, and monthly energy information provided by the local utility NSTAR, the authors created models to predict energy usage for 6,500 buildings in Cambridge, Massachusetts. These models were able explain about 75% of observed variance in energy consumption given building characteristics. From their models, the authors designed two potential tools. For utilities - which are able to access all of their clients data without privacy restrictions - the authors developed a map which color codes buildings by energy consumption; this tool enables utilities to readily see which buildings which are consuming more energy than would be expected by their given features. For individual ratepayers, the others created an online calculator where users can manually enter their monthly energy information and then see resulting charts which compare their energy usage to the predicted energy usage of similar buildings. The authors noted the difficulty in assigning specific utility records to buildings. If utilities were able to include a Building ID code which matched with tax assessor parcel IDs, this would facilitate the analysis process. The authors also stated knowing whether buildings were owner- occupied or tenant- occupied would be helpful, but that information was not available in tax assessor records. The authors faced another challenge when multiple meters were associated with one building. They didn t necessarily know which meters were attached to units and which were associated with common spaces. This suggests a potential difficulty in conducting remote energy analyses; without tenant or owner input, it may hard to know what space meters represent. EnergyView faces limitations in that due to privacy restrictions, only utilities can use the mapping feature. Moreover, utility energy data sets do not necessarily identify which meters are for occupied spaces and which are for common spaces, making the analysis more complicated. However, even with these obstacles, EnergyView and similar platforms have the potential to be scaled up and offer utilities mapping tools which could enable them to target efficiency programs at high energy users. Page 38

6 This relationship diagram explains how different data relates to each other in EnergyView. Case Study Cambridge Solar Map Academic Paper by Christoph Reinhart and Alstan Jakubiec Ranks solar potential of roofs and provides info on solar potential, financial costs, environmental benefits, and installation information. Building Type: Multifamily/residential/commercial - indiscriminate Asset Data: LIDAR scan RADIANCE/DAYSIM simulation Standard local weather data Operational Data: None Potentially this could be added to make an even more convincing tool. Visualization Tool: Interactive map which color codes solar suitability on roofs Users can search for specific addresses or zoom and move map Generates numerical breakdowns for individual roofs of solar potential, financial costs, and environmental benefits. Provides an installation overview. While not an efficiency or energy consumption map, the Cambridge Solar Map demonstrates the power of an interactive map for relating energy information to individual homeowners and to community groups. Developed by MIT s Sustainable Design Lab, the map color codes roofs for excellent, good, or poor photovoltaic potential. The data used to build the map includes a LIDAR scan of Cambridge to establish urban geometries, a solar radiance simulation model built by Christoph Reinhart, and local weather station data. The developers used the specifications of a SunPower 185- watt panel to calculate the annual PV generation. Page 39

7 Users are able to search a specific address or manually move the map and select buildings. Upon selection, the Solar Tool generates PV related information for that building if it has a ranking of excellent or good. This information generated includes estimates of potential PV size (kw), annual electricity generation, cost of installation, tax credits and rebates, annual revenue, payback time, and environmental benefits. The map also provides links to find out more about how to get a PV system installed. The power of the Solar Map is that individual homeowners can quite quickly determine whether their home may be suitable for solar power and see and estimate of financial benefits for installing a system. Installers or other community groups can use the map to target specific homes or neighborhoods which would benefit the most from PV installations. Individual homeowners may be able to convince neighbors to also install solar, and perhaps negotiate a group discount on contractor cost. One of the map developers also noted that they compared the map to an existing MIT solar installation. The solar installation seemed to be under producing based on what the map predicts. The system is currently being analyzed, but this suggests that the map could also be used to verify system performance after installation. The Sustainable Design Lab is continuing to work on the map. In the future, they would like to develop a tool to outline panels on a roof to get more specific information about system configuration. They also recognized the potential of incorporating actual energy consumption data to enable house- to- house comparison and augment the financial incentive calculations. If possible to generate, a community efficiency map could benefit from leveraging similar features to the Cambridge Solar Map. These include: Simple, easy- to- understand color coding User- friendly searching and moving Speaks to multiple user groups - individuals, community groups, contractors, utilities, and government agencies Includes estimates of savings and financial incentives Case Study Next Step Living Next Step Living is a one- stop- shop for home energy assessments and weatherization. Building Type: Residential Asset Data: Audits Infrared Imaging Blower Door Tests Page 40

8 Tax Assessor Records Operational Data Utility bills 12 months pre- installation and 12- months post- installation Energy assessment database Visualization Tool: Heat Map compares tax assessor record characteristics to audits of similar homes in the NSL database Next Step Living (NSL) is a Massachusetts- based turnkey home energy assessment and weatherization provider. NSL accounts for 90% of the home performance market in Massachusetts and will be expanding to Connecticut and Maryland. The four- year- old company conducts 25,000 home energy assessments per year and expects that number to continue to grow. NSL collects twelve months of utility data from customers before they complete a weatherization of their home. NSL also asks for 12 months of energy data post- installation. Using this information, NSL is building a detailed database of home energy audits. Using 20,000 homes worth of data, NSL built a Heat Map of Somerville. They used a handful of important data points pulled from tax assessor records to compare Somerville homes to similar homes in their database of audits. They color coded homes so that hot homes were the ones with the most potential for upgrade. Next Step Living s Heat Map is leveraging an increasingly popular method of analyzing home efficiency performance by comparing remote, publicly available housing data (from tax assessor records) to historic energy audits of similar buildings. This enables contractors to develop building profiles before contacting potential customers. They can identify neighborhoods and communities that offer the greatest opportunity for savings and target their outreach efforts there. Case Study - Retroficiency Creates building audits with minimal information by using algorithms to model building performance and making comparisons to prototypical buildings with same characteristics from historic audits. Building Type: Commercial Asset Data: Builds increasingly accurate building profile, but starts with basic info and improve over time by augmenting with more information. Page 41

9 Operational: 15- minute interval data 12 months of historical energy data Retroficiency developed two different tools to conduct remote energy assessments which are highly accurate. Retroficiency leases their tools to energy auditing businesses or to utilities which are able to conduct audits in less time and with less demand of inputs from property owners. Retroficiency s Virtual Energy Assessment (VEA) requires only an address and 12 months of historic energy consumption data to identify end use loads such as heating, cooling, and lighting. (VEA may also use 15- minute interval data from clients if they have smart meters installed.) VEA can identify building usage patterns and recognize moments of inefficiency such high use during periods of low occupancy. From these analytics, VEA can make recommendations for upgrades or performance measures to reduce energy use. Retroficiency also offers an Automated Energy Audit (AEA) which uses limited building asset information to make accurate energy profiles of a building. A building owner or property manager can enter in just a few building characteristics and the AEA will compare that building to Retroficiency s library of thousands of actual audits to build an energy model of the building. As the property manager enters more information overtime, the model becomes more accurate. Similar to the VEA, this is a remote energy assessment tool and it also makes efficiency recommendations. Retroficiency does not currently work in the residential sector though it has been building a database of multi- family [bigger than houses or garden- style apartments] energy models. In an interview, CEO Bennett Fisher indicated that Retroficiency s VEA and AEA tools could be modified to work for residential homes if demand existed in that market. Page 42

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