Harnessing big data to kick-start your energy management plan

Transcription

1 Harnessing big data to kick-start your energy management plan Use technology to gain the facts and insights you need to ensure your energy management plan is based on a solid understanding of your consumption data.

2 Table of Contents The rise in energy costs Challenges to understanding energy costs Complicated electricity bills Multiple operational variables Lacking data transparency Implementing an energy management plan Developing your plan with the right tool: a big data energy software platform Access electricity consumption information a. Access consumption data using the energy software platform Normalize data based on drivers of consumption a. Normalize data using the energy software platform Define an accurate baseline a. Define an accurate baseline using the energy software platform What to look for in a big data energy software platform Ability to link electricity usage data to the business Validation of electricity usage and costs Benchmarking capabilities Data Visualization Cloud Based Solution Top business benefits of a big data energy software platform Objective support for an energy project proposal Measurable time savings Strong ROI Risk mitigation: better understanding of energy consumption Summing up: Becoming an empowered energy consumer About Bruce Power Direct Sources... 20

3 The rise in energy costs Since the release of Ontario s 2013 Long Term Energy Plan (LTEP) in December, business managers across the province have been concerned with the predicted rise in energy costs over the next couple of years. According to the report, energy costs are expected to rise at an unprecedented rate, increasing by approximately 10% in 2014 and 2015, followed by a 15% increase in In order to help commercial and industrial energy consumers mitigate the effects of the cost increase, the provincial government presents a number of tools throughout the plan. The most prominently featured tool is to adopt a Conservation First mandate for their business. The province has had significant success in deploying these tactics. By adopting conservation practices since 2005, Ontario managed to conserve approximately 8.6 billion kwh of electricity at a rate of approximately 9.0 /kwh for total savings of $776 million by the end of While the idea of adopting a conservation mandate is a great one, many energy customers in Ontario find it challenging to implement these practices in their business environment. Much needed energy data analytics are very difficult to obtain and even more difficult to affix to their business KPIs. Lack of this insight and data transparency makes it extremely challenging for managers to make informed and measurable business investments in energy conservation projects. Challenges to understanding energy costs COMPLICATED ELECTRICITY BILLS Whether an industrial manufacturing facility or commercial property, all businesses face similar problems when it comes to understanding and managing their electricity consumption and spend. The first problem is that the electricity bill can be a very complex entity, with a number of different components that are difficult to understand on their own, let alone as a collective group. Figure A breaks down the electricity bill of a sample commercial electricity consumer in Ontario who consumes 5 million kwh per annum and demonstrates the fluctuating cost structure. 3 Harnessing big data to kick-start your energy management plan

4 FIGURE A The components of a typical electricity bill $100,000 $90,000 $80,000 $70,000 $60,000 $50,000 $40,000 $30,000 $20,000 $10,000 $0 Sample 5 Million kwh Ontario commercial electricity consumer Sep-12 Oct-12 Nov-12 Dec-12 Jan-13 Feb-13 Mar-13 Apr-13 May-13 Jun-13 Jul-13 Aug-13 GA HOEP DELIVERY REGULATORY DEBT RETIREMENT CHARGE HST MULTIPLE OPERATIONAL VARIABLES There are a number of operational variables that make it even more difficult to understand how consumption and costs are related. Some of these variables include unpredictable changes in: Electricity demand Production/sales demand Weather patterns Energy market prices Facility configuration FIGURE B The Electricity cost structure YEAR TO DATE COST STRUCTURE MONTH TO DATE COST STRUCTURE 12% 11% 6% 7% 5% 9% 12.7 /kwh 44% 6% 11% 11.1 /kwh 41% 24% 24% For most businesses, paying the bill each month is much simpler than trying to understand and analyze how each component relates to their business metrics and overall consumption. In addition, larger businesses may need to access data from multiple utilities for all their locations and facilities. Not only is it tedious and time consuming to obtain the data from each utility, but the data itself is limited as it provides only aggregate electricity consumption and spend for the last billing period (i.e. 30 days). In order to correctly analyze and interpret the data the manager needs to access hourly consumption data. Without the proper tools this type of data is difficult to obtain and even harder to work with. 4 Harnessing big data to kick-start your energy management plan

5 Understanding consumption and related costs are especially important for companies where electricity is a significant percentage of their annual budget. Take plastics manufacturers in Ontario as a prime example, where energy costs are consistently one of the top five 2 operating expenses. For companies in similar situations, the electricity cost is simply seen as a required line item on the budget, with no accessible way of reducing the total. LACKING DATA TRANSPARENCY The most significant challenge in understanding energy consumption is that businesses do not have access to the information required to verify that the charges on the bill match the actual amount of electricity consumed during the billing period. To illustrate, imagine that the company in Figure A is a Toronto-based location of a large coffee shop chain. The manager is used to ordering coffee by the bag a delivery that can be physically counted and verified upon arrival. This same practice cannot be mirrored when trying to verify electricity consumption. As a result, the manager must accept that the bill is a true reflection of their electricity usage. When reading the monthly electricity bill that manager sees a complex cost structure, making it challenging to determine how these numbers relate to their company s actual electricity consumption. Without the required insights into their energy consumption, a manager is unable to determine where required changes should be made to reduce usage and costs. As we ve covered, consumption is complex and developing these insights can be challenging. How can businesses overcome these challenges? The best approach is to develop and implement an energy management plan. An effective plan will help a manager understand and analyze their consumption so that they can make changes and realize savings. Implementing an energy management plan Not only is it important to understand electricity consumption, but it is essential to conduct a thorough energy consumption and business drivers analysis in order to develop a plan, and adopt tactics that aim to reduce it. Planning is a key step when it comes to achieving business objectives. By that same philosophy, developing an energy management plan is the only way to reduce consumption and achieve cost saving objectives. Measuring and monitoring the resulting data will drive efforts towards a cycle of continuous improvement. In a world where rising energy costs are inevitable, a solid plan is a necessity, not an option. 5 Harnessing big data to kick-start your energy management plan

6 FIGURE C Energy Management Plan Energy management is the proactive, organized and systematic coordination of procurement, conversion, distribution and use of energy to meet the requirements, taking into account environmental and economic objectives. The VDI-Guideline Definition 4 ACT Management review CHECK Monitoring, measurement and analysis Nonconformities, correction, corrective action and preventive action PLAN Baseline Energy performance indicators Energy objectives and targets Energy management action DO Competence, training and awareness Communication Operational control Design Procurement Developing your plan with the right tool: a big data energy software platform 1. ACCESS ELECTRICITY CONSUMPTION INFORMATION In order for an energy management plan to help businesses achieve consumption savings, managers must understand the current state of their energy dynamics how much electricity they actually use at any given point as it is affected by their operations or the weather. To do this, they must first collect all of their utility billing data which includes access historical consumption data from the past two or more years. This data provides the transparency required to identify opportunities for improvement and waste elimination, and offers insights into what is driving their electricity spend. Second, business must gain access to the cost information associated with their consumption. Many Ontario businesses find it challenging to dedicate the resources to manually collect the billing information from their utility companies, as well as ensuring the information is consistently captured, organized and reported on. Companies either dedicate internal or external resources to capture required energy metrics, a task that is both error prone and very time consuming. Rarely, do businesses have the technology backing required to automate this process. 6 Harnessing big data to kick-start your energy management plan

7 An energy software platform built using big data is the optimal tool to start developing a robust energy management plan this tool will become the foundation that will help businesses set and achieve goals designed to reduce their company s overall electricity consumption and costs on an ongoing basis. a. Access consumption data using the energy software platform Connecting utility billing data and sub-meter readings to this tool directly from the utility provider ensures a higher level of data transparency. Once initial access to historical billing data is complete, the tool should collect incoming data on an ongoing basis so that the manager can continue to make comparisons to the baseline and customize it as business needs change over time. For businesses with sub-metering infrastructure, the platform should be equipped with the ability to collect additional data provided by equipment throughout each facility. For example, in a manufacturing plant, sub-meters monitor Significant Energy Users (SEU) throughout the production facility. In a commercial building, automated sub-metering can be used to monitor individual equipment, such as HVAC, indoor and outdoor lighting, refrigeration, and kitchen equipment. This is in addition to the main load meter used by utilities to determine overall building consumption Once integrated with the platform, managers are able to collect and monitor this consumption data on an ongoing basis. When any irregularities in consumption, at either the aggregate or equipment level, the platform can detect which piece of equipment was the culprit, providing real-time alerts to the energy or facility manager. As a result, the manager has real time and actionable information allowing them to make timely decisions to address the issue. 2. NORMALIZE DATA BASED ON DRIVERS OF CONSUMPTION When the utility billing data is collected, it is not yet in an analysis ready state. Before investigating any consumption patterns present in the data, it must be normalized for the main drivers of businesses electricity consumption: business inputs and weather. How to normalize the energy data? MANUFACTURING COMPANIES COMMERCIAL COMPANIES Manufacturing companies should use a production based metric that measures electricity consumption per unit of output. Commercial companies should focus on electricity consumption per square foot of facility space or occupancy. 7 Harnessing big data to kick-start your energy management plan

8 Regardless of industry, consumption data must be normalized for weather, as it has a significant impact on electricity demand. For example, in January 2014 temperatures ranged from -20 to -30 degrees Celsius, significantly lower than the -2 to -10 degree range typical of this season causing prices to double6 over the prior year. If a business had installed LED lighting at the beginning of January 2014 and at the end of the month it conducted a year over year analysis. It would appear as though the LED lighting had a negative impact on energy costs. A closer look at normalized data that takes the extreme weather out of the equation would reveal the true result of the LED lighting investment. The graph below (Figure D) helps to illustrate this point further. The Hourly Ontario Energy Price in 2013 was, on average, 2.5 cents/kwh. The spikes indicate some price volatility within the energy market over the year. In January 2014 alone there was an increase in average HOEP compared to January These major spikes seen in the graph below translate to an unprecedented price increase of 115% compared to the same time last year a direct result of the polar vortex.6 Measuring the actual success of an energy savings project yearover-year is impossible without removing the effects of unpredictable weather. FIGURE D Electricity Prices: Winter 2013 vs Winter Jan 08-Jan 15-Jan 22-Jan 29-Jan 05-Feb 12-Feb 19-Feb 26-Feb 05-Mar Factors including facility size and configuration, peak and off-peak production cycles, and unpredictable weather patterns all have an impact on energy consumption. Normalizing of energy data makes it possible to make apples-to-apples comparisons, and to conduct effective benchmarking, rankings and ROI on energy conservation projects. 8 Harnessing big data to kick-start your energy management plan

9 a. Normalize data using the energy software platform Normalization is a necessary feature of a big data energy software platform. Weather normalization should be fed from multiple weather stations throughout Ontario, ensuring the most accurate analytics are used in the analysis. The tool needs to be easily customizable depending on the metrics required by any type of business to help define the business s base consumption. Weather normalization helps a business to aggregate consumption data across a number of facilities in different locations, where vastly different weather patterns would skew the results of a comparative analysis. FIGURE E Weather Normalized vs Non Normalized Electricity Usage (MWh) Volume (MWh) Normalized Load Jan 05-Feb 05-Mar 04-Apr 07-May 04-Jun 02-Jul 06-Aug 3. DEFINE AN ACCURATE BASELINE According to ISO (the standard created by the International Organization for Standardization (ISO) for an energy management system, that aims to help organizations continually reduce their energy use), the energy baseline is defined as a quantitative reference that provides a basis for comparison of performance. It applies to a specific time frame, and provides a reference point for comparison before and after the implementation of any energy improvements. By normalizing your data for weather and business input metrics, including production or square footage, businesses can more accurately estimate and measure energy savings over time. A typical baseline consists of two years of historical electricity consumption data that has been normalized for business inputs and weather. This baseline becomes the foundation for developing your energy management plan. Going forward, every activity undertaken to improve energy efficiency gets measured against the baseline to determine its impact, as depicted in Figure F. 9 Harnessing big data to kick-start your energy management plan

10 FIGURE F Using the baseline to measure true savings Baseline Energy Savings, or Avoided Energy ENERGY USE Installation of Higher Efficiency Lighting Reporting Period YEAR 1 YEAR 2 a. Define an accurate baseline using the energy software platform After normalization, the amalgamated data can be used to produce a consumption analysis that contains valuable, decision ready information. The resulting report removes the complexity of the market, illustrating the concept of energy management by posing a simple question: are you above or below your baseline? The user can customize the report to view data on a range of time frames, from a general monthly view to a highly detailed look at hourly numbers. As any manager works with hourly data, the platform s big data capabilities present a distinct advantage over Excel based methods of analysis, helping to easily isolate what is causing consumption to deviate from the baseline. Businesses can then utilize the reporting capability of the tool to identify and adopt best practices from a particular month and apply it to business activities going forward. Reporting is an important facet of energy management planning as it gives the user transparency which empowers them to make positive operational changes to decrease usage and costs. Creating a baseline also allows for easy energy benchmarking and ranking. Benchmarking is a key energy management best practice. It helps businesses identify poorly performing operations or buildings, strategically invest in energy efficiency projects, and track the effectiveness of the improvements that are undertaken. Ultimately, energy benchmarking allows businesses to lower their operating costs. 10 Harnessing big data to kick-start your energy management plan

11 What to look for in a big data energy software platform ABILITY TO LINK ELECTRICITY USAGE DATA TO THE BUSINESS A big data platform is able to include all information that is important, allowing businesses to produce reports using metrics relevant to their business. For a company that processes and packages milk, the energy software platform will take its hourly production figures and determine the electricity costs on an hourly basis per litre of milk ($\L milk) from their integrated process control automation systems (PAS). This tool allows managers to compare performance for facilities in the company s portfolio. In commercial property environments, buildings are often equipped with a building automation system (BAS); a centralized, interlinked network of hardware and software set to monitor and control the operational performance of all mechanical, electrical and plumbing systems throughout the building. 7 An effective energy software platform will enable quick and easy integration with the BAS or PAS providing real-time notifications when a specific business activity causes an abnormal change in electricity consumption. With this valuable information, managers can take a proactive approach to diffusing any potential increases in costs associated with the activity. Despite the recent attention to commercial building retrofitting projects, according to Natural Resources Canada nearly half of the energy savings opportunities in commercial buildings remain untouched. 8 Operational improvements low and no cost improvements like changing temperature settings, implementing setback schedules and reducing simultaneous heating and cooling are the hidden and low hanging fruit of energy efficiency. The energy software platform can help businesses realize those savings. HVAC systems in a retail building use approximately 48% of all electricity consumed. Therefore, even minimal optimizations to the HVAC can result in great benefits. 9 For example, optimal temperature within a retail environment is between degrees Celsius. Lowering the temperature by 30-40% overnight (4-8 ºC) would lower store consumption by up to 25%. 10 If the building were to leverage a big data platform, the manager would receive real-time notifications whenever any peaks or valleys occurred in a component of the HVAC system and would be able to better optimize certain equipment to help reduce energy costs and use the data and baseline to demonstrate the ROI of investments. 11 Harnessing big data to kick-start your energy management plan

12 VALIDATION OF ELECTRICITY USAGE AND COSTS Billing errors do happen. Hydro One, the electricity provider for more than one million customers across Ontario, had been billing approximately 3% of its customers with estimated usage, some of whom saw over 50% higher monthly charges for over 10 months. 11 That s approximately 32,000 people and businesses being overcharged for their electricity with no dramatic changes in their consumption behaviour to warrant the billing increase. A big data energy software platform is capable of connecting multiple data sources including their utility s usage data, internal business sub metering system data, and hourly pricing data feeds from their Independent Electricity System Operator (IESO). The combination of these data sources provides the most accurate view of the business electricity usage and costs. FIGURE H Big data energy software platform connects multiple data sources Utility Data Bill Verification IESO Pricing Submeters A platform that allows for such data integration provides managers with the most transparent and validated data both necessary elements to ensure businesses pay the verified costs. The business then has access to this accurate information on a rolling basis, making it easier to set and achieve consumption related business objectives. It is clear that real-time notification of errors is critical. It is the only way to ensure managers are capable of taking immediate corrective action. 12 Harnessing big data to kick-start your energy management plan

13 BENCHMARKING CAPABILITIES As we have mentioned earlier, benchmarking enables businesses to lower their operating cost and maximize profits by defining best practices and most importantly, identifying improvement opportunities. Benchmarking is important in an energy management tool as it allows managers to learn from other facilities and locations within their business portfolio. Energy software platforms allow for easy benchmarking analysis with powerful data visualization. To understand this benefit, consider two facilities one in North Bay that is 10,000 square feet, and the other in Niagara Falls that is 5,000 square feet. Since both locations are at opposite ends of the province the weather is dramatically different. By conducting an initial comparison, the North Bay facility would always yield higher electricity demand during the winter, simply due to the colder climate even without the square footage consideration. However, once the energy software platform normalizes consumption for weather and square footage variables, true benchmarking analysis becomes possible. Normalization of that data allows managers to learn what to do from their best performers and what not to do from their worst. LOCATION Sq ft Weather normalized Electricity Cost Cost of Electricity/sq ft North Bay 10,000 $10,000 $1.00 Niagara Falls 5,000 $7,500 $1.50 more expensive There is often a considerable spread in performance from high to low performers. If the business can mimic the best practices from top performing location at the lower performers, it can raise the average performance of the entire portfolio and profitability of the entire business. 13 Harnessing big data to kick-start your energy management plan

14 FIGURE I Benchmarking savings potential Whether a business is a manufacturing company or commercial operation this type of exercise drives a cycle of continuous improvement. Identifying anomalies in consumption across properties or production lines, and making changes that have already proven successful will constantly drive down consumption. DATA VISUALIZATION A big data software platform gives its user the power to make sense of millions of data points, by providing a graphical representation of that data, called data visualization. The purpose of data visualization is to simplify all the energy data values, and communicate important concepts and ideas to the manager. Data visualization gives business users the ability to use information intuitively, without deep technical expertise. Data visualization represents the data in a way that the manager can easily interpret, saving them time and energy. 14 Harnessing big data to kick-start your energy management plan

15 FIGURE J Sample energy consumption visualization usage and temperature FIGURE K Sample energy consumption visualization usage ranking by location 15 Harnessing big data to kick-start your energy management plan

16 CLOUD BASED SOLUTION An energy software platform is capable of collecting and maintaining unrestricted amounts of data in a centralized cloud data centre. A SaaS (software as a service) application is already installed and configured for the end user. A big data solution that resides on a cloud is typically: lower cost, easy to use, accessible through all standard web browsers, and requires little or no IT implementation. Whenever possible, request for the cost of the platform to be delivered as part of the regular monthly electricity bill. Top business benefits of a big data energy software platform OBJECTIVE SUPPORT FOR AN ENERGY PROJECT PROPOSAL Business managers often find themselves questioning certain energy management practices, concerned that the effects are immeasurable because there are too many changing variables demand, weather, production, facility configuration etc. surrounding it. The real purpose of the baseline is to remedy that problem, and allow managers to evaluate the effects of the activity where all other variables, except those under immediate consideration, are taken out of the equation. FIGURE L Challenges to implementing Sustainability McGraw Hill Construction 2011 Budget (Capital and/or Operational) 77% 74% Implementation/Operational Issues 46% 53% Not Knowing How to Measure ROI from Sustainability 45% 31% Lack of Sufficient Tax Incentives 39% 31% Lack of Knowledge Base 36% 26% Organizational Issues/Lack of Leadership 28% 20% 16 Harnessing big data to kick-start your energy management plan

17 Imagine a company that installs solar panels to the roof of its 20-floor office building. By measuring electricity consumption and spend after installation and comparing it to the weather normalized baseline, it will show if the project was successful in helping to conserve electricity. If consumption drops below the baseline and the cost of the newly implemented technology is promised to be paid back within an acceptable time period, then it was clearly a worthwhile investment. The baseline discovered in the energy software platform will help managers measure the true consumption effect caused by the existing efficiency projects and provide more accurate ROI and payback period estimates. With that powerful tool in hand, energy managers will be empowered to build a future pipeline of energy efficiency projects that are more likely to be approved to proceed. MEASURABLE TIME SAVINGS Many businesses in the market are still using excel spreadsheets to track electricity consumption and cost data. This means a person is manually scanning each electricity bill and typing information into a spreadsheet. This is a waste of valuable human resources, not to mention an error prone process. An energy software platform eliminates this manual task altogether, instantaneously collecting data without sacrificing accuracy. The platform enables the business to shift focus from transactional tasks to more strategic initiatives, as employees can now concentrate solely on data interpretation rather than input a much more productive use of man-power. The switch in responsibility empowers users to make decisions aimed at improving the consumption patterns evident in the data. They have the ability, and more time, to measure the success or failure of these decisions and adapt the energy management plan to ensure continuous improvement. Conservation programs over the 2009 and 2010 period cost businesses less than five cents per kilowatt-hour. This compares to five to 80 cents per kilowatt-hour if that energy had to be generated Conservation Results Report12 STRONG ROI All managers want to ensure a new technology generates high enough return on investment to justify its implementation. A big data platform will provide managers with the tools to understand and analyze their consumption data. Armed with this data managers can set goals and implement new energy efficiency initiatives. As the old English proverb says: you can lead a horse to water, but you can t make it drink. Similarly, an energy software platform can t actually reduce consumption for a business, but it can point it in the right direction. Ultimately, it s the actual conservation actions the business takes that will drive improvements and maximize ROI. 17 Harnessing big data to kick-start your energy management plan

18 Take a page out of Toyota Motor Manufacturing Kentucky (TMMK) Inc. s book and look at energy as a controllable number. Mark Rucker, the individual in control of the company s electrical systems, stresses the importance of implementing a utility metering system in order to collect and analyze facilities consumption data, without which there is no case to be made for sustainable energy reduction initiatives. Through the installation of energyefficient equipment and streamlined operations, the massive manufacturer of over 500,000 vehicles a year that s roughly 2,000 vehicles per day in two production shifts per day, five days a week managed to cut their annual energy consumption by nearly 50%. 13 RISK MITIGATION: BETTER UNDERSTANDING OF ENERGY CONSUMPTION Using a big data platform to conduct a thorough consumption analysis is an important step in developing an effective energy management plan. Part of that planning process is to set consumption reduction goals and experiment with energy efficiency initiatives to achieve them. What happens to the electricity consumer who chooses to forego energy management planning? Drift. Drift refers to consumption levels that gradually increase on a yearly basis unbeknownst to the consumer. When a new project is undertaken and consumption levels are not monitored there is no way to measure the impact it had on energy usage. A simple example illustrates the consequences of drift consider a company that institutes a policy that all monitors must be turned off before leaving the office at night. At first most employees will be diligent about abiding by the policy, which will reduce overall consumption. However, without continuous monitoring and enforcement people quickly fall back into old habits, and eventually, employees forget to turn their monitors off and consumption creeps up again. This policy should help the company reduce its energy use; however, without monitoring the actual effects of the policy it is impossible to determine how much consumption changed, if at all. Companies that do not have an energy management solution in place are always going to be at risk of drift and increasing consumption. 18 Harnessing big data to kick-start your energy management plan

19 Summing up: Becoming an empowered energy consumer Electricity should not be treated like a fixed budgeted line item; but rather, as a variable cost that can be reduced by developing and executing a comprehensive energy management plan. If your business wants a transparent look at your billing and consumption data, Bruce Power Direct can help. Our big data energy software platform, the Virtual Energy Manager (VEM), can generate potential savings from 10 25% of your total electricity spend on an annual basis by: Collecting billing data directly from the utility company to provide accurate and transparent data; Integrating with standard building and process automation systems (BAS/PAS) to monitor all consumption related activities in a building in real-time; Normalizing collected data for business-specific drivers of consumption and weather to define an accurate baseline; Aggregating data across different time frames and facilities within a company s portfolio to facilitate benchmarking; Measuring and validating your investments in energy conservation projects to help achieve your consumption objectives. Become an empowered electricity consumer. Let us help you kick-start your energy management plan. About Bruce Power Direct Our combination of world class assets, powerful data and team of experts, is unparalleled in the Ontario energy market. Bruce Power Direct delivers innovative energy management solutions that help leading Ontario private and public sector organizations manage their energy more effectively. For more information about this whitepaper, contact: Chris Loughren Manager, Commercial Energy Solutions Bruce Power Direct chris.loughren@brucepower.com Phone: Toll Free: Bruce Power Direct 123 Front Street West, 4th Floor Toronto, ON M5J 2M Harnessing big data to kick-start your energy management plan

20 Sources 1 Canada. Ontario Ministry of Energy. Achieving Balance: Ontario s Long Term Energy Plan Ontario Ministry of Energy, Dec Web. Feb < story/ >. 2 SME Benchmarking Report Industry Canada rprt-flw.pub?execution=e1s6 3 SME Benchmarking - Plastic Product Manufacturing (NAICS 3261) VDI (The Association of German Engineers) -Guideline VDI 4602, page 3, Beuth Verlag, Berlin Kigar, Jake. Polar Vortex Resurfaces, Bringing Frigid Temperatures to Toronto, Central Canada and The Prairies. National Post News. National Post, 20 Jan Web. Feb < nationalpost.com/2014/01/20/polar-vortex-resurfaces-bringing-frigid-temperatures-to-toronto-centralcanada-and-the-prairies/>. 6 IESO Weekly Market Report January 28, weekly/ pdf 7 Understanding Building Automation and Control Systems. KMC Controls. KMC Controls Inc., Web. Feb < Control_Systems.aspx>. 8 Natural Resources Canada - Buildings Energy Efficiency - statistics/scieu09/scieu_e.pdf 9 Prada, Wayne E. Selling Conservation: How to Secure Buy-in from Senior Executives. N.p.: Sears Canada, PDF. 10 Demand Responsive Commercial Buildings - National Research Council Canada gc.ca/ctu-sc/ctu_sc_n81 11 News, CBC. Hydro One Billing, Customer Service to Be Investigated. CBC News. CBC/Radio Canada, 04 Feb Web. 07 Feb < Conservation Results Report - conservation-results-report 13 Bachman, Kate. How Power Metering Empowers Toyota. Sustainable Manufacturer Network. Fabricators & Manufacturers Association, International, 24 July Web. Feb < 20 Harnessing big data to kick-start your energy management plan