Next Generation of Energy Demand Management

Author:

Dogan Yiginer; Elizabeth Kim; Miro Mo; Irakli Urushadze

When Benjamin Franklin first introduced the concept of electricity to the general public in 1740, he was greeted with skepticism, ridicule, and misbelief. We think about the impact electricity has had since then, it boggles the mind why we didn’t see the value immediately. How could anyone have underestimated the power of electricity? Can you imagine a life without it?

Fast forward a few centuries, and since 1990, the growth rate of electricity generation has been higher than that of total energy consumption. Global electricity generation is expected to grow at an average annual rate of 2.6% till 2030 and is directly correlated to a nation’s GDP. As we stand in 2017, the industry faces a different set of challenges. What challenges are those, you ask? Let’s get technical for a quick moment.

Globally, electricity use varies significantly on short (daily) and medium (seasonal) time frames. Regular variability in demand is attributable to daily activities, with the highest peaks observed on extremely hot or cold weather especially when combined with large regional events like sports. Fig1 shows the annual variation in demand reported by PJM interconnection(US). Since electricity cannot be stored efficiently, it is generated as needed and thus, power generation stations must at least meet demand in order to prevent blackouts as oversupply of electricity to the grid system is wastefully converted into heat.

Fig 1: Hourly and Average annual demand in PJM interconnection (August 2012-July 2013)

Source: US Energy Information Administration, based on PJM data

In addition, the variability in demand differs across different user segments like residential, commercial and industries. Fig 2 shows the retail sales (demand) of electricity to different end-user segments(US) from 2009-2012. Here, it can be observed that homes show the greatest seasonal variation.

Fig 2: Retail sales of electricity by end-use segment (2009-2012)

Source: U.S. Energy Information Administration, Electric Power Monthly

If you take a look at GDPs across the world, under developed companies are now having the fastest growing GDPs. In electricity language, that means, the places that are underinvested in electrical power and grids will see a rise of demand over the next century. How are electrical companies to predict how much power to generate without waste, and if they have the resources to provide them? How will distribution centers calculate where to place the power lines and how much of them to make? One thing is clear. The industry will have to identify goals to meet the demand, while being sustainable and profitable for the next generation of electricity-users.

SOCIAL AND ENVIRONMENTAL SUSTAINABILITY GOALS

Spearheaded by the United Nations, one of the Sustainable Development Goals was to achieve affordable and clean energy by 2030. Specifically –

• By 2030, ensure universal access to affordable, reliable and modern energy services
• By 2030, increase substantially the share of renewable energy in the global energy mix
• By 2030, double the global rate of improvement in energy efficiency
• By 2030, enhance international cooperation to facilitate access to clean energy research and technology, including renewable energy, energy efficiency and advanced and cleaner fossil-fuel technology, and promote investment in energy infrastructure and clean energy technology
• By 2030, expand infrastructure and upgrade technology for supplying modern and sustainable energy services for all in developing countries, in particular least developed countries, small island developing States, and land-locked developing countries, in accordance with their respective programmes of support

To achieve these objectives, we need to continuously improve the energy supply chain and design actionable goals:

1. Improve demand forecasting

In order to build adequate power capacity, precise forecasting of demand for electricity is necessary at the power generation and utility side. Demand forecast is usually carried out at three levels: long, medium and short term. Long term forecast is used for taking policy decisions, system planning and resource allocation. Medium term forecast helps in planning yearly maintenance activities of power plants and monthly peak and energy demand managements while short term forecast help in day-to-day operation of power plants and electrical network to manage daily loads effectively.

However, with increasing power demand and accompanied variability, it has become significantly difficult for power utilities to forecast the demand precisely. Difficulty in forecasting and resulting variability in demand has a significant impact on cost-of-operation and environmental externalities.  Also, conservative forecasts have often resulted in power companies building larger-than-required utilities and hence have incurred significant overage costs in meeting the demand.

2. Reduce the use of auxiliary supply sources

When a peak in demand occurs, the utilities usually turn on older, less efficient power plants thereby producing and supplying ‘less-green’ electricity. The energy generated is expensive and significantly more carbon intensive. Sometimes, Utilities need to rely on cross-border power sources; asking generators of all kinds to come on or off the grid to help them balance supply and demand, or to manage ‘constraints’ – effectively bottlenecks – in the network, to meet the demand. Also, Utilities need to constantly spend significant resources to balance the system and hence incur significant costs in the process.

3. Reduce price variability

Presently, the instantaneous financial and environmental cost of using the above mentioned “peak-hours” sources is not necessarily reflected in the retail pricing system. Hence, the present methodology of managing demand variability has been creating cost crunches to the supply side. Also, it is important to note that in many markets, consumers (particularly retail customers) do not face real-time pricing at all.

Fig3 shows the how real-time energy prices varied with demand PJM interconnectionUS during the mentioned week.

Fig 3:  Electricity demand and real-time prices in PJM interconnection

Source: US Energy Information Administration, based on PJM data

High real-time prices as seen in the above graph indicate opportunities for demand response programs and technologies to reduce demand or shift demand to lower-cost hours.

There is an increasing need to better predict our future energy usage. Understanding the way we use energy, allows us to hope that one day we can control how much we utilize and can manage our precious energy resources.

BUSINESS MODEL INNOVATION

State clearly the context and the social/environmental challenge addressed

Business model innovation is needed to address the inefficiency in energy usage due to variability, and achieve the above stated goals 1) improve demand forecasting, 2) reduce the use of auxiliary supply sources, and 3) reduce price variability.

Since an important factor of the variability in energy consumption is customer behavior, if the power companies could control customer behaviour, there would not be the traditional overage costs of over-procuring energy or over-building the power infrastructure to compensate the significant underage costs of electricity supply. Instead of handling the variability in the customer demand through such costly supply-side management strategies, the power companies can use a portfolio of demand-side management strategies to reduce demand variability through the following two methods:

Smart Meters

A smart meter that can digitally send meter readings to the energy supplier. It can measure real-time energy consumption accurately unlike conventional meters that needs a visual inspection to gauge consumption. Currently, meters installed in most countries cannot communicate remotely nor differentiate energy consumption during peak hours/off-peak hours. With the smart meters, power company can use dynamic pricing, thus incentivize customers to use electricity during off-peak hours. The real-time consumption data can be displayed via various platforms like home-energy monitors or smartphone applications.

Source: Smart-meters “What is a smart meter and how do they work”

Direct-Load Control Program

Traditionally, consumers use energy whenever and however they feel like at any time. Through a direct-load control program, users can give control of their non-critical systems to utility companies.  When electricity begins to peak, the technology can enable power company to switch off or curtail the amount of the customers’ non-critical system for a short period of time, e.g. cooling/heating system. The new technology ensures that demand would not exceed the supply during peak hours (avoid events of power cut-off) and customers would not pay higher bills for usage during peak hours.

Source: Demand response, Kiwi power limited UK

Distributed energy resources (Decentralized Power)

Distributed energy is generated or stored by a variety of small, grid-connected devices referred to as distributed energy resources (DER). Conventional power stations are centralized and often deliver electricity to households over a long distance. DER systems are decentralized, flexible and located closed to the loads they are providing energy to. DER systems usually use renewable energies, including solar and wind power and when paired with battery systems can supply to the peaks in electricity demand, they can be managed and controlled within a smart grid.

WHY THIS COULD BE GAME CHANGING

According to Richard Kauffman, the Chairman of Energy and Finance for New-York, power companies in operate at 57% capacity utilization compared to 71% in US manufacturing and 79% in US automobile industry. In addition to the low asset utilization levels, utilities over-procure power due to high underage costs of a power outage. In North America, power companies procure approximately 15%-50% excess capacity in addition to their demand forecast, referred to as “reserve margin”, as shown in the diagram below.

According to an Electric Reliability Council of Texas(ERCOT)report, the cost of maintaining a 14% instead of 10% reserve margin would cost Texans US$100M annually.

Further, In emerging economies where capacity of the power infrastructure cannot meet demand and outages happen frequently, this innovation can alleviates outages by reducing the variability in demand.

The innovations will reduce risk significantly for utility companies in the following ways:

1. Through smart meters, risk of excessive-demand in peak-hours is shared with users incentivize them to use less electricity, enabling better control on demand.

2. Through Direct-Load Control Program, risk of excessive demand is reduced because utility companies can make decision of switching-off/reduce energy consumption on behalf of their users.
3. Risk of under-utilization of energy during off-peak hours is reduced: Suppliers provide certain amount of energy per day and the supply is usually stable.  Since demand is smoothed out, energy supplied during off-peak hours are better utilized.
4. Through Distributed energy resources (Decentralized Power), risk of variability is reduced because the energy-storage device balance out both upwards and downwards variability.
5. The financial growth and environmental impact form feedback loop that more customer adoption of the new approach generates great cost-savings as well as environmental impact, and thereafter more customer would buy in.

IS ANYONE IN THE WORLD IMPLEMENTING THIS?

Electricity demand-side management has been implemented at various levels in developed and emerging economies. Utilities in California, Texas and New York spearhead the largest demand-side management. For instance, New York’s ConEd aims to procure a portfolio of DER worth US$200m to avoid building a new substation worth US$1.2bn. The power company intends to fund energy efficiency upgrades to customer’s electrical and mechanical equipment, lighting and cooling systems to reduce the load on the company’s constrained-grid. In addition, the company is providing incentives to customers to install various DER such as standby generators, solar panels, smart thermostats, thermal and electric storage devices. ConEd’s incentives come with a contract giving ConEd power to control the DER to shift power usage from peak periods to off-peak periods. ConEd provides no-cost smart thermostats to eligible customers in the constrained networks when the customers opt-in for the Direct-Load Control program which increases thermostat cooling set-points during hottest days of the year to reduce the peaks in demand.

Further, Tesla has expands into the energy storage business for residential and commercial electricity customer through the Power-Wall capable of offsetting 7kW of load at the customer’s facility.

POTENTIAL COSTS OF RISKS IN IMPLEMENTATION

Financing

The cost of smart power devices continue to drop significantly as have green power sources and battery technology. This has made wide-scale rollouts of this technology economically feasible. However, 2 key financing challenges do exist for our innovation:

1. Who pays?- There are three main customers who we solve problems for. 1^st power companies who no longer need to invest in additional capacity or use old power generation methods. 2^nd, end consumers, who no longer need to pay for the costs of high capacity systems. 3^rd, governments, who often subsidise power or own the power companies. Ideally a blend of these three pay for the investment in cleaner, greener, more efficient power.
2. Company financing- The cost of procuring and installing all of these devices represents a significant cash investment. Our aim is to work with stable governments to obtain cheaper bank financing and take partial payment early to finance these costs.

Customer willingness to change behaviour

Smart meters allow customers to real-time monitor their electricity usage and prices with the aim of changing their behaviour. Many customers will choose not to allow the smart meters to automatically switch down some devices with the concern that their air conditioner will shut-down during peak summer heat. Further even through allowing the customer to self-regulate their behaviour, the smart meter could have the opposite to the intended effect as:

1. Customers may change their behaviour to use more off-peak power however through dynamic pricing the off-peak power prices will increase as demand increases, this reduces the benefit for customers and they are likely to switch back to old habits.
2. Smart meters showing customers dynamic pricing monetizes every usage of power down to the minute. Studied of shown by putting a direct price on an activity as opposed to indirect, people can frequently increase their usage of that good/service as they can justify spending the money and may not feel the ‘guilt’. We plan to mitigate this effect by including clearly visible metrics on how environmentally friendly the power consumption is in addition to dynamic pricing and total fees accumulated for the period.

The ultimate goal of this business model innovation is to reduce the need for traditional electricity generation firms to need to build high capacity into the system, thereby reducing the cost of production saving taxpayers and consumers of electricity as-well as reducing the industry’s contribution to global warming. However the excess capacity already exists in most modern nations which means the time to see the impact of reduced costs will only occur as existing power stations are decommissioned rather than upgraded; this often has long time horizons and therefore may reduce the willingness of power companies to invest in our technologies now. This is why we propose first targeting those nations who are running close to peak capacity and can avoid investing further into traditional power and also nations wanting to implement this technology to reduce costs into the future.