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These crucial questions determine who applies the smarts to the grid and how efficiently those smarts realize the promise of Smart Grid technologies. .
These are:
In the Pure Market model (figure 1), the only information flows required are the changing price signals from the wholesale to retail (end user) side of the market. This is fundamentally how the wholesale market functions now. It is a matter of extending to end-use customers the same price signals that generators rely upon for their decisions on scheduling of generation. When end users are exposed to similar information but with an inverse incentive—what was a sell price for the generator is now a purchase price for the customer—the market has the potential to reach a supply-demand equilibrium that is currently unachievable.
Figure 1
Only limited change occurs on the supply side in the Pure Market model. Dispatchable, distributed generation continues to respond or be scheduled based on the locational value of the energy it can generate, and renewable energy resources are paid based on their locational value when they do generate. Likewise, the wholesale market sees aggregate demand by location exactly as it does today, with the exception that the Smart Utility must take into consideration new demand elasticities in response to prices when forecasting supply requirements. That shouldn’t be too great a challenge as the concept of the “law of large numbers” (of consumers) continues to hold for operational and planning purposes – there is now just more information.
What is the implication of the Pure Market on my opening questions of Decision and Control? The Pure Market is first and foremost about empowering the end user through price signals and information. The Smart Customer makes all decisions as to when and how much to consume based on market conditions, and is responsible for controlling energy use either manually or more likely through innovation in information processing technology.
The Intermediated Market model (figure 2) is characterized by having a key player between the wholesale and retail (end user) sides of the market. This is a Load Aggregator or an Energy Service Company (ESCo). The Aggregator has contracted with the wholesaler to either buy at spot prices and sell at tailored rates to retail customers (energy, or kWh), or limit load based on the utility (supply side) calling for reduction in capacity (KW), or both.
Figure 2
In energy mode the Aggregator tailors the customer rates based on its ability to purchase at spot and sell at a tailored rate knowing the individual customer’s consumption pattern relative to the Aggregator’s total customer base. In the capacity mode the aggregator has contracted with the wholesaler to supply negative capacity (demand response) and with consumers to control energy consumption when called. In both modes the Aggregator is sharing the financial benefits (savings in kWh or KW) with individual consumers.
Regarding Decision and Control, the end user makes the decision as to whether and how to participate based on the market information provided by the Aggregator. In the energy mode the end user maintains control of consumption either manually or through technology. In the capacity mode, the end user has made the decision (for a financial benefit) to turn over control to the Aggregator. The utility is, in effect, outsourcing direct control and customer contact in order to achieve more efficient operations (average cost per kWh) and/or savings in capacity investment costs through the Aggregator’s direct control of customer load when needed.
The Microgrid Market model (figure 3) is characterized by balancing or attempting to balance energy between supply and demand within a predetermined electrical/geographical area. Within each microgrid, a portion of energy will be supplied by local generation connected at the distribution level, a significant share of which would likely be renewable such as small-scale wind turbines and rooftop solar. The expectation is that both supply and demand will be operating in response to real time price information or equivalent internal signals designed to maintain balance. Within the microgrid there is the potential that many of the individual energy use appliances could be monitored and controlled in order to balance supply and demand but this need not be the case.
Figure 3
In the Microgrid model, interaction with the wholesale system is minimized. The larger, centrally controlled resources, dispatchable by an external system operator, exist to provide back-up power as needed, and possibly will provide the bulk of baseload requirements to the microgrid. To maintain balance both within the microgrid and the larger power system will require real-time communications and control.
Decision and Control on the microgrid can be at either an aggregated local level or left to every individual. In the most cooperative design, the end users’ decisions are made in the aggregate with individual decisions being subsumed in the objectives of the micro grid system. Control of a cooperative modeled microgrid will lay with the grid operator that can be either an organization as in the more centrally controlled model (below) or an automated system responding to hierarchical control rules. At the other extreme, decisions are made by the individual, although that requires advanced signaling in order to align individual preferences with the potential supply volatility within the microgrid.
In the Centrally Controlled Market model (figure 4), the utility monitors and controls the operation of appliance level consumption devices in order to minimize cost of operations and reduce capital costs by controlling peak demands. We see the nascent appearance of this model in utility-managed direct load control programs, such as the remote control of air conditioners. Aspects of a centrally controlled market may be combined with other models, the question is only how far the centrally controlled market model should be pushed.
Figure 4
In its fully developed form, the Smart Utility in this model could monitor and control the operation and disposition of distributed and renewable energy sources in order to maximize their value given “complete” knowledge of locational and aggregated supply and demand. Given total utility control, there would no longer be a meaningful differentiation between retail and wholesale, as the utility operates both to its desired outcomes.
Decision and Control in the Centrally Controlled model rests entirely with a central entity. The end user has made the decision to turn control of individual consuming devices over to that Smart Utility, which constantly monitors the status of end user devices and schedules their energy use.
In all likelihood, the actual form that the Smart Market takes will not fit neatly into one of these models. Rather, there will be mixing and matching as business strategies are rolled out and the results come back from early pilots. Furthermore, there will be no uniform design across the country for the architecture of the Smart Grid, as each state jurisdiction and each utility charts a different course. All that is clear now, at the starting line of Smart Grid development, is that each stakeholder stands to gain substantially different things depending on the design outcomes.
Richard Tabors is Vice President in the Energy & Environment Practice of Charles River Associates. He is a retired Senior Lecturer in Technology & Policy at the Massachusetts Institute of Technology, and co-authored the book Spot Pricing of Electricity.
The views expressed in this article are those of the author and do not necessarily reflect the opinion of Charles River Associates or its Energy & Environment Practice.
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