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How software controls can bridge the gap between wholesale market prices and consumer behavior.
As ideas go, a microgrid is nothing new. Think of steam pipes for district heating in older urban cores. But add a few software controls, and the possibilities grow.
A microgrid-in our case a simple aggregation of electrical loads and generation-can take many forms: a shopping center, an industrial park, or a college campus. Within the system, you may find fuel cells, microturbines, or reciprocating engines. Typically, the generators within the microgrid also supply heat for local needs, such as space heating or dehumidification.
From a utility's viewpoint, the microgrid looks just like a single electric load. But seen from the opposite side-from behind the meter where the consumer resides-a microgrid can function as a distributed energy resource (DER). It can produce value both by (1) maximizing energy and thermal efficiencies to reduce electric demand, and (2) selling useful product back to the integrated utility grid in the form of ancillary services, like voltage control or regulation.
Microgrids might even help the industry achieve the elusive goal of demand response-a feature now missing from electric industry restructuring models, which lack retail tariffs that expose consumers to the real market consequences of their decisions about power usage.
In fact, a study has shown that using microgrids for load management not only benefits those consumers who use the technologies, but also lowers the wholesale market prices paid by all consumers.
All that is needed to start the revolution is a system of software controls called an EMS (energy management system). The EMS is the system that dispatches the power output of the generators (e.g., microturbines, reciprocating engines, fuel cells, and photovoltaic cells) and controls the heating and cooling equipment (e.g., boilers, chillers, fans, desiccant removal, dampers, etc.).
In the simple case, EMS can optimize generator performance. But beyond that, an EMS can integrate various decisions on energy production, consumption and storage within the microgrid-and then coordinate them with such other factors as thermal energy conservation, emissions limits and credits, and wholesale market attributes such as transmission congestion and locational marginal energy prices. These decisions will be based on the heat requirements of the local equipment, the weather, the price of electric power, the cost of fuel, and other considerations.
Of course, real-time price data is first required. But with that information, microgrids could provide a highly elastic demand curve for wholesale energy markets. That would be of significant value in a day-ahead market, where the EMS could bid in "capacity" based on anticipated weather and process plans.
Other technical problems remain as well. A primary example would be conventional protection schemes that are designed chiefly for one-way power flow from the source of supply-the substation-to the load points. With two-way power flow, conventional protective relaying and fusing based on fault current levels will not work properly because the fault current levels will vary greatly depending on the number of connected generators, system configuration, etc. Getting around this problem will require development of fault detection systems that can operate on a