
Load Management Group
In partnership with PLMA, this group is for practitioners from energy utilities, solution providers, and trade allies to share load management expertise and explore innovative approaches to program delivery, pricing constructs, and technology adoption.
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Managing Loads in a Smart Way

Demand Side Management (DSM) will play an important role in the development of smart grids by managing loads in a more effective way. DSM applications, realized via Home Energy Management (HEM) systems for smart buildings and even cities, will provide many benefits:
- Consumers can realize electricity price savings
- Utility companies will operate at greater efficiency.
- More renewable energy can be integrated on the grid
- Smart charging of electric vehicles will become commonplace
Global energy demand is increasing rapidly in comparison to the availability of energy generation and transmission. Consequently, a widening of the supply and demand gap becomes inevitable in traditional grids. Many utilities respond to this situation by increasing the total generation capacity. This results in underutilized plant for much of the time. Demand Response (DR) is one option for better load management.
United States electricity usage data show that 42% of energy is consumed by household appliances. Major forces are creating a new paradigm for domestic electricity markets as energy optimization becomes an increasingly important facet of the electricity supply sector. New technologies are being deployed, including advanced meters, controllable appliances (the Internet of Things), distributed energy generation and storage systems, i.e., electric vehicle batteries, as well as stand-alone storage, and the use of hydrogen fuel cells.
Smart home appliances have been trialed to utilize residential energy consumption more effectively. For DR to be effective, it needs to be highly automated, at both the supplier and consumer end of the operation, so it can have a marked effect on energy utilization. This means home Energy Management Systems using advanced software, and Smart Cities, where everything from street lighting to sewage transport fall under the purview of machine learning systems which can adapt to circumstances. It is also easier to install these systems while construction is underway, than retrofitting them to existing buildings which suggests that the most likely smart cities will be “new builds” on greenfield sites to maximize the benefit all round.
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