Demand response can increase access to clean, affordable, and secure energy. Demand response can ease the challenges of carbon neutral transition of the energy system. The electrification of society increases the demand for electricity, e.g. data centers, electric vehicles, heat pumps, etc. At the same time, renewable energy is becoming cheaper: the price of solar and wind power has fallen rapidly and is already cheaper in some places than electricity produced with fossil fuels. Weather-dependent RES production increases the need to balance the electricity grid. In addition, battery technologies have developed rapidly. 

Demand response can also reduce the energy costs for peak power timing. There are high price peaks in the electricity market and reserving capacity for those binds capital and affects consumer prices. The capability for cutting peak power can reduce the size, and thereby the price of the electricity connection to the power grid if the peak power capacity needed would be smaller.  
 

Demand response is linked with:  Building automation and control systems (BACS); home energy management system (HEMS); AI-based energy management agents...

It can form a solution bundle (or a package of solutions) with monitoring and control systems (e.g. smart meters, intelligent devices, aggregators' energy management systems), local RES, energy storage, EV charging, and standard-based ICT solutions (system interoperability).

The bundle can be used for Nearly Zero Energy Building (NZEB), Positive energy building (PEB), Positive energy district (PED) or Virtual power plant (VPP)

Connections also with: 

• Economic incentive to connect buildings
• peak power cutting: reducing energy costs.
   

Technical aspects:

Solution requires both technical interoperability and the contract for demand management with an aggregator. Data transfer standards and technical interoperability are required for the whole demand management chain (from aggregator to building level).

Economic context:

Business models for sharing the economic benefits of the demand management for all participants (win-win-model). Business models for profitable integration of local intermittent RES production to the grid.

Policy and regulatory/legal framework:

Related to removing legal and regulatory barriers for energy communities: Among others, the current legalisation hinders the selling of electricity to neighbouring plots; and the taxation of the capacity limits small-scale power generation. Lots of variation in national level regulatory barriers, depending on the level of development in the country. 

Economic:

The economic incentive for the building owner is still often quite minor: the economic benefit of the demand management can be small for a single building, even when virtual power plants formed from large building masses would be very beneficial for the overall sustainable power generation.

Technical:

Technical readiness (both hardware and software) is currently often missing from the buildings; usually small investments are required at the buildings to start using demand management in a building. Intelligent algorithms (AI-based energy management agent) are usually missing.  

Building owners have difficulties seeing and getting the economic benefit: it is very small for the building owner, which is a drawback for the broader uptake of demand response. (For example, case studies with 1000€ profit per year for an individual building owner, against the cost of adjusting building systems: the profit is rather small and has not been very motivating, at least before 2022). Extra benefits could come also via additional services, e.g. related to the building performance and status.

Systems are not standardized now: every case needs to be built from scratch. Interoperability and standards would solve this, and ease the starting to implement the demand response.

Impacts should be monitored on the aggregators' side or on the power grid side:

• Energy savings are assessed via energy flows and energy balance: this requires an optimized overall energy system, including demand, generation, storage, and energy sold/bought (MWh: total, per m2).
  • District heating networks: Peak shaving up to 30%, reduction of primary energy needs up to 5%.https://doi.org/10.1016/j.energy.2020.119440
  • Application in 27 buildings of student apartment in Finland(Tampere):  peak reduced up to 15% and energy/cost/emissions reduced up to 9% https://www.mdpi.com/2624-6511/3/2/9
• Building level indicators
• Aggregator level indicators
• CO2 reduction impact: from the total electricity generation status to the grid at each time (which energy sources are being used, transferring loads to times that have more sustainable energy production): (this can be difficult in practice)
• Costs of energy (at each time): (this can be difficult in practice)

• Demand response management strategies at district level have been estimated in Groningen as having the potential to reduce energy costs by 30% (MAKING-CITY project)

Demand management is often one element in energy communities (https://netzerocities.app/resource-618)

• iFLEX EC funded project about demand management, link to deliverables
• MySmartLife SCC Lighthouse project: demand management demonstrations in the lighthouse city of Helsinki