Demand-side management by real-time market-based control

Energy Transition and the Distribution Grid

Future distribution grids will very much differ from what we currently define as a distribution grid. Deregulation of electricity markets, along with electrification of transportation and heating, and the shift towards cleaner renewable energy resources are all inevitable, together with their effects. Future distribution grids will be characterized by[i] [1]:

  • Self-interested prosumers (producers/consumers) with bi-directional power flows, different characteristics and preferences.
  • High number of electric vehicles (EVs) and heat pumps (HPs).
  • High penetration of renewable energy sources (RES).

Such a transition to the new distribution grid offers great advantages from the environmental, economic and energy efficiency points of view. The competition among different independent parties in a deregulated market environment leads to economic efficiency, which consequently leads to higher utilization of cheap, clean energy resources. Also, electrification of transportation and heating replaces inefficient parts of our energy system with their more efficient alternatives.

However, disadvantages are also present, for example:

  • Current distribution grids are not designed to handle bi-directional power flows.
  • Demand peaks caused by EVs charging simultaneously, usually when people start returning from work, or HPs switched on simultaneously on cold days exceed the capacities of the current distribution grids.
  • Uncertainties caused by RES due to weather conditions, increase the difficulty of supply/demand matching.

Therefore, the need arises to act. Figure 1 shows the impact of EV charging on a distribution grid with only 47% penetration of EVs [2]. While uncontrolled charging, and cost minimization result in high demand peaks, these peaks can be avoided by coordinated charging.


Figure 1 - Impact of EV charging on distribution grids

Figure 1 - Impact of EV charging on distribution grids


Demand Side Management

While investing in grid expansions and reserve generation may seem like an intuitive solution to the problem, it is very inefficient[3]; For example, expanding an existing grid to accommodate a load peak that occurs for a very short time (see figure 1) is not a sound investment strategy. Similarly, installing reserve power plants to compensate for the uncertainty caused by RES would be a bad investment decision and would have dramatic environmental effects.

For this reason, Demand side management (DSM) solutions are being developed[ii] with the objective of coordinating among resources and devices on the distribution level, in a manner that achieves economic and environmental efficiency, and maintains system operability. Some of the most developed DSM solutions are [1][4]:

  • Top-down switching: A central controller determines which devices to supply/consume what amount of energy, regardless of personal preferences (centralized-one way communication).
  • Centralized Optimization: A central optimizer receives the requirements of prosumers and attempts to schedule their operation in an optimal manner (centralized-two way communication).
  • Price reaction: Prosumers are allowed to determine their production/consumption according to price signals (decentralized-one way communication).


Market-based Control for DSM

An effective DSM technique is the use of Market-based control (also known as transactive control). Here, prosumers submit their supply/demand bids in real-time to a market place. When the market is cleared, each prosumer receives his assigned price and takes an action based on the previously submitted bid[1] (see figure 2).


Figure 2 - Market-based control

Figure 2 - Market-based control


A well-designed market-based control system requires a prosumer to declare only the amount of power he would like to supply/consume and the price he is willing to pay, thus preserving prosumer privacy compared to centralized approaches. Also, autonomy of decision making is increased. System reaction to the market clearing process is known and flexibility resources are fully utilized as they aim at maximizing their own benefit. These are all features suitable for a distribution grid where a large number of prosumers with different objectives and parameters are connected[1][4].

Open Research and Discussion

In this field, many open research problems still exist; for example, real-time supply/demand matching is a must in electrical power systems; therefore, the cycle of formulating bids, collecting them, market clearing and price communication must be done in very little time. In that case, algorithms are required for small prosumers to determine their optimal bids. The different characteristics of these prosumers and their small computation capabilities are challenges facing the development of such algorithms[5]. Also, in order to achieve efficiency in electrical power systems, planning ahead is required[5][6]. However, with so much uncertainty, this becomes a harder task. The collective response of a system to changes in real-time price is also important to study (e.g. how to reduce demand peaks rather than shifting them to lower price periods) is still an open question[7]. Incorporating physical network constraints and parameters in the control mechanism remains an open research direction.


[1]     J. Kok, “The PowerMatcher: Smart Coordination for the Smart Electricity Grid,” Amsterdam: Vrije Universiteit, 2013.

[2]     E. Veldman and R. A. Verzijlbergh, “Distribution Grid Impacts of Smart Electric Vehicle Charging From Different Perspectives,” IEEE Transactions on Smart Grid, vol. 6, no. 1, pp. 333–342, Jan. 2015.

[3]     N. O׳Connell, P. Pinson, H. Madsen, and M. O׳Malley, “Benefits and challenges of electrical demand response: A critical review,” Renewable and Sustainable Energy Reviews, vol. 39, pp. 686–699, Nov. 2014.

[4]     C. Eid, P. Codani, Y. Perez, J. Reneses, and R. Hakvoort, “Managing electric flexibility from Distributed Energy Resources: A review of incentives for market design,” Renewable and Sustainable Energy Reviews, vol. 64, pp. 237–247, Oct. 2016.

[5]     N. Höning and H. L. Poutré, “An Electricity Market with Fast Bidding, Planning and Balancing in Smart Grids,” Multiagent Grid Syst., vol. 10, no. 3, pp. 137–163, May 2014.

[6]     M. H. Syed, P. Crolla, G. M. Burt, and J. K. Kok, “Ancillary service provision by demand side management: A real-time power hardware-in-the-loop co-simulation demonstration,” in 2015 International Symposium on Smart Electric Distribution Systems and Technologies (EDST), 2015, pp. 492–498.

[7]     A. van der Veen, “Connecting PowerMatcher to the electricity markets: an analysis of a Smart Grid application,” TNO, 2015.



[i] More information:  “Electric Vehicles and Microgrids: They Need Each Other” by Zofia Lukzo, “The Role of Electrical Storage Systems in Future Grids” by Unnikrishnan Raveendran Nair

[ii] More information:  “THE ROLE OF DEMAND RESPONSE” by Konstantinos Kotsalos.

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