Elsevier

Applied Energy

Volume 146, 15 May 2015, Pages 344-352
Applied Energy

Potential of demand side integration to maximize use of renewable energy sources in Germany

https://doi.org/10.1016/j.apenergy.2015.02.015Get rights and content

Highlights

  • Former system and market oriented DSI investigations have been summarized.

  • We used an original scenario based approach on a scalable model region.

  • Load blocks were optimally shifted by applying a genetic algorithm.

  • The practical DSI potential in the investigated sectors in Germany is 8 GW.

Abstract

The use of Demand Side Integration (DSI) makes it possible to control electricity consumption and, at the same time, allows for different ancillary system (e.g. voltage and frequency control) or market services (e.g. load shifting) to be provided. In light of today’s power system, which is faced with a high penetration of renewable energy (more than 20%), DSI has become even more important. These new power systems make it especially necessary to shift plenty of demand to times of high feed-in from wind and solar power plants in order to avoid wasting green energy. Additionally providing ancillary services using DSI can help balancing the system. This paper is focused on the analysis of load shifting potential in the residential and commercial sectors. Therefore a scenario based procedure was developed and applied. It uses a genetic algorithm to consider the time-dependent behavior of the different loads, which are modeled as load blocks. The investigation was conducted in the scope of a VDE/ETG working group in close cooperation with industrial partners. The results determined a practical shifting potential for the investigated sectors (residential and commercial) in Germany which could reach 8 GW in 2030.

Section snippets

Introduction to optimization algorithms for DSI

Maintaining the balance between generation and demand in the power system is generally based on the controllability of the energy production of the conventional and hydro power plants. The other balancing option is the control of loads. This method also allows for providing all kinds of system services [1]. The use of flexible loads can be managed by a Demand Side Management (DSM) system. In [2] DSM is defined as the direct influence on the load by increasing or decreasing the energy demand at

Modeling approach for analyzing the DSI potential

As mentioned in Section 1, different methods can be used to determine the DSI potential. For the most part, statistical approaches are used to model electrical equipment or typical load profiles in commercial and residential areas.

To understand the trends, a novel scenario based modeling approach is presented in this investigation. Using information about typical load profiles of domestic and commercial appliances and the individual share and type of different players one is able to globally

Optimization algorithm

The goal of the optimization is the sequential shifting of load blocks – taking into account the load and time factors as well as the concurrency parameters – to find the optimal positions for minimizing the peak load.

There are different mathematical approaches available to solve the described problem. Algorithms such as linear and dynamic programming [31], [32], [33] as well as fuzzy logic [33], [34], can be applied to find the maximal peak load reduction by focusing on optimal unit commitment

Scenarios and simulation results

The scenarios used for the investigation are based on the results of other studies for Germany [29], [30]. They also examine future developments regarding the increasing electrification of domestic appliances (Fig. 7) and transportation (electric vehicles). The trend for households mainly shows a change to electric heating and an increased penetration of air conditioning systems, both of which represent a significant resource for load shifting which is in line with the requirement to minimize

Discussion and conclusion

This work focused on the analysis of DSI potential for households and the commercial sector in the German power system. These areas could be used for the better integration of renewable energy, today and in the future, in order to reach the goal of avoiding the wasting of surplus green energy.

In the first step, a substantial simulation based on a genetic algorithm was presented that estimated the technical potential for load shifting. On average, up to 8 GW can be used to integrate renewable

Acknowledgments

The authors are grateful to the director Wolfgang Glaunsinger and to the members of the ETG Task Force Demand Side Integration. The heated but fruitful discussions during the meetings between 2010 and 2012 have made an important contribution to this paper. A full list of members is published in [2].

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