Heuristic optimization of clusters of heat pumps: A simulation and case study of residential frequency reserve

The technological challenges of adapting energy systems to the addition of more renewables are intricately interrelated with the ways in which markets incentivize their development and deployment. Households with own onsite distributed generation augmented by electrical and thermal storage capacities (prosumers), can adjust energy use based on the current needs of the electricity grid. Heat pumps, as an established technology for enhancing energy efficiency, are increasingly seen as having potential for shifting electricity use and contributing to Demand Response (DR). Using a model developed and validated with monitoring data of a household in a plus-energy neighborhood in southern Germany, the technical and financial viability of utilizing household heat pumps to provide power in the market for Frequency Restoration Reserve (FRR) are studied. The research aims to evaluate the flexible electrical load offered by a cluster of buildings whose heat pumps are activated depending on selected rule-based participation strategies. Given the prevailing prices for FRR in Germany, the modelled cluster was unable to reduce overall electricity costs and thus was unable to show that DR participation as a cluster with the heat pumps is financially viable. Five strategies that differed in the respective contractual requirements that would need to be agreed upon between the cluster manager and the aggregator were studied. The relatively high degree of flexibility necessary for the heat pumps to participate in FRR activations could be provided to varying extents in all strategies, but the minimum running time of the heat pumps turned out to be the primary limiting physical (and financial) factor. The frequency, price and duration of the activation calls from the FRR are also vital to compensate the increase of the heat pumps’ energy use. With respect to thermal comfort and self-sufficiency constraints, the buildings were only able to accept up to 34% of the activation calls while remaining within set comfort parameters. This, however, also depends on the characteristics of the buildings. Finally, a sensitivity analysis showed that if the FRR market changed and the energy prices were more advantageous, the proposed approaches could become financially viable. This work suggests the need for further study of the role of heat pumps in flexibility markets and research questions concerning the aggregation of local clusters of such flexible technologies.Comisión Europea 69596

Reducing Energy Consumption and Carbon Footprint by Smart and Sustainable Use

The workshop “Reducing energy consumption and carbon footprint by smart and sustainable use” was organized on 29 June 2017 in the context of the International conference Sustainable Places 2017 with the aim to discuss the latest progress and innovations resulting from 7 projects developing solutions to reduce energy consumption and carbon footprint by smart and sustainable use

A set of comprehensive indicators to assess energy flexibility: a case study for residential buildings

The increasing share of renewable energy sources in the power industry poses challenges for grid management due to the stochastic nature of their production. Besides the traditional supplyside regulation, grid flexibility can also be provided by the demand side. Demand-Response is an attractive approach based on adapting user demand profiles to match grid supply constraints. Nevertheless, defining the flexibility potential related to buildings is not straightforward and continues to pose challenges. Commonly accepted and standardized indicators for quantifying flexibility are still missing. The present paper proposes a new quantification methodology to assess the energy flexibility of a residential building. A set of comprehensive indicators capturing three key elements of building energy flexibility for demand response, notably, capacity, change in power consumption and cost of the demand response action have been identified. The proposed methodology is applied to a residential building, whose heating system is controlled by means of a model predictive control algorithm. The building model is developed on the basis of the experimental data collected in the framework of a European Commission supported H2020 research project Sim4Blocks, which deals with the implementation of demand response in building clusters. The optimal control problem has been investigated by means of mixed-integer linear programming approach. Real time prices are considered as external signals from the grid driving the DR actions. Results show that the proposed indicators, presented in the form of daily performance maps, allow to effectively assess the energy flexibility potential through its main dimensions and can be easily used either by an end-user or a grid-operator perspective to identify day by day the best DR action to be implemented

Reducing Energy Consumption and Carbon Footprint by Smart and Sustainable Use

The workshop “Reducing energy consumption and carbon footprint by smart and sustainable use” was organized on 29 June 2017 in the context of the International conference Sustainable Places 2017 with the aim to discuss the latest progress and innovations resulting from 7 projects developing solutions to reduce energy consumption and carbon footprint by smart and sustainable use

Using agent-based models to generate transformation knowledge for the German energiewende-potentials and challenges derived from four case studies

The German Energiewende is a deliberate transformation of an established industrial economy towards a nearly CO2-free energy system accompanied by a phase out of nuclear energy. Its governance requires knowledge on how to steer the transition from the existing status quo to the target situation (transformation knowledge). The energy system is, however, a complex socio-technical system whose dynamics are influenced by behavioural and institutional aspects, which are badly represented by the dominant techno-economic scenario studies. In this paper, we therefore investigate and identify characteristics of model studies that make agent-based modelling supportive for the generation of transformation knowledge for the Energiewende. This is done by reflecting on the experiences gained from four different applications of agent-based models. In particular, we analyse whether the studies have improved our understanding of policies’ impacts on the energy system, whether the knowledge derived is useful for practitioners, how valid understanding derived by the studies is, and whether the insights can be used beyond the initial case-studies. We conclude that agent-based modelling has a high potential to generate transformation knowledge, but that the design of projects in which the models are developed and used is of major importance to reap this potential. Well-informed and goal-oriented stakeholder involvement and a strong collaboration between data collection and model development are crucial.Energy & Industr