Demand-Orientated Power Production from Biogas: Modeling and Simulations under Swedish Conditions

The total share of intermittent renewable electricity is increasing, intensifying the need for power balancing in future electricity systems. Demand-orientated combined heat and power (CHP) production from biogas has potential for this purpose. An agricultural biogas plant, using cattle manure and sugar beet for biogas and CHP production, was analyzed here. The model Dynamic Biogas plant Model (DyBiM) was developed and connected to the Anaerobic Digestion Model No. 1 (ADM1). Flexible scenarios were simulated and compared against a reference scenario with continuous production, to evaluate the technical requirements and economic implications of demand-orientated production. The study was set in Swedish conditions regarding electricity and heat price, and the flexibility approaches assessed were increased CHP and gas storage capacity and feeding management. The results showed that larger gas storage capacity was needed for demand-orientated CHP production but that feeding management reduced the storage requirement because of fast biogas production response to feeding. Income from electricity increased by 10%, applying simple electricity production strategies to a doubled CHP capacity. However, as a result of the currently low Swedish diurnal electricity price variation and lack of subsidies for demand-orientated electricity production, the increase in income was too low to cover the investment costs. Nevertheless, DyBiM proved to be a useful modeling tool for assessing the economic outcome of different flexibility scenarios for demand-orientated CHP production

Neues Planungswerkzeug für Verteilnetzbetreiber

In den Verteilnetzen ist die Energiewende in vollem Gange. Mit der „Nemo Tool Suite“ hat das Fraunhofer-Institut für Solare Energiesysteme (ISE) zusammen mit dänischen und niederländischen Partnern einen Software-Werkzeugkasten für Verteilnetzbetreiber erarbeitet. Damit können Netzpläne unter Berücksichtigung moderner Smart-Grid-Lösungen so adaptiert werden, dass sie auch bei höherem Anteil fluktuierender Energien und neuer Stromverbraucher wie elektrischen Wärmepumpen und Elektromobilität sicher funktionieren

Model for electric load profiles with high time resolution for German households

Approximately 27% of the European energy consumption is caused by the domestic sector, where 19% ofthe end use energy demand is caused by electric devices. To investigate the factors at play, a stochasticbottom-up model for the generation of electric load profiles is introduced in this paper. The model isdesigned for investigating the effects of occupant behaviour, appliance stock and efficiency on the electricload profile of an individual household. For each activity of a person in the household, an electric applianceis used, and its electricity consumption is linked to measured electric load traces with a time resolutionof 10 s. Probability distributions are incorporated for when and how often an appliance is operated.Duration of operation is given as probability density conditional on the start time. Shared use of anappliance by multiple persons is included in the model. Seasonal effects are considered by using changingprobability sets during the course of the year. For validation, seven subgroups, which reflect typicalhousehold configurations, were formed and tested against measured field data from 430 households in9 different cities across Germany. The results showed an accuracy of 91% and a correlation of up to 0.98

Uncertainty and error analysis of calculation procedures for PV self-consumption and its significance to investment decisions

Self-consumption of PV electricity has become a very important aspect for both, investment decisions as well as for calculating excessive or shortage energy supply. The objective of this paper is to identify uncertainties in the modeling process for calculating such PV self-consumption and quantify their impact. Results show: First, applying a realistic electric load profile was the most important factor for a correct calculation of the self-consumption rate. Second, altering PV simulation methods and parameters had only moderate influence on the rate compared to the alterations in consumption. Third, the timely resolution of data and hence, the simulation also had a significant effect on the outcome

Evaluation of methods for estimating distribution grid stress due to future installations of photovoltaic units

The rising number of photovoltaic (PV) units in distribution grids will necessitate significant investments in grid reinforcement. In research and practice, various methods are employed to estimate grid stress due to future installations of PV units. In this paper, the most common methods are presented and their accuracy is evaluated in a comparative case study. We find that methods assuming homogeneous plant sizes significantly underestimate grid stress. A probabilistic approach that assumes heterogeneous PV plant sizes provides considerably more accurate estimates

Modeling a vendor independent IEC 61850 profile for energy management of micro-CHP units

As distributed energy resources are growing in number it becomes increasingly important to efficiently integrate them in a communication network to monitor and control them. Many envision IEC 61850 to be the best communication solution in this field. But the standard is still far from a plug and play setup. One step in this direction is the modeling of vendor independent IEC 61850 profiles for different kinds of DER. This paper analyzes the modeling of such a profile for intelligent energy management of micro-CHP systems. It discusses common system structures, control hierarchies, and control use cases. Finally it proposes a profile that could be implemented by all micro-CHP vendors to allow easy integration of their devices in an energy management system

Vickrey-Clarke-Grove based multi agent energy management system: Paper presented at 14th International Conference on Autonomous Agents and Multiagent Systems, AA-MAS 2015, May 4-8, 2015, Istanbul, Turkey

Energy management systems (EMS) are being developed to approach challenges emerging with the expansion of renewable energies, electric vehicles, and thermal-electric heating systems. The majority of the developed EMS show a central-hierarchical control structure (e.g. for Virtual Power Plants and grid control centers). In applied research little emphasis has been placed on agent-based EMS and most actors in the energy sector still have reservations towards the application of multi agent systems. Thus, proof of concept studies by means of concrete examples are necessary to show functionality and advantages. By focusing on grid operation and local load flow management in electrical distribution grids, we developed an agent-based EMS applying the Vickrey-Clarke-Groves mechanism. Comparing it against a central-hierarchical system, we show that the agent-based system's mean absolute residual load deviates from the result of the central-hierarchical system by 4.2kW at most, which is 5% of the maximum absolute residual load and 20% of the mean absolute residual load. However, the VCG-Algorithm is the only known approach which ensures both truthfulness in dominant strategies and efficiency, but it lacks when applied in a double-sided trading situation where local electrical demand and local distributed supply need to be matched. With this paper we want to initiate a discourse of how agent-based systems need to be designed for future Smart Grid applications and how they yield benefits comparable to conventional central control architecture