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Photovoltaics Energy Prediction Under Complex Conditions for a Predictive Energy Management System
(2015)
Encapsulant-free N.I.C.E. modules have strong ecological advantages compared to conventional laminated modules but suffer generally from lower electrical performance. Via long-term outdoor monitoring of fullsize industrial modules of both types with identical solar cells, we investigated if the performance difference remains constant over time and which parameters influence its value. After assessing about a full year’s data, two obvious levers for N.I.C.E. optimization are identified: The usage of textured glass and transparent adhesives on the module rear side. Also, the performance loss could be alleviated using tracking systems due to lower AOI values. Our measurements show additionally that N.I.C.E. module surfaces are in average about 2.5°C cooler compared to laminated modules. With these findings, we lay out a roadmap to reduce today’s LIV gap of about 5%rel by different optimizations.
In this paper, a new method is demonstrated for online remote simulation of photovoltaic systems. The required communication technology for the data exchange is introduced and the methods of PV generator parameter extraction for the simulation models are analysed. The method shown for parameter extraction from the manufacturer data is especially useful for the commissioning procedure, where the measured installed power is transferred to standard test conditions using the simulation model and can then be easily compared with the design power. At a simulation accuracy of 2% using the software environment INSEL ® any problems with the PV generator can reliably be detected. Online simulation of a grid connected PV generator is then carried out during the operation of the photovoltaic plant. The visualisation includes both the monitored and the simulated online data sets, so that a very efficient fault detection scheme is available. The method is implemented and validated on several grid connected photovoltaic power plants in Germany. It is excellently suited to provide automatic and real time fault detection and significantly improve the commissioning procedure for photovoltaic plants of all sizes.
The twin concept is increasingly used for optimization tasks in the context of Industry 4.0 and digitization. The twin concept can also help small and medium-sized enterprises (SME) to exploit their energy flexibility potential and to achieve added value by appropriate energy marketing. At the same time, this use of flexibility helps to realize a climate-neutral energy supply with high shares of renewable energies. The digital twin reflects real production, power flows and market influences as a computer model, which makes it possible to simulate and optimize on-site interventions and interactions with the energy market without disturbing the real production processes. This paper describes the development of a generic model library that maps flexibility-relevant components and processes of SME, thus simplifying the creation of a digital twin. The paper also includes the development of an experimental twin consisting of SME hardware components and a PLC-based SCADA system. The experimental twin provides a laboratory environment in which the digital twin can be tested, further developed and demonstrated on a laboratory scale. Concrete implementations of such a digital twin and experimental twin are described as examples.
Three real-lab trigeneration microgrids are investigated in non-residential environments (educational, office/administrational, companies/production) with a special focus on domain-specific load characteristics. For accurate load forecasting on such a local level, à priori information on scheduled events have been combined with statistical insight from historical load data (capturing information on not explicitly-known consumer behavior). The load forecasts are then used as data input for (predictive) energy management systems that are implemented in the trigeneration microgrids. In real-world applications, these energy management systems must especially be able to carry out a number of safety and maintenance operations on components such as the battery (e.g. gassing) or CHP unit (e.g. regular test runs). Therefore, energy management systems should combine heuristics with advanced predictive optimization methods. Reducing the effort in IT infrastructure the main and safety relevant management process steps are done on site using a Smart & Local Energy Controller (SLEC) assisted by locally measured signals or operator given information as default and external inputs for any advanced optimization. Heuristic aspects for local fine adjustment of energy flows are presented.
The PHOTOPUR project aims to develop a photocatalytic process as a type of AOPs (Advanced Oxidation Processes) for the elimination of plant protection products (PPP) of the cleaning water used to wash sprayers. At INES a PV based energy supply for the photocatalytic cleaning system was developed within the framework of two bachelor theses and assembled as a demonstration unit. Then the system was step by step extended with further process automation features and pushed to a remote operating device. The final system is now available as a mobile unit mounted on a lab table. The latest step was the photocatalytic reactor module which completed the first PHOTOPUR prototype. The system is actually undergoing an intensive testing phase with performance checks at the consortium partners. First results give an overview about the successful operation.
Sustainable Aspects force a building manager to continuous observation of actual states and developments concerning building use, energy and media flows.In the presented approach a communication structure was built up to use different software applications and tools in order to optimize the operation of the building.
Meeting the requirements of smart grids local, decentralized subnets will offer additional potentials to stabilize and compensate the utility grid mainly on the low voltage level. In a quite complex configuration these decentralized energy systems are combined power, heat and cooling power distributions. According to the regional and local availability of renewable energy sources advanced energy management concepts should consider climatic conditions as well as the state of the interacting utility grid and consumption profiles. The approach uses demonstrational setups to develop a forecast based energy management for trigeneration subnets by taking into account the running conditions of local electrical and thermal energy conversion units. This should lead to the best coverage of the demand and supporting/stabilizing the utility grid at the same time. For the first of three demonstrational projects the priorities of the subnet are given with the maximization of the CHP operation to substitute a major part of the heating and cooling power delivered by electric heaters or compression chillers.