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The increase in households with grid connected Photovoltaic (PV) battery system poses challenge for the grid due to high PV feed-in as a result of mismatch in energy production and load demand. The purpose of this paper is to show how a Model Predictive Control (MPC) strategy could be applied to an existing grid connected household with PV battery system such that the use of battery is maximized and at the same time peaks in PV energy and load demand are reduced. The benefits of this strategy are to allow increase in PV hosting capacity and load hosting capacity of the grid without the need for external signals from the grid operator. The paper includes the optimal control problem formulation to achieve the peak shaving goals along with the experiment set up and preliminary experiment results. The goals of the experiment were to verify the hardware and software interface to implement the MPC and as well to verify the ability of the MPC to deal with the weather forecast deviation. A prediction correction has also been introduced for a short time horizon of one hour within this MPC strategy to estimate the PV output power behavior.
In rural low voltage grid networks, the use of battery in the households with a grid connected Photovoltaic (PV) system is a popular solution to shave the peak PV feed-in to the grid. For a single electricity price scenario, the existing forecast based control approaches together with a decision based control layer uses weather and load forecast data for the on–off schedule of the battery operation. These approaches do bring cost benefit from the battery usage. In this paper, the focus is to develop a Model Predictive Control (MPC) to maximize the use of the battery and shave the peaks in the PV feed-in and the load demand. The solution of the MPC allows to keep the PV feed-in and the grid consumption profile as low and as smooth as possible. The paper presents the mathematical formulation of the optimal control problem along with the cost benefit analysis . The MPC implementation scheme in the laboratory and experiment results have also been presented. The results show that the MPC is able to track the deviation in the weather forecast and operate the battery by solving the optimal control problem to handle this deviation.
An energy oriented design concept was developed within the research project PHOTOPUR which has the development of a PV powered water cleaning system as main focus. During a wine season Plant Protection Products (PPP) are several times sprayed on plants to protect them of undesired insects and herbs or avoid hazardous fungus
types. A work package of the project partner INES in Offenburg led to a design introducing energy profiling already in the early beginning of a product design. The concept is based on three pillars respecting first the
requirements of the core process making up filtering and cleaning and secondary aspects which run, support, maintain and monitor the system to secure availability and product reliability.
The presented paper shows that the results of the design tools guided the developers to assemble a functional model of the water decontamination unit which was manually tested with its concatenated steps of the water cleaning process.
Das Projektvorhaben "Energienetzmanagement dezentraler KWK‐Anlagen mit diversen Verbraucherstrukturen", das vom Innovationsfonds der badenova AG & Co KG von Mai 2012 bis Juli 2016 unter der Fördernummer 2012‐09 gefördert wurde kann aus Sicht des Projektnehmers Hochschule Offenburg und seiner Partner Stadt Offenburg und G. und M. Zapf Energie GbR mbH als sehr erfolgreich umgesetztes Fördervorhaben bezeichnet werden. Während der ca. vier Jahre Projektlaufzeit konnten mehrere Reallabore geschaffen werden, die an die Eigenschaften eines Subnetzes in einem Smart Grid sehr nah herangeführt wurden. Alle Objekte bzw. Netzstrukturen verfügen über typische Komponenten eines Microgrids mit Energiequellen, Speichern und Senken. Auch wurde die Trigeneration als Netzvariante mit Strom‐ Wärme und Kältebereitstellung aufgegriffen und für Verteilnetzmodelle der Niederspannungsebene beschrieben. Ausgehend von einem Mikronetzmodell für jede Energieart kann hinter jeder Trafostation eine beliebig komplexe Energieversorgungsstruktur aufgespannt werden.
The building sector is one of the main consumers of energy. Therefore, heating and cooling concepts for renewable energy sources become increasingly important. For this purpose, low-temperature systems such as thermo-active building systems (TABS) are particularly suitable. This paper presents results of the use of a novel adaptive and predictive computation method, based on multiple linear regression (AMLR) for the control of TABS in a passive seminar building. Detailed comparisons are shown between the standard TABS and AMLR strategies over a period of nine months each. In addition to the reduction of thermal energy use by approx. 26% and a significant reduction of the TABS pump operation time, this paper focuses on investment savings in a passive seminar building through the use of the AMLR strategy. This includes the reduction of peak power of the chilled beams (auxiliary system) as well as a simplification of the TABS hydronic circuit and the saving of an external temperature sensor. The AMLR proves its practicality by learning from the historical building operation, by dealing with forecasting errors and it is easy to integrate into a building automation system.
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.
In this study, a high-performance controller is proposed for single-phase grid-tied energy storage systems (ESSs). To control power factor and current harmonics and manage time-shifting of energy, the ESS is required to have low steady-state error and fast transient response. It is well known that fast controllers often lack the required steady-state accuracy and trade-off is inevitable. A hybrid control system is therefore presented that combines a simple yet fast proportional derivative controller with a repetitive controller which is a type of learning controller with small steady-state error, suitable for applications with periodic grid current harmonic waveforms. This results in an improved system with distortion-free, high power factor grid current. The proposed controller model is developed and design parameters are presented. The stability analysis for the proposed system is provided and the theoretical analysis is verified through stability, transient and steady-state simulations.
Der sommerliche Wärmeschutz von Schulgebäuden im Oberrheingraben und die Bereitstellung von Kühlenergie wurden bereits untersucht und finden Aufnahme im Leitfaden „Natürliche Gebäudeklimatisierung in Klassenzimmern des südlichen Oberrheins“. Im Rahmen der Arbeiten zur Minderung der sommerlichen Überhitzung wurde durch den Einbau und die damit verbundene kontinuierliche Aufzeichnung der CO2‐Konzentrationen der Raumluft festgestellt, dass besonders im Winterhalbjahr eine Verbesserung der Luftqualität erreicht werden muss.
There is a growing trend for the use of thermo-active building systems (TABS) for the heating and cooling of buildings, because these systems are known to be very economical and efficient. However, their control is complicated due to the large thermal inertia, and their parameterization is time-consuming. With conventional TABS-control strategies, the required thermal comfort in buildings can often not be maintained, particularly if the internal heat sources are suddenly changed. This paper shows measurement results and evaluations of the operation of a novel adaptive and predictive calculation method, based on a multiple linear regression (AMLR) for the control of TABS. The measurement results are compared with the standard TABS strategy. The results show that the electrical pump energy could be reduced by more than 86%. Including the weather adjustment, it could be demonstrated that thermal energy savings of over 41% could be reached. In addition, the thermal comfort could be improved due to the possibility to specify mean room set-point temperatures. With the AMLR, comfort category I of the comfort norms ISO 7730 and DIN EN 15251 are observed in about 95% of occasions. With the standard TABS strategy, only about 24% are within category I.
Adaptive predictive control of thermo-active building systems (TABS) based on a multiple regression algorithm: First practical test. Available from: https://www.researchgate.net/publication/305903009_Adaptive_predictive_control_of_thermo-active_building_systems_TABS_based_on_a_multiple_regression_algorithm_First_practical_test [accessed Jul 7, 2017].
The uncertain and time-variant nature of renewable energy results in the need to deal with peaks in the production of energy. One approach is to achieve a load shift and thereby help balancing the grid by using thermally Activated Building Systems (TABS). Control systems currently in place do not exploit the full potential of TABS. This paper reviews how Model Predictive Control can possibly reduce the fluctuations of the demand and supply of (renewable) energy as it enables the TABS to react to the dynamics of weather and its impact on the grid at any time.
Energietechnik
(2015)
Kurz und prägant werden die Energieumwandlungsprozesse dargestellt. Die Schwerpunkte reichen von der kompletten Beschreibung der nachhaltigen, erneuerbaren Energietechniken, über Gas- und Dampfturbinen-Kraftwerke sowie Kraft-Wärme-Kälte-Kopplungsanlagen bis hin zur Energieverteilung und zum Kyoto-Protokoll. Zu allen Kapiteln gibt es Aufgaben mit vollständigen Lösungen im Anhang. In der aktuellen Auflage wurden in den Kapiteln 3 und 15 die Zahlenwerte aktualisiert. Kapitel 9 wurde entsprechend der neuen Anbieterstruktur überarbeitet und Kapitel 10 um die Adsorptionstechniken ergänzt. Die Kapitel 17-20 wurden vollständig überarbeitet und stellen den aktuellen Stand der globalen politischen Aspekte dar.