An operational bidding framework for aggregated electric vehicles on the electricity spot market

Fluctuating electricity prices offer potential economic savings for the consumption of electricity by flexible assets such as Electric Vehicles (EVs). This study proposes an operational bidding framework that minimizes the charging costs of an EV fleet by submitting an optimized bid to the day-ahead electricity market. The framework consists of a bidding module that determines the most cost-effective bid by considering an electricity price and an EV charging demand forecast module. In this study we develop and evaluate several regression and machine learning models that forecast the electricity price and EV charging demand. Furthermore, we examine the composition of a most optimal operational bidding framework by comparing the outcome of the bidding module when fed with each of the forecast models. This is determined by considering the day-ahead electricity price and imbalance costs due to forecast errors. The study demonstrates that the best performing self-contained forecast models with the objective of electricity price and EV charging demand forecasting, do not deliver the best overall results when included in the bidding framework. Additionally, the results show that the best performing framework obtains a 26% cost savings compared to a reference case where EVs are charged inflexibly. This corresponds to an achieved savings potential of 92%. Consequently, along with the developed bidding framework, these results provide a fundamental basis for effective electricity trading on the day-ahead market

Solar Irradiance Ramp Forecasting Based on All-Sky Imagers

Solar forecasting constitutes a critical tool for operating, producing and storing generated power from solar farms. In the framework of the International Energy Agency’s Photovoltaic Power Systems Program Task 16, the solar irradiance nowcast algorithms, based on five all-sky imagers (ASIs), are used to investigate the feasibility of ASIs to foresee ramp events. ASIs 1–2 and ASIs 3–5 can capture the true ramp events by 26.0–51.0% and 49.0–92.0% of the cases, respectively. ASIs 1–2 provided the lowest

Nieuwe technieken voor glas in lood renovatie met zonnecellen

In dit artikel licht ik toe hoe ramen ingezet kunnen worden om elektriciteit op te wekken, op basis van experimenten met een zogenaamde Electric Mondrian, een soort ‘glas in lood’ lookalike. Toepassen van kleurstoffen in de vorm van coatings op glas maakt het mogelijk elektriciteit op te wekken met zonnecellen in de sponningen van het kozijn. Dit zou een mogelijkheid kunnen zijn bij renovatie van glas in lood ramen die tevens elektriciteit kunnen opwekken

On the Effect of Dynamic Albedo on Performance Modelling of Offshore Floating Photovoltaic Systems

In this paper, the effect of dynamic albedo on modelling energy generation of a floating offshore photovoltaic system is quantified, for a system assumed to be installed at the North Sea. The dynamic albedo is modeled as a function of solar irradiation, wind speed and solar zenith angle at an hourly time resolution. The energy output of a floating offshore PV system is compared considering two scenarios (i) implementing constant albedo and (ii) implementing a modeled dynamically varying albedo. The quantified results show that the system performance in case of a varying albedo is larger by about 1.03% compared to using a constant albedo

Simulation of performance differences between offshore and land-based photovoltaic systems

Abstract The purpose of this study is to model, simulate, and compare the performance of a photovoltaics system on land and at sea. To be able to have a fair comparison the effect of sea waves, wind speed and relative humidity are considered in this model. The sea waves are modeled in the frequency domain, using a wave spectrum. The irradiation on a tilted surface for a floating system is calculated considering the tilt angle that is affected by the sea waves. Moreover, the temperature is estimated based on heat transfer theory and the natural cooling system for both floating and land-based photovoltaic systems. Actual measured weather data from two different locations, one located at Utrecht University campus and the other one on the North Sea, are used to simulate the systems, thus making the comparison possible. Energy yield is calculated for these weather conditions. The results show that the relative annual average output energy is about 12.96% higher at sea compared with land. However, in some months, this relative output energy increases up to 18% higher energy yield at sea

A density‐based time‐series data analysis methodology for shadow detection in rooftop photovoltaic systems

The majority of photovoltaic (PV) systems in the Netherlands are small scale, installed on rooftops, where the lack of onsite global tilted irradiance (GTI) measurements and the frequent presence of shadow due to objects in the close vicinity oppose challenge in their monitoring process. In this study, a new algorithmic tool is introduced that creates a reference data-set through the combination of data-sets of the unshaded PV systems in the surrounding area. It subsequently compares the created reference data-set with the one of the PV system of interest, detects any energy loss and clusters the distinctive loss due to shadow, created by the surrounding objects. The new algorithm is applied successfully to a number of different cases of shaded PV systems. Finally, suggestions on the unsupervised use of the algorithm by any monitoring platform are discussed, along with its limitations algorithm and suggestions for further research