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.

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Hydrogen is deemed necessary for the realization of a sustainable society, especially when renewable energy is used to generate hydrogen. As most of the photon-driven hydrogen production methods are not commercially available yet, this study has investigated the techno-economic and overall performance of four different solar-to-hydrogen methods and photovoltaics-based electrolysis methods in the Netherlands. It was found that the photovoltaics-based electrolysis is the cheapest option with production cost of 9.31 $/kgH2. Production cost based on photo-catalytic water splitting, direct bio-photolysis, and photoelectrochemical water splitting are found to be 18.32 $/kgH2, 18.45 $/kgH2, and 18.98 $/kgH2, respectively. These costs are expected to drop significantly in the future. Direct bio-photolysis (potential cost of 3.10 $/kgH2) and photo-catalytic water splitting (3.12 $/kgH2) may become cheaper than photovoltaics-based electrolysis. Based on preferences of three fictional technology investors, i.e. a short-term, a green and a visionary investor, the overall performance of these methods are determined. Photovoltaics-based electrolysis is the most ideal option, with photoelectrochemical water splitting a complementary option. While photovoltaics-based electrolysis has an advantage on the short-term because it is a non-integrated energy system, on the long-term this might lead to relatively higher cost and performance limitations. Photochemical water splitting are integrated energy systems and have an advantage on the long-term because they need a relatively low theoretical overpotential and benefit from increasing temperatures. Both methods show performance improvements by the use of quantum dots. Bio-photolysis can be self-sustaining and can use wastewater to produce hydrogen but sudden temperature changes could lead to performance decrease.@en

The use of the rotor equivalent wind speed for determination of power curves and annual energy production for wind turbines is advocated in the second edition of the IEC 61400-12-1 standard. This requires the measurements of wind speeds at different heights, for which remote sensing equipment is recommended in addition to meteorological masts. In this paper, we present a theoretical analysis that shows that the relevance of the rotor equivalent wind speed method depends on turbine dimensions and wind shear regime. For situations where the ratio of rotor diameter and hub height is smaller than 1.8, the rotor equivalent wind speed method is not needed if the wind shear coefficient at the location of the wind turbine has a constant value between −0.05 and 0.4: in these cases, the rotor equivalent wind speed and the wind speed at hub height are within 1%. For complex terrains with high wind shear deviations are larger. The effect of non-constant wind shear exponent, ie, different wind shear coefficients for lower and upper half of the rotor swept area especially at offshore conditions is limited to also about 1%.

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In this paper, a framework is presented for the evaluation of smart grid environment which is called the three-layer model. This three-layer model comprises three specific categories, or 'layers', namely, the stakeholder, market and technologies layers. Each layer is defined and explored herein, using an extensive literature study regarding their key elements, their descriptions and an overview of the findings from the literature. The assumption behind this study is that a solid understanding of each of the three layers and their interrelations will help in more effective assessment of residential smart grid pilots in order to better design products and services and deploy smart grid technologies in networks. Based on our review, we conclude that, in many studies, social factors associated with smart grid pilots, such as markets, social acceptance, and end-user and stakeholder demands, are most commonly defined as uncertainties and are therefore considered separately from the technical aspects of smart grids. As such, it is recommended that, in future assessments, the stakeholder and market layers should be combined with the technologies layer so as to enhance interaction between these three layers, and to be able to better evaluate residential smart energy systems in a multidisciplinary context.

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Recent developments in distribution grids, environmental policy, and the energy market liberalisation process, have resulted in a quest for flexibility in power systems operation, with the focus increasingly placed on the aggregation of distributed resources. A generic method is proposed for the identification of opportunities, barriers and potential solutions in developing flexibility mechanisms through aggregator companies by concentrating on the market integration aspects. The method is applied to the Netherlands as a case study, and the outcome is a state-of-the-art review of the electricity market development concerning all relevant issues for advancing the market integration of aggregator companies within the Dutch system and in line with the new European grid codes. Opportunities were framed among six categories which outline the potential for the provision of market-based products and services in the Dutch system, whereas barriers were decomposed into market, regulatory, technical and social issues. A set of recommended actions is provided to facilitate the market integration of aggregator companies in the Netherlands, which point out the need for policy interventions and follow-up research activities.@en

According to the European Union Third Energy Market package, the roll-out of smart meters in the residential sector can presumably play a key role in reaching the goals of sustainability strategies. However, the deployment of smart meters alone does not necessarily drive residential customers to use energy in a more sustainable manner. Therefore, more attention should be paid to customers energy behavior in order to reach the objectives of the roll-out policy. In this study, we propose an interdisciplinary framework that establishes a behavioral model to identify the main energy-related behavior change requirements necessary to engage residential customers in energy applications. To fulfill the requirements, we first present the technical system architecture that enables energy applications for residential customers. Then, we assess how gamification, which is the employment of game design elements in non-game contexts, can be used to enhance energy applications by driving customer engagement and energy-related behavior change. To do that, the most relevant game design elements are discussed and classified. After that, the expected value streams from using a gamification-based solution for different stakeholders in the energy market are identified. Finally, the study discusses the potential of the proposed framework in different energy applications for residential customers.@en

This paper is an attempt to determine the potential for solar water heating (SWH) in South Africa and the prospects for its implementation between 2010 and 2030. It outlines the energy market conditions, the energy requirements related to residential and commercial water heating in the country and the solar water heating market dynamics and challenges. It was estimated that 98% of the potential is in the residential sector and the rest in the commercial sector. The total thermal demand for 20 years for water heating was estimated to 2.2 EJ. A 'Moderate SWH implementation' will provide 0.83 EJ of clean energy until 2030 and estimated cost savings of 231 billion rand. For an 'Accelerated SWH implementation' these figures are 1.3 EJ and 369 billion rand. The estimated accumulated reduction of CO ₂ emissions due to SWH can be as high as 297 Mt. The increased affordability of residential hot water due to SWH is an important social factor and solar water heating has a strong social effect.

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