• Energy Research

To deal with the rising integration of stochastic renewables and energy intensive distributed energy resources (DER) to the electricity network, alternatives to expensive network reinforcements are increasingly needed. An alternative solution often under consideration is integrating flexibility from the consumer side to system management. However, such a solution needs to be contemplated from different angles before it can be implemented in practice. To this end, this article considers a case study of the Amsterdam ArenA stadium and its surrounding network where flexibility is expected to be available to support the network in the future. The article studies the technical aspects of using this flexibility to determine to what extent, despite the different, orthogonal goals, the available flexibility can be used by various stakeholders in scenarios with a large load from electric vehicle charging points. Furthermore, a legal study is performed to determine the feasibility of the technical solutions proposed by analysing current European Union (EU) and Dutch law and focusing on the current agreements existing between the parties involved. The article shows that flexibility in the network provided by Amsterdam ArenA is able to significantly increase the number of charging points the network can accommodate. Nonetheless, while several uses of flexibility are feasible under current law, the use of flexibility provided by electric vehicles specifically faces several legal challenges in current arrangements.

Widespread roll-out of different types of distributed energy resources (DERs) has been introducing capacity challenges in the electrical power distribution networks. Different types of demand response (DR) mechanisms have been developed in order to tackle such problems and defer expensive and unexpected network reinforcement. While the existing centralized mechanisms ensure reliable and secure grid operations, distributed intelligence has also been growing in popularity due to its ability of solving complex problems with minimum exchange of information. This paper discusses a decentralized approach to enable demand response methodologies for managing congestions involving multiple actors more efficiently. The proposed approach is validated with simulations for representative Dutch low-voltage (LV) networks.

With the new Dutch regulation on banning the newly-built petrol vehicles by 2030, urban areas are predicted in the short-term local congestion situation dues to the high penetration level of electric vehicles. These vehicles with fast charging technologies require a high electric demand over some hours to charge their batteries. In order to provide a feasible solution at the utility level to that problem, large-scale battery energy storage systems (BESS) are considered as vital means to provide flexibility and effectively support the local networks. However, the capital cost of the BESS is still a main concern leading to a cost-effective operation schedule is required to ensure the desirable power quality while the lifetime of BESS is extended. This paper investigates the solutions to the power congestion problem and under-voltage issue of a Dutch medium voltage network around the Amsterdam Arena stadium once the penetration of electric vehicles keeps increasing in the years to come. The coordination scheme among BESS is then proposed to ensure the maximum life span of BESS. The numerical results from this work confirm the feasibility and effectiveness of the large-scale BESS in modern distribution networks and suggest the potential benefit that the stadium owner could gain when their BESS system supports the local network.

The built environment has the potential to contribute to maintaining a reliable grid at the demand side by offering flexibility services to a future Smart Grid. In this study, an office building is used to demonstrate forecast-driven building energy flexibility by operating a Battery Electric Storage System (BESS). The objective of this study is, therefore, to stabilize/flatten a building energy demand profile with the operation of a BESS. First, electricity demand forecasting models are developed and assessed for each individual load group of the building based on their characteristics. For each load group, the prediction models show Coefficient of Variation of the Root Mean Square Error (CVRMSE) values below 30%, which indicates that the prediction models are suitable for use in engineering applications. An operational strategy is developed aiming at meeting the flattened electricity load shape objective. Both the simulation and experimental results show that the flattened load shape objective can be met more than 95% of the time for the evaluation period without compromising the thermal comfort of users. Accurate energy demand forecasting is shown to be pivotal for meeting load shape objectives.

Effective Energy Management with an active Demand Response (DR) is crucial for future smart energy system. Increasing number of Distributed Energy Resources (DER), local microgrids and prosumers have an essential and real influence on present power distribution system and generate new challenges in power, energy and demand management. A relatively new paradigm in this field is transactive energy (TE), with its value and market-based economic and technical mechanisms to control energy flows. Due to a distributed structure of present and future power system, the Internet of Things (IoT) environment is needed to fully explore flexibility potential from the end-users and prosumers, to offer a bid to involved actors of the smart energy system. In this paper, new approach to connect the market-driven (bottom-up) DR program with current demand-driven (top-down) energy management system (EMS) is presented. Authors consider multi-agent system (MAS) to realize the approach and introduce a concept and standardize the design of new Energy Flexometer. It is proposed as a fundamental agent in the method. Three different functional blocks have been designed and presented as an IoT platform logical interface according to the LonWorks technology. An evaluation study has been performed as well. Results presented in the paper prove the proposed concept and design.

Along with the development of Smart Energy System (SES), the advancing popularity of hybrid energy appliances, such as micro-combined heat and power (CHP) and electric heaters, requires an overall energy management strategy to optimize the energy using while guaranteeing energy supply for both the electricity and heat demand. This paper based on the concept of Multi-Commodity Smart Energy System (MC-SES) proposes a self-sufficient hybrid energy model to minimize the energy exchange with the external electricity grid. Next to the optimization solution for this hybrid energy management problem, a greedy algorithm has been proposed to alleviate the high computational complexity of optimization searching. The optimization, direct allocation and greedy-based methods will all be analyzed, simulated and compared in this paper.