Home energy management system with multiple assets and multiple value pockets, a utopia?

Details

Supervisors

De Jaeger, Emmanuel

Faculty

Ecole polytechnique de Louvain

Degree label

Master [120] : ingénieur civil électromécanicien, à finalité spécialisée: énergie

Abstract

Historically, large power plants dominated electricity production. These plants, while easy to control for grid balance, emitted significant amounts of carbon emissions. Today, the development of renewable energy sources is increasing, bringing control challenges due to their intermittent nature and decentralized setup. The rise of domestic photovoltaic panels has introduced a bidirectional electricity flow for some consumers, creating prosumers who both produce and consume electricity. Previously, electricity consumption involved limited appliances with minimal flexibility. Today, the electrification of assets, particularly in transportation with electric vehicles, has increased. Moreover, prosumers who both produce and consume electricity can now decide to use their own production when it is necessary to charge an asset. Residential demand side flexibility is now more viable due to the increased number of assets and bidirectional electricity flow. Due to these changes in production and consumption, new pricing programs have been developed to meet today's needs of prosumers who both produce and consume electricity. For consumers, and especially prosumers who both produce and consume electricity, it becomes difficult to manage the recharging of all these electrical assets under various pricing programs. This is why the development of home energy management systems, which are tools that manage all these constraints simultaneously, has become crucial. This study aims to evaluate multiple assets and flexibility mechanisms together, comparing the results with simpler ones. The assets and types of pricing were chosen to correspond to the case of a consumer from Flanders in Belgium. The residential system is composed of a house with photovoltaic panels and an electric vehicle under capacity pricing. Simulations are based on the control of the battery charge of the electric vehicle. Three simple controllers, each based on a control technique of its own, are used. The Self-Consumption controller maximizes the use of local photovoltaic electricity, the Peak-Shaving controller smooths the power consumption, and the Load-Shifting controller moves the recharge to nighttime. A controller called Multi-Pocket is designed for this study. It integrates the control logic of the three simple controllers with additional specifications in order to adapt to the constraints of the capacity pricing of the Flemish household. This household is simulated with each of the four controllers by integrating all the system variable parameters into the simulation. Those parameters vary the type of household consumption, the driving profile of the electric vehicle, the technical parameters of the electric vehicle, and the photovoltaic installation specifications. We compare the results of the controllers with profit generated and the self-consumption factor as key performance indicators. Controllers were grouped into two categories that follow similar trends. The Peak-Shaving and Load-Shifting controllers are adapted for workers with high mileage who commute every day of the week by car. They are particularly suitable for individuals with low household consumption, where an oversized photovoltaic installation is desirable but not necessary. An electric vehicle with standard parameters is sufficient. In contrast, the Self-Consumption and Multi-Pocket controllers are suitable for flexible hybrid workers who park their cars at home several days a week. High domestic consumption is not a disadvantage and is even more advantageous during the summer. An oversized photovoltaic installation and an electric vehicle with robust technical parameters are important. Self-Consumption and Multi-Pocket controllers are much more profitable than Peak-Shaving and Load-Shifting. From this result, it is concluded that a strategy focused on maximizing the consumption of free electricity from photovoltaic production yields significant profit. Conversely, a strategy based on minimizing power peaks to comply with capacity pricing is less successful.