Flexibility from local resources: Congestion management in distribution grids and carbon emission reductions

Abstract: Flexibility from local energy systems has been discussed as a facilitator for the transition towards a more carbon-neutral energy system. Two use cases of this flexibility are congestion management in electricity distribution networks, and an individual-driven reduction of carbon footprints. However, for taping into this flexibility, effective incentive mechanisms and operation planning are essential. This licentiate thesis aims to provide new insights into two areas: 1) the design of market-based incentive mechanisms for congestion management in distribution grids, and 2) the operation planning of local flexible asset owners for reducing their carbon emission footprints. The first area focuses on challenges, design, and evaluation of local flexibility markets (LFMs) for congestion management in distribution grids. The utilized methods include literature review, field studies, scenario planning methods, and demonstration and simulation experiments. Results for identifying the challenges show that the most impactful and uncertain factors are the willingness and ability of end-users to participate in LFMs, and regulatory incentives for distribution system operators (DSOs). Moreover, five challenges are identified for LFM design including low market liquidity, reliability concerns, baselines, forecast errors at low aggregation levels, and the high cost of sub-meter measurements. An LFM design is proposed to address the challenges. The design is a triple horizon market structure including reservation, activation, and adjustment horizons which can support decision making of market participants and improve market liquidity and reliability. Adapted capacity-limitation products are proposed that are calculated based on net-load and subscribed connection capacity of end-users. The products can reduce conflict of interests, and administrative and sub-meter measurement costs related to delivery validation and baselines. Moreover, probabilistic approaches for calculating the cost and value of the products are proposed that can reduce the potential cost of forecast errors for market participants while providing insights on how the utility and cost of the products can be calculated. Evaluating the proposed design is an ongoing work utilizing simulations and real-life demonstrations. The most suitable congestion management solution can vary depending on the context and test-system. Therefore, the evaluation should include comparing the design with other congestion management solutions such as power tariffs. A comparison toolbox is proposed to be used by researchers and DSOs including a qualitative comparison framework and a reusable modeling platform for the quantitative comparison. Four cases are quantitatively compared using the toolbox on a sub-area of Chalmers campus testbed: i) LFM+PT+ET (i.e., considering the LFM, power tariff (PT), and energy cost (ET) simultaneously), ii) LFM+ET, iii) PT+ET, and iv) ET. The most recent results show that case (i), has the lowest number of congested hours. Moreover, congestions due to rebound effects from activating the LFM are observed. The comparison of cases (i) and (ii) suggests that enforcing power tariffs besides the LFM can reduce the rebound effects. The second area utilizes a multi-objective optimization model for identifying CO2 emission abatement strategies and their cost for Chalmers testbed local multi-energy system. The results of the case study show that the carbon emission footprint of the local system can be reduced by 20.8% with a 2.2% increase in the cost. The operation strategies for this purpose include more usage of biomass boilers in heat production, substitution of district heating and absorption chillers with heat pumps, and higher utilization of storage. The cost of the strategies ranged from 36.6-100.2 €/tCO2. This thesis can benefit system operators, flexibility asset owners, policy makers, and researchers dealing with local flexibility resources by offering insights into the challenges and proposing solutions and toolboxes for implementation and evaluation.