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The rapid electrification of residential heating and mobility sectors is expected to drive the existing distribution grid assets beyond their planned operating conditions This change will also reveal new potentials through sector coupling, flexibilities, and the local exchange of decentralized generation. This paper thus presents an optimization framework for multi-modal energy systems at the low voltage (LV) distribution grid level. In this, we focus on the reinforcement requirements of the grid and the techno-economic assessment of flexibility components and coordination between agents. By employing a multi-level approach, computational complexity is reduced, and various levels of coordination and flexibilities are implemented. We conclude the work with a case study for a representative rural grid in Germany, in which we observe high economic potential in the flexible operation of buildings, majorly thanks to better integration of photovoltaics. Across all paradigms barring a best-case benchmark, grid reinforcement based on a mix of passive and active measures was necessary. A synergy effect is observed between flexibilities and coordination, as their combination reduces the peaks to the extent of completely avoiding grid reinforcement. The presented framework can be applied with a wide range of grid and component types to outline the broad landscape of future LV distribution grids. • Optimization framework for holistic planning of multi-modal LV distribution system. • Framework investigates grid reinforcement needs under flexibilities and coordination. • Framework is demonstrated with an exemplary rural distribution grid in Germany. • Synergy effects between flexibilities and coordination to integrate PV excess exist. • Flexibilities and coordination together reduce system costs by %25, and grid costs by 65%. [ABSTRACT FROM AUTHOR]

Abstract: This paper investigates the technical and economic potential of energy-intensive industries to provide demand-side management (DSM) in electricity and balancing markets through 2030. Increasing shares of renewables will lead to a rising demand for ancillary services at the same time that less conventional plants will be available to provide these services. This paper makes projections on the extent to which DSM from industrial processes can provide economic benefits in electricity markets with renewables by providing tertiary reserve capacity. Different industrial processes and their specific technical and economic properties are investigated and compared with other storage devices and electricity generation technologies. Based on an extension of an existing European electricity market model, simulations are used here to make long-term forecasts for market prices, dispatch and investments in the electricity markets through linear optimization. [ABSTRACT FROM AUTHOR]

Abstract: This paper examines the potential effects of Germany’s feed-in tariff policy for small roof-top solar PV systems installed between 2009 and 2030. Employing a partial equilibrium approach, we evaluate the policy by weighing the benefits from induced learning and avoided environmental externalities against the social costs of promoting residential PV. We use a dynamic optimization model that maximizes social welfare by accounting for learning-by-doing, technology diffusion, and yield-dependent demand. We find a wide range of effects on welfare, from net social costs of 2014million€ under a “business as usual” scenario to 7586million€ of net benefits under the positive prospects of PV’s development. Whereas the “business as usual” scenario underestimates actual price reductions, the positive scenario mirrors recent price developments and feed-in tariffs in the German residential PV market. [Copyright &y& Elsevier]

• Linear Program for designing bidirectional low temperature networks. • Holistic sizing approach for all building energy systems in a district. • Performance evaluation with economic, thermodynamic and ecologic indicators. • Comparison with stand-alone HVAC systems. • Bidirectional low temperature network result in substantial energy and cost savings. This paper presents a novel design methodology based on Linear Programming for designing and evaluating distributed energy systems with bidirectional low temperature networks (BLTNs). The mathematical model determines the optimal selection and sizing of all energy conversion units in buildings and energy hubs connected to the BLTN while minimizing total annualized costs. The optimization superstructure of building energy systems comprises heat pumps, compression chillers, heat exchangers for direct cooling, cooling towers and thermal energy storages. The design approach is applied to a real-world use case in Germany and the BLTN performance is compared to a reference case with individual HVAC systems. The BLTN concept shows a cost reduction of 42% and causes 56% less CO 2 emissions compared to individual HVAC systems. [ABSTRACT FROM AUTHOR]