Optimal design of a local renewable electricity supply system for power-intensive production processes with demand response

Abstract

This work studies synergies arising from combining industrial demand response and local renewable electricity supply. To this end, we optimize the design of a local electricity generation and storage system with an integrated demand response scheduling of a continuous power-intensive production process in a multi-stage problem. We optimize both total annualized cost and global warming impact and consider local photovoltaic and wind electricity generation, an electric battery, and electricity trading on day-ahead and intraday market. We find that installing a battery can reduce emissions and enable large trading volumes on the electricity markets, but significantly increases cost. Economically and ecologically-optimal operation of the process and battery are driven primarily by the electricity price and grid emission factor, respectively, rather than locally generated electricity. A parameter study reveals that cost savings from the local system and flexibilizing the process behave almost additively.

Figures (9)

• Figure 1: Structure of the integrated design and scheduling problem: The problem structure allows optimizing the design of the local electricity generation and storage system while considering simultaneous da and id market participation and process dr. The decision tree models the chronological sequence of decisions. Each branch represents the realization of an uncertain parameter and each node represents a decision point.
• Figure 2: Mean and mean daily standard deviation of id electricity price (a) and market deviation (b), i.e., the price difference between the da and the id price.
• Figure 3: Approach to determine scenarios based on historical time series data: The colored dots refer to the multi-dimensional data points that represent (concatenated) time series data.
• Figure 4: Energy system design for id market-only participation: Pareto-optimal solutions are given for 2020 (left), 2021 (center), and 2022 (right). For each year, the tac-optimal, the gwi-optimal, and three intermediate Pareto-optimal solutions are shown, which are equi-distant with respect to gwi. gwi and tac (lower part) are given with vertical gray dashed lines pointing to the respective optimal capacities of the local electricity supply system (upper three parts). Additionally, the tac- and gwi-optimal dr as well as the steady-state operation without a local energy system are given for comparison.
• Figure 5: Process and energy system operation for an exemplary day in 2022 (id-only market participation): An energy system design with maximum admissible PV, wind power, and battery capacities is considered. The operation is shown for the id electricity price and emission factor (a) and the renewable electricity generation (b). The process operation determines the electricity consumption (c). The battery operation determines the state of charge (d).