Abstract
The need to limit climate change has led to policies that aim for the reduction of greenhouse gas emissions. Often, a trade-off exists between reducing emissions and associated costs. In this article, a multi-objective optimization framework is proposed to determine this trade-off when operating a Community Energy Storage (CES) system in a neighbourhood with high shares of photovoltaic (PV) electricity generation capacity. The Pareto frontier of costs and emissions objectives is established when the CES system would operate on the day-ahead spot market. The emission profile is constructed based on the marginal emissions. Results show that costs and emissions can simultaneously be decreased for a range of solutions compared to reference scenarios with no battery or a battery only focused on increasing self-consumption, for very attractive CO2 abatement costs and without hampering self-consumption of PV-generated electricity. Results are robust for battery degradation, whereas battery efficiency is found to be an important determining factor for simultaneously decreasing costs and emissions. The operational schedules are tested against violating transformer, line and voltage limits through a load flow analysis. The proposed framework can be extended to employ a wide range of objectives and/or location-specific circumstances.
Highlights
I N RECENT years, there has been a sharp increase in the deployment of Photovoltaic (PV) systems for generating electricity
Wöhler curves are historically used to predict the material fracture under cycle loading [27]. Using these has become common practice in estimating the number of full-equivalent cycles (FECs) a battery can withhold as a function of depth of cycle (DOC) [11], [28], [29]
In this paper a framework is proposed that enables the multiobjective optimization of cost and emissions by making use of a Community Energy Storage (CES) system
Summary
I N RECENT years, there has been a sharp increase in the deployment of Photovoltaic (PV) systems for generating electricity. Given that the operator of a sufficiently large CES can purchase/sell electricity from/to the grid, e.g., based on forecasted day-ahead spot market prices, this can be done by converting emissions to costs and incorporating these in a cost minimization approach [20]. An alternative is to incorporate time-varying CO2 emission factors as input data, which enables the separate minimization of emissions In this regard, the Pareto frontier can be used to address the trade-off between different objectives [21], for example to decide between different energy devices for satisfying heat and electricity demand [22]. We establish a multi-objective optimization framework based on the Pareto frontier approach to demonstrate the trade-off between economic and environmental objectives for the operation of a CES system, using a spot market electricity price profile and a marginal emission profile as inputs.
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