An Uncertainty Management Framework for Integrated Gas-Electric Energy Systems

Abstract

In many parts of the world, electric power systems have seen a significant shift towards generation from renewable energy and natural gas. Because of their ability to flexibly adjust power generation in real time, gas-fired power plants are frequently seen as the perfect partner for variable renewable generation. However, this reliance on gas generation increases interdependence and propagates uncertainty between power grids and gas pipelines, and brings coordination and uncertainty management challenges. To address these issues, we propose an uncertainty management framework for uncertain, but bounded gas consumption by gas-fired power plants. The admissible ranges are computed based on a joint optimization problem for the combined gas and electricity networks, which involves chance-constrained scheduling for the electric grid and a novel robust optimization formulation for the natural gas network. This formulation ensures feasibility of the integrated system with a high probability, while providing a tractable numerical formulation. A key advance with respect to existing methods is that our method is based on a physically accurate, validated model for transient gas pipeline flows. Our case study benchmarks our proposed formulation against methods that ignore how reserve activation impacts the fuel use of gas power plants, and only consider predetermined gas consumption. The results demonstrate the importance of considering uncertainty to avoid operating constraint violations and curtailment of gas to the generators.

Stochastic Hybrid Approximation for Uncertainty Management in Gas-Electric Systems

“…The second stage gas flow problem is similar to the models in [8], [4], and identifies gas supply and compressor setpoints to satisfy the demand and network constraints while minimizing the expected cost. The demand includes consumption of normal loads and GFPPs, which in turn depends on the wind scenario ω.…”

“…As a basis for our case study, we use the gas and electricity network that has previously been analysed in [8], [4] and is available at [42]. The cost of electrical load shedding is 1000 USD/MWh, gas load shedding is set to 5 USD/kg and the compression cost is set 1 USD.…”

“…However, accounting for the interdependence through simplified or sequential models may overly restrict operation [3]. Furthermore, not accounting for the impact of uncertainty in both electric and natural gas systems can cause safety violations or disruption in gas supply to generators [4]. To address these issues, this paper develops a method for scheduling interconnected gas electric systems under uncertainty.…”

“…In [25], an SAA problem featuring the non-convex natural gas problem (without the electric system) is successfully solved for a small system and sample set, however the scalability of this problem is identified as an issue. In [4], a monotonicity property of dynamic gas networks from [26] was leveraged to formulate a robust gas-electric optimization problem based on two worst-case scenarios. An important challenge to this method is conservativeness, which arises from the limited conditions under which the monotonicity property holds.…”