Abstract
The paper presents an integrated approach to Optimal Power Flow (OPF) in transmission systems with a high share of renewable energy sources (RESs) supported by energy storage systems (ESSs). Unlike conventional approaches, the proposed integrated evaluation framework minimizes operating cost subject to technical (network and ESS) constraints, while separately reporting RES utilization/curtailment and CO2 outcomes as post-solve indicators. The model was implemented as a browser-based JavaScript application using a custom Big-M Simplex linear programming solver and tested on a 24 h horizon under multiple scenarios representing conditions informed by Baltic/Latvian load, generation, and price profiles, applied to a modified IEEE 9-bus test network, including standard operation, high price volatility, high RES penetration, and a transmission line outage (N-1 criterion). The results demonstrate that ESS integration together with RES usage maximization reduces total operating costs by up to 10.2% compared to the baseline strategy without ESS and optimization (about 4.7 percentage points of this saving come from the lower minimum output of the conventional unit alone), increases RES share by about 5 percentage points, and decreases RES curtailment to 0%, under a terminal state of charge condition that prevents the ESS from ending the horizon more depleted than it started (imposed in HiGHS runs of the same linear program). Under high RES scenarios, ESSs become essential for balancing variability, while in volatile markets they support stable dispatching within the model. A sensitivity analysis highlights the dominant influence of market price fluctuations, with smaller effects of ESS capacity and RES share on total operating cost. The findings indicate that, within the transportation-type network model used, the proposed approach improves economic efficiency and environmental performance, offering a practical decision-support tool for transmission system operators and energy planners.