As the amount of variable renewable energy integrated into power systems continues to increase around the world, energy storage systems (ESS) hold the promise of enabling larger amounts of renewable energy to be accommodated and providing additional flexibility in the power system‚s operation. This poster presents an approach based on optimal power flow to improve the performance of a power system with wind generation through the addition of ESS. The placement of the ESS is considered at the site of varying wind generation and/or location of a fluctuating load, and enables an increase in performance of the power system to be achieved over a period of time. Objectives considered for improvements in performance include reduction of a conventional (nonrenewable) generator‚s output power, smoothing of a conventional generator's output power to lessen ramping, and reduction in transmission losses. A single-phase, transmission-level model of a five-bus power system was selected to serve as the test system, which includes a conventional generator, a wind generator with varying power output specified by recorded data, a fluctuating load specified by recorded data, a fixed load, and ESS placed at the varying wind generator and/or fluctuating load. Values from both the varying wind generation and fluctuating load were scaled to be consistent with the five-bus test system and down sampled such that values are given at 30-minute intervals for two days. ESS are sized at 10% of the daily demand for energy, and are modeled by first-order difference equations that relate the rate (average power) of charge/discharge and amount of energy stored at every step. With selected data specified at each time, an optimal load flow problem was formulated and solved (via constrained nonlinear optimization algorithms) over all 96 time steps. The case of load flow with no ESS present served as the baseline to which three scenarios (ESS co-located with wind generation, ESS co-located with fluctuating load, and ESS at both locations) were considered for each of the three objectives such that there were nine results. In all scenarios the performance of the power system is improved as expected with the selected objective. The improvements can be viewed qualitatively in figures of the conventional generator‚s power and line powers, and quantitatively through values calculated for the objective functions (metrics) in all scenarios. As is likely intuitive, the best results are achieved for ESS placed at two locations followed closely by a single installation of ESS at the bus with fluctuating load. The approach and associated results demonstrate examples of improvements that can be achieved in a power system‚s performance through integration of ESS along with renewable energy. An additional impact is that insight into the preferable location and size of ESS can be determined based upon the desired objective.