Proposal information to include, objective, methods, results, and conclusion: Cost improvements in the energy storage technologies have caused PV plus Storage (PVS) to be the dominant choice of design for new renewable energy power plants. In California alone, there are over 27GW of PVS assets with CAISO interconnection agreements. The increase in PVS assets has created a need for more advanced asset performance-management metrics as the assumptions and methodologies for performance monitoring for PV-only system do not readily apply to PVS systems.
Our PVS analytics developments focus on solving two major challenges: 1. Performance indicators based on photovoltaics related parameters such as irradiance and backplane temperature, fall short on assessing PVS systems since they do not capture the metrics involved in storing and releasing energy from a storage system. 2. Battery Energy Storage Systems (BESS) are complex in nature with multiple devices that makes it susceptible to data volatility. For example, a state of energy reading could occasionally get stuck for several minutes and then return to normal. This data volatility makes it difficult to compute stable metrics.
The renewable energy industry has not yet developed extensive experience on performance management of PVS systems. Combining various data points to produce accurate and consistent results is a complex challenge, so developing the necessary metrics demands careful study of data and robust experimentation on large, real-world data sets.
Our holistic PVS performance management methodology evaluates the performance of PVS assets. We created algorithms that can be applied on granular time series intervals to provide users with actionable and near-instantaneous performance insights. Trimark Associates is one of the largest control vendors in the US and has access to data from many large PVS plants in addition to hundreds of PV only power plants. We used anonymized data from these plants to validate our methodology. Our methodology leverages the insight that energy storage assets do not create energy by themselves; therefore, it is possible to assess the performance of a PVS plant by following the energy flow to the grid and to the BESS and then comparing the output to a theoretical PV-only power plant that can ship as much energy as it needs to the grid.
We used a two-phase approach to analyze PVS performance data. In the first phase we developed a mathematical formula with assumptions based on potential power flow between devices involved in AC and DC coupled sites. The parameters used as a feature are weather data, PV generation, charge rate, discharge rate, battery state of charge and real power at POI. Using these parameters, we developed four analytics points that directly contribute to the overall performance index: BESS Charge throughput, BESS Discharge throughput, Expected Direct PV energy to grid and the change of battery State of Energy. The mathematical research extended the calculation of these four points to yield the expected energy of the site at different time intervals. The second phase consisted of applying the mathematical approach to historical data to develop thresholds, outlier detection logic and data quality measures based on irradiance and battery data. We then calculated the logical analytics points down at the battery level. Using our approach, each BESS device has its own charge and discharge throughput, state of energy and expected yield points. Once a site-wide underperformance is determined, we can use these new points to effectively identify which device is responsible for underperformance of the site.
To summarize, the most significant results of our research are a holistic performance index, a BESS performance index and a new PV performance index.
The holistic performance index provides a single number that captures the overall performance of AC- and DC-coupled PVS assets, for timeframes ranging from an hour to the lifetime of the asset. The Holistic Performance Index compares the AC generation to expected energy that accounts for three adjustments: temperature adjusted PV Direct expected energy, the BESS system’s round trip efficiency loss, and the change in state of energy of the BESS. This index can then be used as a point of reference for alarming and reporting services.
The BESS Performance Index captures if the charging and discharging process is efficient considering the expected round trip losses. The PV Performance Index evaluates the DC generation of PV modules given the weather conditions. The combination of these indices helps the user to understand the performance status from site level to granular device level.
