Publications

Over the next three years, the Public Service Company of New Mexico (PNM) plans to increase utility-scale solar photovoltaic (PV) capacity from today’s roughly 330MW to about 1600MW. This massive increase in variable generation—from about 15% to 75% of peak load—will require changes in how PNM operates their system. We characterize the 5 and 30-minute solar and wind forecast errors that the system is likely to experience in order to determine the level of reserves needed to counteract such events. Our focus in this study is on negative forecast error (in other words, shortfalls relative to forecast) – whereas excess variable generation can be curtailed if needed, a shortfall must be compensated for to avoid loss of load. Calculating forecast error requires the use of the same forecasting methods that PNM uses or a reasonable approximation thereof. For wind, we use a persistence forecast on actual 5-minute 2019 wind output data (scaled up to reflect the amount of wind capacity planned for 2025). For solar, we use a formula incorporating the clear sky index (CSI) for the forecast. As the solar on the grid now is a small fraction of what is planned for 2025, we generated 5-minute solar data using 2019 weather inputs. We find that to handle 99.9% of the 5-minute negative forecast errors, a maximum of 275MW of variable generation reserve during daylight hours, and a maximum of 75MW during non-daylight hours, should be sufficient. Note that this variable generation reserve is an additional reserve category that specifies reserves over and above what are currently carried for contingency reserve. This would require a significant increase in reserve relative to what PNM currently carries or can call upon from other utilities per reserve sharing agreements. This variable generation reserve specification may overestimate the actual level needed to deal with PNM’s planned variable generation in 2025. The forecasting methodologies used in this study likely underperform PNM’s forecasting – and better forecasting allows for less reserve. To obtain more precise estimates, it is necessary to consider load and use the same forecasting inputs and methods used by PNM.

In 2017, Hurricane Maria damaged a large portion of the Puerto Rico (PR) electrical infrastructure, leading to longterm outages across many regions. Therefore, transformation and re-development of the island's grid system is of high interest. A key part of this re-development is the passing of an updated renewable portfolio standard (RPS), originally enacted in 2010, which states that by 2050 the energy needs in PR will be met entirely by renewable resources. The purpose of this paper is to determine the amount of renewable generation and energy storage necessary to meet these energy goals. An increase in renewable generation within any system poses several difficulties such as meeting night-time demand and handling the operation of the existing thermal fleet. A mixed-integer linear program optimization is formulated to identify the required investments in photovoltaic solar and energy storage to meet the RPS and to minimize the investment and operational costs. Within this RPS case study a sensitivity analysis is performed with different energy storage investment costs scenarios.

Abstract not provided.