Conference Agenda

E-redes, S.A. is the main Distribution System Operator (DSO) for high (HV), medium (MV), and low voltage (LV) in Portugal mainland. In Portugal, energy distribution is a regulated activity with regulated revenues, thereby managing OPEX is particularly relevant for E-redes' operations. One of E-redes main responsibilities is to ensure customer connection to the distribution network, according with regulated prices and response time. This article aims to describe some actions taken in operations management related with MV customers connection process, focusing on the following aspects:

- Meeting deadlines defined by the regulator for this activity (avoiding penalties)

- Minimizing process times to meet MV customers’ expectations and thus contribute for boosting country's economic activity (industry, services, etc.)

- Maximizing operations efficiency and consequently OPEX

To achieve this, strategy was based on three main axes:

- Separation of project/budgeting activity from construction activity, centralized at a national level and regionally settled respectively

- Rethink and redesign project/budgeting processes enhancing technology usage

- Revue external services hiring strategy

After one year, results of this strategy are visible, with measurable impacts in OPEX but also in customers' satisfaction. However, challenge is not yet over, and relevant initiatives are underway and worth sharing.

Renewable Energy Communities (RECs) allow owners of photovoltaic (PV) systems to share surplus energy in their neighborhood. A main goal of RECs is the optimized use of locally produced energy and thus a load reduction of the higher-level power grid. Better utilization of renewable energy should offer incentives for households to invest in PV systems and thus contributes to the decarbonization of the energy sector.

Main tools for better utilization are load shifting and intelligent battery management. Based on forecasts of (weather dependent) production and consumption profiles, the associated operational decisions can be optimized to improve the overall performance of the community. The strong interdependence between the community members’ individual resources prohibits the use of simple heuristic decision rules for this purpose. As actual conditions may well deviate from the forecasts used for optimization, not all optimized decisions will yield the intended outcome. Therefore, we developed a model predictive control inspired planning framework comprising an optimization and a simulation model, which models the actual real-world outcome of the planning decisions for the current time step. The introduced framework can be used to generate realistic performance measures over the course of one year and to reach a better understanding of the benefits of forecast-based coordinated operating strategies in RECs. Moreover, the analysis of different scenarios can be used as a basis for investment decisions, e.g., for houseowners considering the purchase or extension of a PV system or a battery.

In 2022 TIWAG (Tiroler Wasserkraft AG), an operator of hydro-electric power plants, integrated a new power plant into their existing network. Increased complexity plus new and extremely rigorous environmental regulations made the established control of their power station network infeasible.

TIWAG needs to ensure energy provision according to the demand forecast, while fulfilling regulatory constraints, such as the limitation of allowed water level gradients in the river. Failing to fulfill these constraints may not only result in penalty fees for TIWAG but can also lead to massive environmental damage.

To solve this, TIWAG and MathWorks Consulting have developed a software solution that regulates the water flow through the power plants and over the weirs into the river, while optimizing the operating schedule. Regulatory constraints can be modeled as nonlinear inequalities.If water flow over the weirs is increased or decreased it must remain constant for several following time steps. Semicontinuous constraints are required to model that the power plant is either switched off (zero water flow) or operating at or above minimal level. Due to the complexity of the nonlinear constraints, we propose an iterative algorithm solving a series of nonlinear optimization problems.

The software is embedded into TIWAG’s productive SCADA (Supervisory Control and Data Acquisition) system and triggered every 3 minutes. It fetches the latest prognosis data, simulates the water flow and reservoir levels, and computes an optimized operation schedule for the next 24 hours. These results are directly used to control the power plants.