Congestion forecasting using a custom loss function: Application to congestion mitigation on substation Middelharnis

Whereas in the past, the Distribution System Operator (DSO) almost never encountered congestion in their grids, nowadays, with the increase of connected renewable energy sources, this will become more prevalent. To forecast congestion on transformer stations, with the goal of mitigating it, the Dutch DSO Stedin uses machine learning models with...

Sustainable and smart distribution networks: Machine Learning and Forecasting

Increasing distributed generation of and demand for electrical energy results ever more in problems like congestion. Forecasting the demand, photovoltaic power generation and the number of electric vehicles connected to charging station for a residential neighbourhood can be an important part of a smarter distribution network for such a...

Probabilistic security assessment of sustainable power grids: Multivariate analysis and dependence modeling for risk-based security assessment

Among the existing Renewable Energy Sources (RES), wind power has become significantly important to Transmission System Operators (TSOs) because of two reasons, namely: i. large Wind Power Plants (WPPs) can be connected to bulk power system at transmission level, and ii. large WPPs are being built or planned in regions with a high potential for...

Investment Costs Reduction of Marine Energy Storage using Smart Power Generation Control

To reduce global warming and air pollution, the maritime industry is searching for solutions to reduce fuel consumption. This thesis focuses on the reduction of generator running hours and fuel consumption of Dynamically Positioned (DP) vessels. In this ship type, redundancy of the power generation system is regularly achieved by running on one...

Long-Term Electricity Load Forecasting Considering Volatility Using Multiplicative Error Model

Long-term electricity load forecasting plays a vital role for utilities and planners in terms of grid development and expansion planning. An overestimate of long-term electricity load will result in substantial wasted investment on the construction of excess power facilities, while an underestimate of the future load will result in...

Forecasting the load of electrical power systems in mid- and long-term horizons: A review

Load forecasting has always been an important part in the planning and operation of electric utilities, i.e., both transmission and distribution companies. With technological advancement, change in economic condition and many other factors (to be discussed in this work), load forecasting is becoming more important. The forecast affects as well...

Volatility in Electrical Load Forecasting for Long-term Horizon: An ARIMA-GARCH Approach

Electrical load forecasting in long-term horizon of power systems plays an important role for system planning and development. Load forecast in long-term horizon is represented as time-series. Thus, it is important to check the effect of volatility in the forecasted load time-series. In short, volatility in long-term horizon affects four main...

Neural Network-based Load Forecasting and Error Implication for Short-term Horizon

Load forecasting is considered vital along with many other important entities required for assessing the reliability of power system. Thus, the primary concern is not to forecast load with a novel model, rather to forecast load with the highest accuracy. Short-term load forecast accuracy is often hindered due to various load impacting factors....