Key Technical Performance Indicators for Power Plants

In this chapter, we will underline the importance of the key performance indicators (KPIs) computation for power plants’ management. The main scope of the KPIs is to continuously monitor and improve the business and technological processes. Such indicators show the efficiency of a process or a system in relation with norms, targets or plans. They usually provide investors and stakeholders a better image regarding location, equipment technology, layout and design, solar and wind exposure in case of renewable energy sources and maintenance strategies. We will present the most important KPIs such as energy performance index, compensated performance ratio, power performance index, yield, and performance, and we will compare these KPIs in terms of relevance and propose a set of new KPIs relevant for maintenance activities. We will also present a case study of a business intelligence (BI) dashboard developed for renewable power plant operation in order to analyze the KPIs. The BI solution contains a data level for data management, an analytical model with KPI framework and forecasting methods based on artificial neural networks (ANN) for estimating the generated energy from renewable energy sources and an interactive dashboard for advanced analytics and decision support

Electricity Consumption and Generation Forecasting with Artificial Neural Networks

Nowadays, smart meters, sensors and advanced electricity tariff mechanisms such as time-of-use tariff (ToUT), critical peak pricing tariff and real time tariff enable the electricity consumption optimization for residential consumers. Therefore, consumers will play an active role by shifting their peak consumption and change dynamically their behavior by scheduling home appliances, invest in small generation or storage devices (such as small wind turbines, photovoltaic (PV) panels and electrical vehicles). Thus, the current load profile curves for household consumers will become obsolete and electricity suppliers will require dynamical load profiles calculation and new advanced methods for consumption forecast. In this chapter, we aim to present some developments of artificial neural networks for energy demand side management system that determines consumers’ profiles and patterns, consumption forecasting and also small generation estimations

Decision Support System Design for Photovoltaic Systems Operation and Maintenance by using Big Data Technologies

Main goal of this paper is to present a decision support system (DSS) for operation andmaintenance (O&M) of photovoltaic power (PV) systems which are integrated with batterysystems. Such DSS essentially necessitates inclusion of Big Data analytics that will be utilized tomaximize profit from power generation and consumption in a PV-battery integrated system

Data Management for Photovoltaic Power Plants Operation and Maintenance

Main goal of this paper is to present our approach in terms of data management for operationand maintenance (O&M) activities of photovoltaic power (PV) systems that aims to decrease O&Mcosts and increase the availability and life cycle of the PV and profit of the business. The O&M activities targets PV output maximization and cost minimization, improvingperformance and lifetime of the PV. Data management for PV O&M activities, proposed in thispaper, contributes to the long-term performance and revenue capacity of PV

Electricity Price Evolution and the Disruptive Economic and Geopolitical Context on the Spot Market. A Romanian Case Study

The current context of the electricity markets is marked by the lingering effects of COVID-19 and the conflict in Ukraine that have a significant influence on the European wholesale electricity markets. Both Day-Ahead Market (DAM) and balancing market have been heavily impacted by fluctuating prices. This trend started in October 2021 when the lockdowns were removed and the high request for commodities led to a higher inflation. Then in 2022, the conflict in Ukraine accentuated this evolution and even higher prices were recorded for electricity, gas, oil and other resources. In this paper, we analyze a set of fundamental variables and provide an electricity price forecast on DAM using a multiple regression model. The exogenous variables considered in this paper are the following: power system data (total consumption, total generation and its breakdown: renewables (RES) and Non-RES), economic data (inflation, interest rate), certificate price for CO2 emissions (EU-ETS), level of Danube River and other resources prices (oil, gas). Interesting insights can be extracted from a data set that consists of merged time series collected from January 2019 until August 2022. The results are measured using Mean Absolute Percentage Error (MAPE)

Analyses of Wind and Photovoltaic Energy Integration from the Promoting Scheme Point of View: Study Case of Romania

The integration of renewable energy sources (RES) has several complex technical and economic aspects, such as: grid reinforcement, tertiary power reserves required for intermittent operation of RES, promoting or support scheme, etc. In this paper, the focus will be given to wind and photovoltaic energy integration from the promoting scheme point of view, with a special emphasis on the case of Romania. In this respect, we propose a model that shows the relation between wind and photovoltaic energy integration and support scheme in Romania. Due to the green certificates (GC) support scheme design that is related to several elements such as total consumption forecast, installed power of the plants based on each type of RES and their full load hours that are expected to vary, we also perform several sensitivity analyses. The GC support scheme implemented in Romania provides interesting insights regarding the installed power based on the primary energy source that could benefit from the GC for RES investors, policy and decision makers

Consumption Management Informatics Solution for Increasing Consumers’ Awareness towards Energy Efficiency

The paper presents an informatics solution for increase consumers’ awareness towards energy efficiency considering three main aspects: consumption optimization, market segmentation and smart application for monitoring and scheduling electrical appliances and real time billing information

Aspects Referring Wind Energy Integration from the Power System Point of View in the Region of Southeast Europe. Study Case of Romania

Wind energy integration is a complex target that could refer to different aspects such as: grid capacity; power system; support scheme; environmental; social issues; etc. It is probably the less predictable renewable energy sources (RES) due to its high volatility being difficult to be securely integrated into the power systems. This paper will focus on the wind energy integration from the power system point of view, emphasizing the case of Romania. Before going into the Romanian case, the paper analyzes the potential benefits of the regional approach in terms of power system integration, revealing that it can bring significant advantages by reducing the required power reserves or increasing wind power plants (WPP) generation. Currently, the power system integration is one of the major obstacle to large scale wind energy penetration in the region of Southeast (SE) Europe with high wind energy potential. The results of our research consist in proposing a model for estimating the balancing reserves sharing at regional level, comparing regional to country-by-country approach in terms of the power reserve requirements for balancing the operation of WPP. It definitely reveals that by regional Transmission System Operators (TSO) coordination; less reserves are needed; therefore, the space for RES enlarges. We also propose a model for Romanian power system that is able to calculate the installed power of WPP that could operate without considerable interruptions. Also, the model estimates the additional power reserves required for larger wind energy integration. This perspective can provide interesting insights on what should be foreseen as reasonable behavior of the policy makers and investors