High Levels Of Renewable Penetration Research Articles

Consumer Theory-Based Primary Frequency Regulation in Multi-Microgrid Systems within a P2P Energy Management Framework

This paper presents a novel primary frequency regulation strategy for multi-microgrid (MMG) systems, utilizing consumer theory within a peer-to-peer (P2P) energy management framework. By coordinating photovoltaic (PV) systems and energy storage systems (ESS), the proposed method ensures a rapid and effective response to frequency deviations. Unlike conventional approaches, this strategy minimizes the curtailment of renewable energy sources by prioritizing the use of ESS, allowing excess energy to charge the ESS for later use during under-frequency events. This not only enhances energy efficiency but also maximizes renewable energy utilization. Simulations demonstrate that the proposed scheme achieves lower frequency deviations and faster stabilization compared to traditional droop and virtual inertia methods. These results highlight the potential benefits of integrating consumer theory-based models into primary frequency regulation, significantly enhancing system stability and efficiency in power systems with high levels of renewable energy penetration.

Studying the Optimal Frequency Control Condition for Electric Vehicle Fast Charging Stations as a Dynamic Load Using Reinforcement Learning Algorithms in Different Photovoltaic Penetration Levels

This study investigates the impact of renewable energy penetration on system stability and validates the performance of the (Proportional-Integral-Derivative) PID-(reinforcement learning) RL control technique. Three scenarios were examined: no photovoltaic (PV), 25% PV, and 50% PV, to evaluate the impact of PV penetration on system stability. The results demonstrate that while the absence of renewable energy yields a more stable frequency response, a higher PV penetration (50%) enhances stability in tie-line active power flow between interconnected systems. This shows that an increased PV penetration improves frequency balance and active power flow stability. Additionally, the study evaluates three control scenarios: no control input, PID-(Particle Swarm Optimization) PSO, and PID-RL, to validate the performance of the PID-RL control technique. The findings show that the EV system with PID-RL outperforms the other scenarios in terms of frequency response, tie-line active power response, and frequency difference response. The PID-RL controller significantly enhances the damping of the dominant oscillation mode and restores the stability within the first 4 s—after the disturbance in first second. This leads to an improved stability compared to the EV system with PID-PSO (within 21 s) and without any control input (oscillating more than 30 s). Overall, this research provides the improvement in terms of frequency response, tie-line active power response, and frequency difference response with high renewable energy penetration levels and the research validates the effectiveness of the PID-RL control technique in stabilizing the EV system. These findings can contribute to the development of strategies for integrating renewable energy sources and optimizing control systems, ensuring a more stable and sustainable power grid.

Optimization Technique for Renewable Energy Storage Systems for Power Quality Analysis with Connected Grid

Power quality is the main problem with the power system network. Poor electricity quality may cause disruptions and financial challenges for consumers. Additionally, it could cause electronic gadgets to overheat, be damaged, or operate inadvertently. Transformers and other components of the power distribution system may also overheat and experience core saturation. This study investigates potential problems with the quality of the electricity in a photovoltaic linked power system. This paper suggests a new optimization method for day-ahead trading and control in DC microgrid power management (MG). The goal of the multiobjective optimization dispatch (MOOD) problem is to lower overall operational costs as well as the costs associated with power loss in efficient conservation systems and exhaust emission quantities such as nitrogen oxides, sulphur dioxide, and carbon dioxide. Using the weighted sum approach, the multiobjective optimization problem is reduced to a single optimization problem. The analytical hierarchy process (AHP) method is then used to calculate the weight coefficients while accounting for each objective function’s preferences. Power balancing, high levels of renewable energy penetration, the most effective scheduling of battery charging and discharging, control of load curtailment, and the technical limitations of the system are all taken into account when evaluating the system’s performance in both grid-connected and standalone operation modes. The ant lion optimizer (ALO) technique is taken into account to tackle MOOD, comparing the effectiveness of the proposed method to other well-known heuristic optimization techniques. The simulation’s results demonstrate how effectively the proposed strategy can address the coordinated control and optimization dispatch difficulties. They also found that operating the MG system economically in grid-connected mode can save overall costs by roughly 4.70% compared to doing it in independent mode.

Development of isolated energy systems based on renewable energy sources and hydrogen storage

For the development of the energy infrastructure of remote isolated consumers, an expedient solution is the creation of a modular hybrid energy system based on renewable energy sources, which will save tens of billions of rubles a year by saving expensive diesel fuel. Taking into account the high wind energy resource in these territories, the use of wind power plants as part of that system is justified. The article discusses the methodology for substantiating the parameters and modes of operation of an autonomous wind-diesel power complex based on the territorial-power classification of power supply systems and a 4-level methodology for optimizing parameters, an example of upgrading an existing diesel power plant in the Arkhangelsk region is given. The existing diesel units with a capacity of 1300 kW were replaced by a modular wind-diesel power system with a high renewable penetration level (58%) with four wind turbines with a capacity of 200 kW and a storage system with a capacity of 65 kWh. This made it possible to achieve a diesel fuel replacement share of 232 000 L per year, which in monetary terms in 2021 prices is 25 million rubles per year. As a promising direction, a variant of the territorial development of the energy sector of the Leshukonsky district of the Arkhangelsk region based on wind energy with the possibility of producing up to 100 tons of “green” hydrogen annually is considered. Various options for reducing harmful emissions in the region were considered, the maximum use of local resources allows saving up to 22 000 tons of CO2e per year.

Relaxation‐based bi‐lever reformulation and decomposition algorithm‐based collaborative optimization of multi‐microgrid for cloud energy storage

AbstractEnergy storage devices become an indispensable part of modern power systems with high renewable energy penetration level. To reduce the operating costs, it is a promising way to allow the sharing and leasing of energy storage devices. In this paper, a bi‐lever optimized dispatch scheme is proposed to improve the usage efficiency of cloud energy storage in multi microgrids (MMG) system. Minimizing the operating costs of shared cloud energy storage is the main task of the upper lever while maximizing the profits of MMG is the goal of the lower lever. Moreover, the transaction cost and benefit between the two levers play an important role in system level optimization. This leads to a hybrid optimization problem with both discrete decision variables and continuous decision variables. To solve the problem, a relaxation‐based bi‐lever reformulation and decomposition algorithm is developed. The effectiveness of the proposed bi‐lever dispatch optimization model is verified by carrying out numerical experiments in three scenarios. It is shown that the proposed cloud energy storage service can effectively reduce the operating cost of MMG.

Electricity storage requirements to support the transition towards high renewable penetration levels – Application to the Greek power system

This paper investigates the electricity storage requirements to support the transition towards a high renewable energy source (RES) penetration in a cost-optimal manner. The achieved reduction of renewable energy curtailments and the decrease in the total generation cost of the system are quantified against a counterfactual scenario without storage. A methodology is presented to determine the optimum mix of short- and medium-duration storage needed to support system operation at increased RES penetration levels, using the mixed integer linear programming mathematical optimization. The Greek power system serves as a realistic study case, in its planned development for the year 2030, with a targeted annual RES energy penetration in the order of 60%. Li-ion batteries and pumped-hydro are selected as the representative technologies to include in the storage mix, assuming energy-to-power ratios of up to 6 h for the former and 10 h for the latter. It is shown that the introduction of a suitable mixture of storage facilities may improve renewable energy integration and, at the same time, reduce system cost to the extent that entirely compensates for the full cost of storage, thus allowing for a net economic benefit for the system. The optimum storage portfolio for the study case system and the targeted RES penetration level combines 2-h batteries and 6-h pumped-hydro stations, with an aggregate capacity of new facilities between 1250 MW and 1750 MW, on top of the existing 700 MW of open-loop pumped hydro plants. The optimum storage requirements vary with the targeted RES penetration and with the balance of RES technologies in the generation mix, particularly the level of PV integration.

A comparative evaluation of CO2 emissions between internal combustion and electric vehicles in small isolated electrical power systems - Case study of the Canary Islands

One of the goals of the European Union (EU) is to reduce greenhouse gas (GHG) emissions. To this end, internal combustion vehicles (ICVs) will be progressively replaced with battery electric vehicles (BEVs) over the course of a transition period that is expected to last until 2035. While GHG reductions have been extensively evaluated for continental territories, this is not the case for territories with isolated electrical power systems, as in some islands of the EU. Emissions generated in these territories are considerably higher than in continental systems because their electricity generation mixes commonly have more polluting fuels. In this study, a calculation is performed of the CO2 emissions that result from the charging of a reference BEV in the different isolated electrical power systems of the Canary Islands (Spain). The results are then compared with the CO2 emissions of ICVs. Results show that the Canary electrical power systems that consume the least energy are the most contaminating and that charging a BEV entails higher CO2 emissions than those generated by an ICV. In addition, no significant differences were observed between BEV- and ICV-related CO2 emissions in the electrical power systems of the islands with higher energy consumption. A small decrease in CO2 emissions was only observed in isolated insular systems with energy storage systems and high levels of renewable penetration.

Data-driven energy management of isolated power systems under rapidly varying operating conditions

We propose an energy management algorithm for isolated industrial power systems that integrate uncertain renewable generation and energy storage. The proposed strategy is designed to ensure sustainable and cost-effective operations by managing the energy flows in the grid, and is structured so to cope with: (1) high levels of renewable power penetration, and (2) load profiles characterized by non-smooth patterns and irregular events (i.e., events such as those occurring from connections/disconnections of large scale equipment, or from large wind speed ramps). The proposed algorithm leverages a stochastic economic model predictive control (MPC) scheme capable of dealing simultaneously with the dispatch and scheduling of the local generation units. More precisely, the scheme embeds a mixed-integer linear programming (MILP) optimal control policy formulation together with a stochastic programming approach. Moreover, the optimization problem accounts for multiple techno-economical objectives, such as minimization of operational costs, battery degradation, and non-utilized energy. We test the algorithm on a case study of an isolated offshore Oil & Gas platform producing energy onsite with conventional gas turbines and a local wind farm, while integrating a battery energy storage system. The results show that the proposed approach can issue ensemble predictions that successfully capture the potential irregular variations just by using recent past information of the associated random variable, even when no particular sudden events are anticipated in the near-future (i.e., step changes/trend reversals). In this way, the approach provides useful future information for the optimal management of the grid. This effect is numerically quantified via simulations that compare the performance of the proposed stochastic optimization approach against its deterministic MPC version in several realistic operating conditions. The empirical results suggest that the stochastic version leads to better scheduling of the conventional generators, with up to 12.86% reductions of the operating cost, 2.56% reduction in fuel consumption and emissions, and 35.29% reduction in status transitions (on/off) of the gas turbines, while keeping dumped energy and battery degradation as low as possible.

Transmission System Electromechanical Stability Analysis with High Penetration of Renewable Generation and Battery Energy Storage System Application

Despite the benefits of wind and solar photovoltaic generation, its stochastic characteristic imposes uncertainties on the electric power system’s transient stability. The dynamics considering large synchronous generators has been studied for many decades, and its behavior is well known. On the other hand, the penetration of renewable sources has reached records, showing that it is still vital to study their impact. The present work proposes computer modeling and simulations for the dynamic analysis of electromechanical stability in a transmission system with significant renewable generation. In general, the literature does not propose solutions to the electromechanical stability analysis, proving that there are gaps to be filled. Therefore, the main work contribution consists of designing and coupling a battery energy storage system to a solar plant to smooth power variations. A significant innovation is the proposition of different scenarios that replicate disturbance situations, where the analyses were carried out using the Brazilian grid code. It was possible to evaluate the robustness of the proposed system and the efficiency of the storage system in mitigating the impacts of renewable generation. Thus, it is possible to achieve high levels of renewable penetration if extensive and rigorous studies are carried out.

Analytical Methods of Voltage Stability in Renewable Dominated Power Systems: A Review

The ongoing development of renewable energy and microgrid technologies has gradually transformed the conventional energy infrastructure and upgraded it into a modernized system with more distributed generation and localized energy storage options. Compared with power grids utilizing synchronous generation, inverter-based networks cannot physically provide large amounts of inertia, which means that more advanced and extensive studies regarding stability considerations are required for such systems. Therefore, appropriate analytical methods are needed for the voltage stability analysis of renewable-dominated power systems, which incorporate a large number of inverters and distributed energy sources. This paper provides a comprehensive literature review of voltage stability analyses of power systems with high levels of renewable energy penetration. A series of generalized evaluation schemes and improvement methods relating to the voltage stability of power systems integrated with various distributed energy resources are discussed. The existing voltage stability analysis methods and corresponding simulation verification models for microgrids are also reviewed in a systematic manner. The traditional and improved voltage stability analysis methods are reviewed according to the microgrid operation mode, the types of distributed generators, and the microgrid configurations. Moreover, the voltage stability indices, which play a crucial role in voltage stability assessments, are critically evaluated in terms of the applicable conditions. The associated modeling and simulation techniques are also presented and discussed. This contribution presents guidelines for voltage stability analysis and instability mitigation methods for modern renewable-rich power systems.

A multi-model method to assess the value of power-to-gas using excess renewable

Power-to-Gas (P2G) is a process that produces a gas from electricity, which is most commonly hydrogen via electrolysis. While some studies have considered hydrogen as a power-to-power storage vector, it could also be used as a fuel across the energy system, for example for transport or heat generation. Here, two energy models are used to explore the potential contribution of P2G as a cost-effective source of hydrogen, particularly for future energy systems with high variable renewable energy (VRE) in which there are occasional periods when electricity supply exceeds demand. A detailed electricity system model is iterated with a multi-vector energy system model using a soft-linking approach. This iterative approach addresses shortcomings in each model to better understand the optimal capacity of P2G and the potential economic capture rate of excess VRE. The modelling method is applied to Great Britain in 2050 as a case study. A substantial proportion of excess VRE in 2050 can be captured by P2G, and it is economically competitive compared with alternative sources. Moreover, the effectiveness and economic viability of P2G for reducing excess renewable is robust at even very high levels of renewable penetration. • We soft-linked long-term energy system model (UK TIMES) with power system model to examine value of Power-to-Hydrogen(P2G). • The variability of VRE and the potential curtailment are investigated at spatially and temporally explicit details. • P2G using excess renewable could be an important hydrogen supply and also help integrate high level of VRE. • P2G using excess renewable is found as the most cost-effective technology for generating hydrogen for 2050 in GB case study. • P2G would accounts for 87%-100% of total excess renewable in different scenarios, with the lowest production cost.

Demand Side Flexibility Potential and Comfort Performance of Non-Residential Buildings

The need to create and maintain a sustainable indoor environment is now more than ever compelling. Both the legislation framework concerning the energy performance of buildings, as determined in its evolution through the EU Directives 2010/31/EU, 2012/27/EU and 2018/844/EU, and the European strategic plans towards green buildings, denote the need of sustainability and comfort of indoor environment for the occupant. Moreover, the EU Directive 2018/2001 sets the renewable energy target of at least 32% for 2030, denoting that the high renewable energy sources penetration level leads to challenges in the design and control of power generation, transmission and distribution. Demand side management may be able to provide buildings with the energy flexibility needed, in order to utilize the intermittent production of Renewable Energy Sources in a much more efficient and cost-effective way. The flexibility potential of installed building systems is investigated, while considering the effects on the indoor environment conditions and the perceived comfort. The implemented Demand Response (DR) control strategy shifts loads by changing heating system set point temperatures, based on market clearing prices of the day ahead market. The results indicated a reduction in energy consumption and energy costs, while maintaining indoor environment quality at satisfactory levels.

Robust Volt-Var control of a smart distribution system under uncertain voltage-dependent load and renewable production

As empirical reports validate dependency between power load and voltage at the distribution level, the distribution system operators are concerned with how to benefit from this relationship to achieve a more efficient Volt-Var control (VVC). Specifically, the potential impact of this dependency is a critical issue under uncertain operational parameters. For the first time, this paper develops a robust optimization (RO) model to handle the uncertain voltage-dependent load (VDL) and renewable power production involved in the VVC of a smart distribution system. The uncertain data are presented as uncertainty sets in a finite rolling horizon. The smart grid technology allows the VVC unit to schedule the system devices near real-time. This way, the VVC unit seeks to maintain voltages within their admissible limits through the schedules while minimizing the total cost of power losses, switching operations, and renewable energy spillage plus the penalty of voltage violations. A number of comparative studies are performed through a 69-bus test system to analyze the impact of load models, robustness parameters, renewable penetration level, and alternative uncertainty models on the VVC performance. The results verify that by ignoring the voltage-dependent terms of the ZIP model, the VVC unit estimates total cost and voltage violation with meaningful errors. Additionally, a conservative RO strategy provides a reduced voltage violation compared to a less conservative RO strategy while resulting in a higher cost. Compared to the deterministic and stochastic programming approaches, the RO model has the medium priority based on the metrics of the total cost, voltage violation, and computation time under a medium renewable penetration level, and even the top priority from the aspect of voltage violation under a high renewable penetration level.

Study of the Intelligent Control and Modes of the Arctic-Adopted Wind–Diesel Hybrid System

For energy supply in the Arctic regions, hybrid systems should be designed and equipped to ensure a high level of renewable energy penetration. Energy systems located in remote Arctic areas may experience many peculiar challenges, for example, due to the limited transport options throughout the year and the lack of qualified on-site maintenance specialists. Reliable operation of such systems in harsh climatic conditions requires not only a standard control system but also an advanced system based on predictions concerning weather, wind, and ice accretion on the blades. To satisfy these requirements, the current work presents an advanced intelligent automatic control system. In the developed control system, the transformation, control, and distribution of energy are based on dynamic power redistribution, dynamic control of dump loads, and a bi-directional current transducer. The article shows the architecture of the advanced control system, presents the results of field studies under the standard control approach, and models the performance of the system under different operating modes. Additionally, the effect of using turbine control to reduce the effects of icing is examined. It is shown that the advanced control approach can reduce fuel consumption in field tests by 22%. Moreover, the proposed turbine control scheme has the potential to reduce icing effects by 2% to 5%.

Power-Sensitivities-Based Indirect Voltage Control of Renewable Energy Generators With Power Constraints

Recently, renewable energy has received considerable attention worldwide due to environmental problems such as climate change. However, there are still many problems to be solved to increase the penetration level of renewable energy sources in a power system. Above all, a power system with a high renewable penetration level requires an entirely novel operational strategy and control approach to achieve reliable operation by considering the intermittency of variable renewable energy sources. This paper proposes power-sensitivities-based indirect voltage control of renewable energy generators with power constraints. The proposed method realizes seamless control of the voltage by compensating with the reactive power if the real power of the distributed generator (DG) is insufficient due to its intermittency. To achieve the proposed method, the real and reactive power references of DGs are initially operated based on the power sensitivities between generation and loads if all the DGs operate within the power constraints. However, if at least one of the DGs reaches its constraint limit, the references can be modified using other sensitivities between real and reactive power generation enabling indirect voltage control of DGs. Therefore, a high level of renewable penetration in power systems can be accomplished with the proposed method. The proposed method is verified with several case studies that are based on a microgrid with practical data from a real island power system. Verification is carried out using the power system computer aided design and electromagnetic transient including DC (PSCAD/EMTDC™) simulation software.

Frequency regulation of a weakly connected microgrid using the fuzzy-PID controller

Abstract Microgrid system stability is a major source of concern due to the rapid increase in load demand and a high level of renewable energy penetration. During the grid- connected mode, the microgrid power quality is mainly affected by the level of connection strength with the host grid. Thus, this paper aims to investigate the impact of the implemented control strategy in the microgrid, on frequency response when its level of connection strength is weak, that is, the frequency and voltage are not dominantly controlled by the grid. A control scheme based on a fuzzy logic-based self-tuning PID controller (fuzzy-PID) is used to maintain the frequency within the acceptable range. Simulations illustrate that the frequency dynamic response of the microgrid guarantees a good performance using the fuzzy-PID controller despite a large drop in grid inertia and the presence of disturbances whereas the classical PID controller cannot maintain the frequency within the acceptable range.

Multi-objective optimization for an integrated renewable, power-to-gas and solid oxide fuel cell/gas turbine hybrid system in microgrid

Power-to-gas (P2G) using excess renewable sources is an effective method to reduce renewable curtailment issues in microgrid system. The produced hydrogen is versatile green fuel for different energy sectors, such as electricity, heat and mobility. In recent researches, fuel cell-based system is considered as a promising technology to consume hydrogen (H2) generated from P2G due to high efficiency and cleanness. However, its economic and thermodynamic adaptability when coupled with intermittent renewable sources remains an open question to be addressed carefully. One of the major challenges in optimizing such system is to simultaneously capture the intraday and seasonal variation of renewable sources & load, as well as the internal thermodynamic process of critical components in appropriate modeling detail. This paper presents a multi-energy system for microgrid in which a wind-powered P2G is coupled with a detailed thermoeconomic model of solid oxide fuel cell/gas turbine (SOFC/GT) hybrid system. A two-level multi-objective optimization of planning and operation together is proposed. For system planning, the optimal balance between the least wind curtailment rate and total life cycle cost (LCC) is determined. To facilitate the coordinate operation of system components, a power management strategy is proposed in response to fluctuations of wind power and electricity load with considerations of multiple thermodynamic safety criteria. Results show that in the selected case, the multi-energy system operates with low wind curtailment rate of 0.63% and high renewable penetration level of 90.1%. The optimized LCC of multi-energy system is £2,468,093 with wind power accounting for 68.35% of total capital investment. With the power management strategy applied, the SOFC/GT could operate under the maximum electrical efficiency of 67.1% with safety constraints satisfied, making up only half investment cost of P2G. To capture seasonal variations, both winter and summer scenarios are detailly analyzed, sensitivity analysis is also carried out to evaluate the interaction between capacities of MES components.

Impact of Renewable Energy Sources on Inertia and Frequency Response of Power Systems

With its extensive and growing use in power systems, renewable energy sources (RES) affect power system dynamics and stability. This paper presents the impact of renewable energy sources on power system dynamics, especially through their effect on reducing the system inertia. Thus, affecting power system frequency response and stability. An analysis of the effect of inertia on system frequency dynamics is presented. Also, the possibility of determining the system inertia through online measurements is discussed and illustrated with a double-bus case study. Finally, some suggested solutions for enhancing power system dynamics with high penetration levels of renewables are presented

A novel matching formulation for startup costs in unit commitment

We present a novel formulation for startup cost computation in the unit commitment problem (UC). Both our proposed formulation and existing formulations in the literature are placed in a formal, theoretical dominance hierarchy based on their respective linear programming relaxations. Our proposed formulation is tested empirically against existing formulations on large-scale UC instances drawn from real-world data. While requiring more variables than the current state-of-the-art formulation, our proposed formulation requires fewer constraints, and is empirically demonstrated to be as tight as a perfect formulation for startup costs. This tightening can reduce the computational burden in comparison to existing formulations, especially for UC instances with large reserve margins and high penetration levels of renewables.

PFR ancillary service in low‐inertia power system

A high level of renewable resource penetration could lead to displacement of conventional synchronous generators from dispatch, and consequently, reduce the system inertia. The decline in the system inertia will increase the primary frequency response (PFR) need requiring to maintain grid frequency stability. This study proposes a new market design to co-optimise energy, inertia and PFR while considering uncertainties in renewable energy productions. A full dynamic model of Electric Reliability Council of Texas (ERCOT) interconnection is used to quantify the PFR requirement for the system inertia. The proposed method explicitly incorporates frequency dynamics and uncertainties in energy production from renewable resources in the scheduling process, which is formulated as a stochastic unit commitment problem. A case study of ERCOT grid demonstrated that the proposed stochastic scheduling of energy, inertia and PFR could yield a more cost-effective solution than the traditional deterministic formulation for the grids with a high penetration of renewable resources.