Insufficient flexibility in system operation caused by traditional "heat-set" operating modes of combined heat and power (CHP) units in winter heating periods is a key issue that limits renewable energy consumption. In order to reduce the curtailment of renewable energy resources through improving the operational flexibility, a novel optimal scheduling model based on chance-constrained programming (CCP), aiming at minimizing the lowest generation cost, is proposed for a small-scale integrated energy system (IES) with CHP units, thermal power units, renewable generations and representative auxiliary equipments. In this model, due to the uncertainties of renewable generations including wind turbines and photovoltaic units, the probabilistic spinning reserves are supplied in the form of chance-constrained; from the perspective of user experience, a heating load model is built with consideration of heat comfort and inertia in buildings. To solve the model, a solution approach based on sequence operation theory (SOT) is developed, where the original CCP-based scheduling model is tackled into a solvable mixed-integer linear programming (MILP) formulation by converting a chance constraint into its deterministic equivalence class, and thereby is solved via the CPLEX solver. The simulation results on the modified IEEE 30-bus system demonstrate that the presented method manages to improve operational flexibility of the IES with uncertain renewable generations by comprehensively leveraging thermal inertia of buildings and different kinds of auxiliary equipments, which provides a fundamental way for promoting renewable energy consumption.
This paper proposed an approach to identify the change of inertia distribution in high renewable power systems. Using the footprints of electromechanical wave propagation at the distribution level, this approach provides a new and non-invasive way to aware the system inertia distribution for primary frequency response. Actual measurements and high renewable dynamic models validated effectiveness of the approach.
Traditionally, inertia in power systems has been determined by considering all the rotating masses directly connected to the grid. During the last decade, the integration of renewable energy sources, mainly photovoltaic installations and wind power plants, has led to a significant dynamic characteristic change in power systems. This change is mainly due to the fact that most renewables have power electronics at the grid interface. The overall impact on stability and reliability analysis of power systems is very significant. The power systems become more dynamic and require a new set of strateg…
Traditionally, power system's inertia has been estimated according to the rotating masses directly connected to the grid. However, a new generation mix scenario is currently identified, where conventional supply-side is gradually replaced by renewable sources decoupled from the grid by electronic converters (i.e., wind and photovoltaic power plants). Due to the significant penetration of such renewable generation units, the conventional grid inertia is decreasing, subsequently affecting both reliability analysis and grid stability. As a result, concepts such as 'synthetic inertia', 'hidden ine…
Modern electricity grids throughout the world, particularly in islands such as Great Britain, face a major problem on the road to decarbonisation: the significantly reduced level of system inertia due to integration of Renewable Energy Sources (RES). Given that most RES such as wind and solar are decoupled from the grid through power electronics converters, they do not naturally contribute to system inertia. However, RES could support grid stability through appropriately controlling the converters, but currently no market incentives exist for RES to provide this support. In this paper we devel…
The progressive integration of electronic converter based Renewable Energy Sources will lead to a reduction of the system synchronous inertia that can endanger the system frequency stability behavior, especially in the case of isolated or poorly interconnected systems, such as the case of Iberian Peninsula system. This work focuses on the study of the impact that the synchronous inertia reduction can have on the Iberian system frequency stability for different critical operation scenarios and disturbances. For this purpose, an equivalent dynamic model of the Iberian system interconnected with …
Load-generation balance and system inertia are essential for maintaining frequency in power systems. Power grids are equipped with Rate-of-Change-of Frequency (ROCOF) and Load Shedding (LS) relays in order to keep load-generation balance. With the increasing penetration of renewables, the inertia of the power grids is declining, which results in a faster drop in system frequency in case of load-generation imbalance. In this context, we analyze the feasibility of launching False Data Injection (FDI) in order to create False Relay Operations (FRO), which we refer to as FRO attack, in the power s…
To stabilize the frequency of the renewable energy sources (RESs) dominated power system, frequency supports are required by RESs through virtual inertia emulation or droop control in the newly published grid codes. Since the long-term RES prediction involves significant errors, we need online configure the frequency control parameters of RESs in a rolling manner to improve the operation economics under the premise of stabilizing system frequency. To address this concern, this paper proposes a frequency constrained stochastic look-ahead power dispatch (FCS-LAPD) model to formulate the frequenc…
On the path towards power systems with high renewable penetrations and ultimately carbon-neutral, more and more synchronous generation is being displaced by variable renewable generation that does not currently provide system inertia nor reactive power support. This could create serious issues of power system stability in the near future, and countries with high renewable penetrations such as Ireland are already facing these challenges. Therefore, this paper aims at answering the questions of whether and how explicitly including inertia and reactive power constraints in generation expansion pl…
This paper proposes a control strategy for a Reverse Fuel Cell used to manage a Renewable Energy Community. A two-stage scenario-based Model Predictive Control algorithm is designed to define the best economic strategy to be followed during operation. Renewable energy generation and users' demand are forecasted by a suitably defined Discrete Markov Chain based method. The control algorithm is able to take into account the uncertainties of forecasts and the nonlinear behaviour of the Reversible Fuel Cell. The performance of proposed approach is tested on a Renewable Energy Community composed by…
Maintaining the stability of renewable-dominant power systems requires the procurement of virtual inertia services from non-synchronous resources (e.g., batteries, wind turbines) in addition to inertia traditionally provided by synchronous resources (e.g., thermal generators). However, the pricing of inertia provision has not been studied in a stochastic electricity market, where the uncertainty characteristics of renewable energy sources (RES) are considered. To fill in this research gap, this paper formulates a chance-constrained stochastic unit commitment model with inertia requirements and…
Energy and water systems are highly interconnected. Energy is required to extract, transmit, and treat water and wastewater, and water is needed for cooling energy systems. There is a rapid increase in demand for energy and water due to factors such as population and economic growth. In less than 30 years, the need for energy and water will nearly double globally. As the energy and water resources are limited, it is critical to have a sustainable energy-water nexus framework to meet these growing demands. Renewable energies provide substantial opportunities in energy-water nexuses by boosting …
As renewable energy sources replace traditional power sources (such as thermal generators), uncertainty grows while there are fewer controllable units. To reduce operational risks and avoid frequent real-time emergency controls, a preparatory schedule of renewable generation curtailment is required. This paper proposes a novel two-stage robust generation dispatch (RGD) model, where the preparatory curtailment schedule is optimized in the pre-dispatch stage. The curtailment schedule will then influence the variation range of real-time renewable power output, resulting in a decision-dependent un…
Conventional synchronous machines are gradually replaced by converter-based renewable resources. As a result, synchronous inertia, an important time-varying quantity, has substantially more impact on modern power systems stability. The increasing integration of renewable energy resources imports different dynamics into traditional power systems; therefore, the estimation of system inertia using mathematical model becomes more difficult. In this paper, we propose a novel learning-assisted inertia estimation model based on long-term recurrent convolutional network (LRCN) that uses system wide fr…
Integration of intermittent renewable energy sources in modern power systems is increasing very fast. Replacement of synchronous generators with zero-to-low variable renewables substantially decreases the system inertia. In a large system, inertia distribution may vary significantly, areas of low inertia are more susceptible to frequency deviation, posing risks of load shedding and generation trip. Therefore, it is necessary for operators to evaluate and quantify the system inertia and its distribution in real time. This paper proposes a novel synchronized phasor measurement units (PMUs)-based…
This paper proposes a robust transient stability constrained optimal power flow problem that addresses renewable uncertainties by the coordination of generation re-dispatch and power flow router (PFR) tuning.PFR refers to a general type of network-side controller that enlarges the feasible region of the OPF problem. The coordination between network-side and generator-side control in the proposed model is more general than the traditional methods which focus on generation dispatch only. An offline-online solution framework is developed to solve the problem efficiently. Under this framework the …
Nowadays, power system inertia is changing as a consequence of replacing conventional units by renewable energy sources, mainly wind and PV power plants. This fact affects significantly the grid frequency response under power imbalances. As a result, new frequency control strategies for renewable plants are being developed to emulate the behaviour of conventional power plants under such contingencies. These approaches are usually called 'virtual inertia emulation techniques'. In this paper, an analysis of power system inertia estimation from frequency excursions is carried out by considering d…
An increasing penetration of renewable generation has led to reduced levels of rotational inertia and damping in the system. The consequences are higher vulnerability to disturbances and deterioration of the dynamic response of the system. To overcome these challenges, novel converter control schemes that provide virtual inertia and damping have been introduced, which raises the question of optimal distribution of such devices throughout the network. This paper presents a framework for performance-based allocation of virtual inertia and damping to the converter-interfaced generators in a low-i…
There has been a significant growth of variable renewable generation in the power grid today. However, the industry still uses deterministic optimization to model and solve the optimal power flow (OPF) problem for real-time generation dispatch that ignores the uncertainty associated with intermittent renewable power. Thus, it is necessary to study stochastic OPF (SOPF) that can better handle uncertainty since SOPF is able to consider the probabilistic forecasting information of intermittent renewables. Transmission network congestion is one of the main reasons for renewable energy curtailment.…
In this article, we focus on the problem of mitigating the risk of not being able to meet the power demand, due to the inherent uncertainty of renewable energy generation sources in microgrids. We consider three different demand scenarios, namely meeting short-time horizon power demand, a sustained energy demand and a scenario where the power demand at a prescribed future time has to be met with almost sure guarantee with power generation being stochastic and following dynamics governed by geometric Brownian motion. For each of these scenarios we provide solutions to meet the electrical demand…
The integration of distributed renewable generation (DRG) in distribution networks can be effectively promoted by scheduling flexible resources such as heating, ventilation, and air conditioning (HVAC) loads. However, finding the optimal scheduling for them is nontrivial because DRG outputs are highly uncertain. To address this issue, this paper proposes a learning-based joint chance-constrained approach to coordinate HVAC loads with DRG. Unlike cutting-edge works adopting individual chance constraints to manage uncertainties, this paper controls the violation probability of all critical const…
The infusion of renewable energy sources into the conventional synchronous generation system decreases the overall system inertia and negatively impacts the stability of its primary frequency response. The lowered inertia is due to the absence of inertia in some of the renewable energy-based systems. To maintain the stability of the system, we need to keep the frequency in the permissible limits and maintain low rotational inertia. Some authors in the literature have used the virtual synchronous generators (VSG) as a solution to this problem. Although the VSG based distributed recourses (DER) …
In this paper, the impact of stochastic load and renewable generation uncertainty on the dynamic voltage stability margin is studied. Stochastic trajectories describing the uncertainty of load, wind and solar generation have been incorporated in the power system model as a set of Stochastic Differential-Algebraic Equations (SDAEs). A systematic study of Monte Carlo dynamic simulations on the IEEE 39-Bus system has been conducted to compute the stochastic load margin with all dynamic components active. Numerical results show that the uncertainty of both demand and generation may lead to a decre…
Driven by ambitious renewable portfolio standards, large-scale inclusion of variable energy resources (such as wind and solar) are expected to introduce unprecedented levels of uncertainty into power system operations. The current practice of operations planning with deterministic optimization models may be ill-suited for a future with abundant uncertainty. To overcome the potential reliability and economic challenges, we present a stochastic hierarchical planning (SHP) framework. This framework captures operations at day-ahead, short-term and hour-ahead timescales, along with the interactions…
A community integrated energy system (CIES) is an important carrier of the energy internet and smart city in geographical and functional terms. Its emergence provides a new solution to the problems of energy utilization and environmental pollution. To coordinate the integrated demand response and uncertainty of renewable energy generation (RGs), a data-driven two-stage distributionally robust optimization (DRO) model is constructed. A comprehensive norm consisting of the 1-norm and infinity-norm is used as the uncertainty probability distribution information set, thereby avoiding complex proba…
This paper proposes a reliable energy scheduling framework for distributed energy resources (DER) of a residential area to achieve an appropriate daily electricity consumption with the maximum affordable demand response. Renewable and non-renewable energy resources are available to respond to customers' demands using different classes of methods to manage energy during the time. The optimal operation problem is a mixed-integer-linear-programming (MILP) investigated using model-based predictive control (MPC) to determine which dispatchable unit should be operated at what time and at what power …
Integration of renewable energy resources with the electric grid is necessary for a sustainable energy future. However, increased penetration of inverter based resources (IBRs) reduce grid inertia, which might then compromise power system reliability. Therefore, power utilities are often interested in identifying the maximum IBR penetration limit for their system. The proposed research presents a methodology to identify the IBR penetration threshold beyond which voltage, frequency, and tie-line limits will be exceeded. The sensitivity of the IBR penetration threshold to momentary cessation due…
In this paper, we propose a high-level Stochastic steady-state model to analyze the value of co-located energy storage systems for wind power producers that participate in an electricity market through Forward or Day Ahead contracts. In particular, we try to find optimal sizing and contracting and stationary operating policies for profit maximization in the long-run. We obtain a stylized model calibrated to actual wind power production and electricity wholesale price data that allows us to asses the value of storage size and perform sensitivity analysis on key parameters such as contract price…
Nowadays, power imbalance happens more frequently due to the more integration of renewable energy sources. Energy storage is a kind of devices that can charge energy at one time and discharge energy at another time. This function makes that storage is widely envolved into promoting power balance of power system. Besides this function, storage can also emulate virtual inertia to respond to frequency deviations in the system. This work provides a generalized optimization framework to analyze how to control power and virtual inertia from storage to participate in frequency response when a large d…
With the integration of Renewable Energy Sources (RESs), the power network must be robust to handle the system's uncertain scenarios. DC Transmission Expansion Planning (TEP) plans are generally not feasible for the AC network. A first bi-level Robust Optimization (RO) solution approach for AC TEP with injection uncertainties in loads and RESs generations is proposed in this paper. It utilizes a well-known convex relaxation and is solved by Benders Decomposition (BD), where the master determines the robust AC TEP plan. A novel dual slave model is developed for the second level of BD, which cir…
In light of a reliable and resilient power system under extreme weather and natural disasters, networked microgrids integrating local renewable resources have been adopted extensively to supply demands when the main utility experiences blackouts. However, the stochastic nature of renewables and unpredictable contingencies are difficult to address with the deterministic energy management framework. The paper proposes a comprehensive distributionally robust joint chance-constrained (DR-JCC) framework that incorporates microgrid island, power flow, distributed batteries and voltage control constr…
Under the downward tendency of prices of renewable energy generators and upward trend of hydrogen demand, this paper studies the technoeconomic supplement of P2G clusters with hydrogen pipeline for HVDC to jointly consume renewable energy. First, the planning and operation constraints of large-capacity P2G clusters is established. On this basis, the multistage coordinated planning model of renewable energy, HVDCs, P2Gs and hydrogen pipelines is proposed considering both variability and uncertainty, rendering a distributionally robust chance-constrained (DRCC) program. Then this model is applie…
The utilization of renewable energy sources (RESs) has become significant throughout the world especially over the last two decades. Although high-level RESs penetration reduces negative environmental impact compared to conventional fossil fuel based energy generation, control issues become more complex as well as total inertia to the system is significantly decreased due to removal of conventional synchronous generators. Some other technical issues, high uncertainties, low fault ride through capability, high fault current, low generation reserve, and low power quality, arise due to RESs integ…
As renewable sources increasingly replace existing conventional generation, the dynamics of the grid drastically changes, posing new challenges for transmission system operations, but also arising new opportunities as converter-based generation is highly controllable in faster timescales. This paper investigates grid stability under the massive integration of grid-forming converters. We utilize detailed converter and synchronous machine models and describe frequency behavior under different penetration levels. First, we show that the transition from 0% to 100% can be achieved from a frequency …
The synchronized operation of power generators is the foundation of electric power network stability and a key to the prevention of undesired power outages and blackouts. Here, we derive the conditions that guarantee synchronization in power networks with inherent generator heterogeneity when subjected to small perturbations, and perform a parametric sensitivity analysis to understand synchronization with varied types of generators. As inverter-based resources, which are the primary interfacing technology for many renewable sources of energy, have supplanted synchronous generators in ever grow…
In order to balance the interests of integrated energy operator (IEO) and users, a novel Stackelberg game-based optimization framework is proposed for the optimal scheduling of integrated demand response (IDR)-enabled integrated energy systems with uncertain renewable generations, where the IEO acts as the leader who pursues the maximization of his profits by setting energy prices, while the users are the follower who adjusts energy consumption plans to minimize their energy costs. Taking into account the inherent uncertainty of renewable generations, the probabilistic spinning reserve is writ…
A community integrated energy system (CIES) with an electric vehicle charging station (EVCS) provides a new way for tackling growing concerns of energy efficiency and environmental pollution, it is a critical task to coordinate flexible demand response and multiple renewable uncertainties. To this end, a novel bi-level optimal dispatching model for the CIES with an EVCS in multi-stakeholder scenarios is established in this paper. In this model, an integrated demand response program is designed to promote a balance between energy supply and demand while maintaining a user comprehensive satisfac…
Seoul National University（首尔国立大学）；Ewha Womans University（梨花女子大学）；Pukyong National University（釜庆国立大学）
Energy management systems (EMS) are becoming increasingly important in order to utilize the continuously growing curtailed renewable energy. Promising energy storage systems (ESS), such as batteries and green hydrogen should be employed to maximize the efficiency of energy stakeholders. However, optimal decision-making, i.e., planning the leveraging between different strategies, is confronted with the complexity and uncertainties of large-scale problems. Here, we propose a sophisticated deep reinforcement learning (DRL) methodology with a policy-based algorithm to realize the real-time optimal…
This paper summarizes the operational challenges imposed by integration of renewable electricity generation units in transmission level where the most common renewable generation units are solar and wind farms at the scale of 100s to 1000s MW. Such units, because of their stochastic nature, introduce new complexity and uncertainty to the grid. Throughout this paper, some results from the recent planning study of integration of 1,000 MW offshore wind farm into the U.S. Eastern Interconnection transmission system are shown.
