Providing Spinning Reserve Research Articles

Estimating Spinning Reserve Capacity With Extreme Learning Machine Method in Advanced Power Systems Under Ancillary Services Instructions

In advanced power systems, to balance load generation mismatches in the face of unexpected events and to meet unforeseen possibilities, load taking and shedding instructions are required under Ancillary Services (AS), which are performed by providing spinning reserve (SR) in the units. SR is an important factor, which is rather uncertain to predict due to the unpredictability of customers’ consumption, excessive or under-energy generation, and unpredictability in the integration of renewable energy sources. In this study, integration of renewable energy is addressed as a factor for predicting SR. Increasing the integration of solar and wind into the power system requires larger amounts of SR, which creates a significant increase in generation and emission costs. Optimum estimation of SR capacity helps system operators (SO) plan generators in advance and in a better bidding environment. In the past, estimation tools such as feed forward networks and time series models have been used to estimate load and electricity generation. In this article, Extreme Learning Machine (ELM) method is used to estimate SR capacity in the day-ahead and intraday market. The results obtained with ELM were also compared with the results observed with ANN, LR and SVM methods.

Evaluate the capacity of electricity-driven water facilities in small communities as virtual energy storage

In small communities, such as small islands, campuses of universities/industrial parks/lab facilities, and remote villages/cities, the Water-Energy Nexus (WEN) operators generally need to purchase electricity from the power grid to meet a portion of their power demand. The WEN of these communities creates new opportunities of providing virtual energy storage (VES) and virtual power plant (VPP) services to the power grid by properly controlling their electricity-driven water facilities (EDWF). This paper investigates the capacity of EDWFs in small communities as VES and VPP. Small communities in four different types of areas, e.g., island, desert, urban, and rural, are studied based on their geographical specifications, to evaluate and compare the capabilities of their WENs as VES and VPP respectively. WENs with high penetration of photovoltaic resources are considered, for which battery energy storage systems (BESS) are needed. An optimization approach of operating the EDWFs as VES is proposed to reduce the required size of BESSs. The state-of-the-art convex technologies are adopted to reduce the computational burden of the developed optimization models which are large-scale mixed-integer nonlinear programming problems. Besides, the WEN of small communities is modeled as a VPP to provide spinning reserve energy for the power grid in emergency conditions. This paper also describes how the EDWFs can be controlled to serve as a virtual system and provides substantial benefits for the small communities. Numerical results validate that it is economically beneficial to operate the WENs of small communities as VES or VPP for renewable energy management of power grids.

On Secured Spinning Reserve Deployment of Energy-Limited Resources Against Contingencies

Featured with fast response abilities and high ramp rates, energy storage systems (ESS), such as pumped-storage hydropower (PSH) plants and battery storage systems (BSS), are considered as key first-responders to provide spinning reserve in response to system contingencies. However, ESSs are energy-limited resources, and their sustained spinning reserve deployment is restricted by the stored energy and available capacity. Indeed, the spinning reserve deployment against contingencies may deviate actual state-of-charge (SOC) from the scheduled value, inducing potential SOC boundary violations and non-dispatchability in later hours. This paper proposes the post-contingency operation model and the spinning reserve secure constraints to address these issues. The post-contingency operation model describes that spinning reserve from ESSs is promptly deployed when contingency occurs, and then gradually substituted by quick-start units when they are switched online. By leveraging this operation strategy, spinning reserve secure constraints in terms of SOC headrooms are adopted to guarantee its deployability. A modified IEEE 118-bus system with multiple PSHs and BSSs is used to verify the proposed approach.

A Short-Term Optimal Scheduling Model for Wind-Solar-Hydro Hybrid Generation System With Cascade Hydropower Considering Regulation Reserve and Spinning Reserve Requirements

In order to meet the challenges brought by the high penetration of intermittent and fluctuating wind and solar power, a short-term optimal scheduling model for wind-solar-hydro hybrid generation system with cascade hydropower is established with the objective of minimizing the amount of abandoned wind, solar and hydro power and maximizing the stored energy of hydro stations. Cascade hydropower is considered to provide spinning reserve and regulation reserve to ensure the security of system. Mixed Integer Linear Programming (MILP) method is used for the short-term optimal schedule of wind-solar-hydro hybrid generation system. The case studies show that spinning reserve and regulation reserve are beneficial to the hybrid generation system, and verify the practical applicability of the proposed model.

A Novel Incentive Mechanism for CCHP-Based Microgrids in Spinning Reserve

To ensure the safe and reliable operation of power system, it is vital to retain some spinning reserve. The increasingly widespread utilization of combined cooling, heating and power (CCHP)-based microgrids (MGs) brings a new way to provide spinning reserve for power system. Therefore, to motivate independent CCHP-based MG operators (CMGOs) to participate in the spinning reserve trading, an incentive mechanism is proposed in this paper. In the mechanism, a distribution system operator (DSO) organizes a number of local CMGOs to participate in the spinning reserve trading and gets spinning reserve from them. A novel index, termed as contribution rate, is proposed to evaluate the participants' contributions to the spinning reserve trading and asymmetric Nash bargaining is adopted to design benefit allocation mechanism. As CMGOs may belong to different economic entities, the centralized solution is not suitable for practical implementation. Distributed solution is proposed to solve the optimization problem through the alternating direction method of multipliers decomposition technique. The simulation results demonstrate the efficacy of the proposed incentive mechanism in achieving benefits for all participants.

Unit commitment of wind integrated power system considering optimal scheduling of reserve capacity

There are multiple uncertainties in the power system with wind farms, such as wind power output, load and forced outage of units, which lead to consider the spinning reserve capacity in unit commitment, which undoubtedly increases the difficulty of problem solving. In order to solve this problem, the fuzzy parameters of wind power output and load are obtained by using the error’s fuzzy characteristics, and the mathematical model of generating unit combination is established to optimize the generator output and spinning reserve simultaneously by using the chance constraint, and the model is solved by using intelligent algorithm. The model fully analyses the cost difference of different units providing spinning reserve and the economic benefit of spinning reserve, aiming at minimizing the difference between the cost of generating reserve and the economic benefit of reserve, so as to maximize the overall economic benefit of the system. The feasibility and validity of the proposed model are verified by a 10-unit system with wind farms. The analysis shows that the model can reasonably consider reserve decision-making in unit commitment to deal with uncertainties in power system.

The value of flexible selling: Power production with storage for spinning reserve provision

A stored commodity is sold under a capacity constraint depending on an exogenous random market price, and, alternatively, a service contract can be provided in which the selling amount must be held constant over time independent of price changes. The seller of the commodity is assumed to optimize the trade-off between the received payment for the provision of the service and the loss of flexibility by the reduced selling on the market. The chosen setup allows for closed-form solutions, such that the analysis is of theoretical interest. A potential application is hydropower storage optimization against exogenous electricity prices with the option to enter contracts for providing spinning reserve; spinning reserve is needed to stabilize large-scale power systems. A single-period model is considered, and the storage level of the commodity is bounded from below in expectation. These simplifications allow a closed-form solution of bang-bang type, even under our assumption of an infinite probability space.

Incorporating energy storage and user experience in isolated microgrid dispatch using a multi‐objective model

In order to coordinate multiple different scheduling objectives from the perspectives of economy, environment and users, a practical multi-objective dynamic optimal dispatch model incorporating energy storage and user experience is proposed for isolated microgrids. In this model, besides Microturbine units, energy storage is employed to provide spinning reserve services for microgirds; and furthermore, from the perspective of demand side management, a consumer satisfaction indicator is developed to measure the quality of user experience. A two-step solution methodology incorporating multi-objective optimization (MOO) and decision analysis is put forward to address this model. First, a powerful heuristic optimization algorithm, called the {\theta}-dominance based evolutionary algorithm, is used to find a well-distributed set of Pareto-optimal solutions of the problem. And thereby, the best compromise solutions (BCSs) are identified from the entire solutions with the use of decision analysis by integrating fuzzy C-means clustering and grey relation projection. The simulation results on the modified Oak Ridge National Laboratory Distributed Energy Control and Communication lab microgrid test system demonstrate the effectiveness of the proposed approach.

Determination of optimal reserve contribution of thermal units to afford the wind power uncertainty

Due to unforeseen variations in wind speed profiles, wind farm integrations are recognized as intermittent and uncertain energy contributors. More specifically, integration of such renewable energy resources aligned with the conventional thermal units although reduces the emissions and brings about a clean environment, it introduces serious problems in assigning optimal and reliable level of these units in load supplying and spinning reserve provision. This situation is more intensified considering the uncertainties arisen by the power system loading demand. To facilitate such operational hurdles, the ongoing study puts forward an efficient model for assigning the optimal spinning reserve which accommodates the uncertainties in both the wind speed and load profiles. Stochastic behavior of these parameters is simulated by generating a proper number of scenarios through the Monte Carlo simulation (MCS) approach. Then, each of these scenarios is evaluated based on the established linear mixed integer approach in a deterministic fashion. Accordingly, a computationally efficient approach is obtained paving the way for real-world implementations and assuring the global optimum results. The proposed approach is applied to a 12-unit test system including 10 thermal units and 2 wind farms. Results are reflected in terms of the commitment status, energy dispatches, and reserve contributions of each committed unit. A comprehensive discussion is conducted to disclose the possible improvements.

Economic environmental unit commitment for integrated CCHP-thermal-heat only system with considerations for valve-point effect based on a heuristic optimization algorithm

For the purposes of lowering environmental emission and total cost, energy efficient combined cooling, heat, and power (CCHP) units can be integrated with conventional separate cooling, heat, and power production units to meet demands. The goal of this study is to develop and examine a heuristic and deterministic optimization algorithm for solving the unit commitment problem for integrated CCHP-thermal-heat only system for (i) satisfying demands for cooling, heat, and power, (ii) providing spinning reserve for power, (iii) reducing environmental emission, and (iv) accounting for valve-point effects for steam turbines of thermal units. When environmental emission cost and valve-point effects are considered, the utilization of CCHP units in an integrated CCHP-thermal-heat only system results in environmental emission and total cost reduction by and 38.37 and 0.03%, respectively, as compared with those resulting from operating thermal and heat only units separately.

Experimental and Numerical Investigations on the Origins of Rotating Stall in a Propeller Turbine Runner Operating in No-Load Conditions

Hydraulic turbines are more frequently used for power regulation and thus spend more time providing spinning reserve for electrical grids. Spinning reserve requires the turbine to operate at its synchronous rotation speed, ready to be linked to the grid in what is termed the speed-no-load (SNL) condition. The turbine's runner flow in SNL is characterized by low discharge and high swirl leading to low-frequency high amplitude pressure fluctuations potentially leading to blade damage and more maintenance downtime. For low-head hydraulic turbines operating at SNL, the large pressure fluctuations in the runner are sometimes attributed to rotating stall. Using embedded pressure transducer measurements, mounted on runner blades of a model propeller turbine, and numerical flow simulations, this paper provides an insight into the inception mechanism associated with rotating stall in SNL conditions. The results offer evidence that the rotating stall is in fact associated with an unstable vorticity distribution not associated with the runner blades themselves.

Cooperation of Demand Response and Traditional Power Generations for Providing Spinning Reserve

Spinning reserve in the electric power system is vital in dealing with the sudden drop of electricity supply caused by failure, which used to be provided by traditional power generations. With the development of information and communication technologies (ICTs), demand response (DR) is deployed gradually for providing spinning reserve by shedding flexible loads. Air conditioners (ACs) are one of the most high-quality flexible loads due to its high proportion of capacity in electricity consumption. However, power rebound spike (PRS) of AC loads tend to emerge at the end of DR. Therefore, traditional spinning reserve providers (TSRPs) have to ramp to cooperate with ACs immediately. In this paper, a DR management approach is proposed for controlling DR duration time and capacity by sequent temperature configuration. Meanwhile, the connection between PRS and DR duration time is studied. Reliability indices have also been applied to evaluate different cooperation strategies between ACs and TSRPs. Simulations based on Monte Carlo methods are performed quantitatively.

Distributed algorithm for dynamic economic power dispatch with energy storage in smart grids

The dynamic economic dispatch problem with energy storage in a smart grid scenario is studied, which aims at minimising the aggregate generation costs over multiple periods on condition that the time-varying demand is met, while physical constraints on generation and storage as well as system spinning reserve requirement are satisfied. In our model, energy storage devices are incorporated for not only inter-temporal energy arbitrage to reduce total generation cost, but also providing spinning reserve to share generators' burden. To solve this problem, we assume that the communication networks are strongly connected directed graphs and propose a fully distributed algorithm based on the `consensus-like' iterative algorithm and the alternating direction method of multipliers. Our algorithm is distributed in the sense that no leader or master nodes are needed, while all the nodes conduct local computation and communicate merely with their neighbours. Numerical simulation is included to show the effectiveness of the proposed algorithm.

The economics of commercial demand response for spinning reserve

Demand response (DR) for spinning reserve may be appropriate for customers whose operational constraints preclude participation in energy and capacity DR programs. We investigate the private business case of an aggregator providing spinning reserve in California across customer end uses and business segments. Revenues are calculated using end use level hourly load profiles. With average annual revenue of $$\sim $$ $35/kW, steady end uses (e.g., lighting) are more than twice as profitable as seasonal end uses (e.g., cooling) because spinning reserve is needed year-round. Business segments with longer operating hours, such as groceries or lodging, have more revenue potential. Total costs for participation would need to be under $250/kW for many end uses and business segments to have payback periods less than 5 years, which is plausible given equipment cost data from California’s Automated Demand Response programs. Avoided carbon emission damages from using DR instead of fossil fuel generation for spinning reserve could justify incentives for DR resources.

Multi-objective stochastic scheduling optimization model for connecting a virtual power plant to wind-photovoltaic-electric vehicles considering uncertainties and demand response

A stochastic chance-constrained planning method is applied to build a multi-objective optimization model for virtual power plant scheduling. Firstly, the implementation cost of demand response is calculated using the system income difference. Secondly, a wind power plant, photovoltaic power, an electric vehicle group and a conventional power plant are aggregated into a virtual power plant. A stochastic scheduling model is proposed for the virtual power plant, considering uncertainties under three objective functions. Thirdly, a three-stage hybrid intelligent solution algorithm is proposed, featuring the particle swarm optimization algorithm, the entropy weight method and the fuzzy satisfaction theory. Finally, the Yunnan distributed power demonstration project in China is utilized for example analysis. Simulation results demonstrate that when considering uncertainties, the system will reduce the grid connection of the wind power plant and photovoltaic power to decrease the power shortage punishment cost. The average reduction of the system power shortage punishment cost and the operation revenue of virtual power plant are 61.5% and 1.76%, respectively, while the average increase of the system abandoned energy cost is 40.4%. The output of the virtual power plant exhibits a reverse distribution with the confidence degree of the uncertainty variable. The proposed algorithm rapidly calculates a global optimal set. The electric vehicle group could provide spinning reserve to ensure stability of the output of the virtual power plant. Demand response could optimize customers’ power consumption behaviors and improve the grid connection space of the virtual power plant. The electric vehicle group and demand response could achieve a linkage optimization effect between the generation side and demand side, achieving optimal system scheduling objectives.

Contributions to the preliminary assessment of a Water Pumped Storage System in Terceira Island (Azores)

The need to provide Spinning Reserve (SR), together with the need to respect some operational constraints, points to high power state combinations of the thermal power plants, therefore reducing the penetration of renewables in the power mix and eventually leading to wind curtailment. Water Pumped Storage Systems (WPSS) are a way to overcome this issue, by storing the surplus energy not needed in the valley periods, to use it later in peak periods. This situation is dealt with in this paper, through the proposal of an energy balance technical model, taking into account the constraints and operational limits of the thermal power plant, together with an economic model based on NPV and IRR. This model is applied to assess the Terceira Island case-study. Despite the fact that this is a simplified model, not using any optimization techniques, it was possible to conclude that WPSS provide both thermal based electricity and wind curtailment reduction, therefore facilitating the integration of renewable energy in the power system and enhancing the environmental aspects of electricity production. Moreover, it was found that there are turbine/pump sizing combinations that can turn the project into an economically viable one. Also, it was demonstrated that further economic feasibility could be achieved if SR requirements could be lowered. This aspect should be considered by Terceira system operator.

Value of flexible electric vehicles in providing spinning reserve services

As the share of integrated renewable energy sources (RES) increases, traditional operation principles of the power systems need to change in order to maintain reliable and secure service provision, on one hand, and minimal cost and environmentally friendly electricity generation on the other. The challenge of alleviating additional uncertainty and variability brought by new sources to the system operation is seen as defining both flexibility capacities and flexibility requirements through provision of multiple services. In this context the role of emerging technologies, such as electric vehicles (EV) and energy storage (ES), is recognized through their active participation in providing both energy and reserve service.This paper elaborates on the benefits of active EV participation in multiple system services through various charging strategies. The presented mixed integer linear programming (MILP) unit commitment problem (UC) considers the capability of EV to provide primary, secondary and tertiary reserve as well as energy, however the focus is put on the benefits of EV providing spinning reserve services. The results clearly show benefits of multiple EV role to that of providing energy only. In addition the paper analyses multiple power systems, with regards to their energy mix, and recognizes how integration of EVs reflects on power system flexibility through metrics expressed as operational cost, environmental benefits and reduced wind curtailment.

Application of data envelopment analysis theorem in plug‐in hybrid electric vehicle charging station planning

In the near future, millions of electric vehicles (EVs), especially plug-in hybrid EVs (PHEVs), will be integrated into the electrical system. Such an increase in the demand for energy will require optimised management of distribution networks. This study presents a new formulation to determine the optimal size and location of PHEV charging stations to maximise the distribution system manager (DSM) benefit. A two-stage procedure has been considered to optimise PHEV charging station planning. In the first stage, the candidate locations and their size are determined based on: (i) the sum of benefits from the appropriate use of charging station for charging and discharging of vehicles and (ii) the benefit of providing spinning reserve and supplying the network's load demand at peak times by DSM. In the next stage, an improved framework is proposed to classify charging stations into efficient and inefficient sets characterised by non-financial indices. The proposed method is data envelopment analysis efficiency and three indices, including active power loss, voltage profile improvement and CO2 emission. The suggested model is successfully applied to a test system with nine buses. Simulation results show that appropriate planning results in economic benefits as well as improvements in active power losses and the voltage profile.

Spinning reserve supply with presence of electric vehicles aggregator considering compromise between cost and reliability

By increasing the spinning reserve capacity, reliability of the power system is improved, however, total cost is increased. Therefore to supply the spinning reserve of power system, a compromise between reliability and cost should be considered. In this study, by considering the value of lost load for each important customer, the spinning reserve capacity is determined based on minimisation of total cost of problem. In addition, to supply the spinning reserve of power system, a new market player called plug-in electric vehicles (PEVs) aggregator is proposed. In this base, the aggregator's self-scheduling problem for participating in spinning reserve market is modelled using an agent-based model and behaviour of the PEVs fleet is modelled from the aggregator's point of view. To improve the accuracy of results, the market players are considered as price makers and their offers to the market are modelled using a dynamic game theory simulation. The numerical results show that the presence of PEVs aggregator in spinning reserve market has desired impacts on power system reliability and total cost of system.

Probabilistic Spinning Reserve Provision Model in Multi-Control Zone Power System

Inter-zonal trading in multi-area power system (MAPS) improves the market efficiency and the system reliability by sharing the resources (energy and reserve services) across zonal boundaries. Actually, each area can operate with less reserve resources than would normally be required for isolated operation. The aim of this work is to propose a model that includes the problem of optimal spinning reserve (SR) provision into the security constraint unit commitment (SCUC) formulation based on the reliability criteria for a MAPS. The loss of load probability (LOLP) and the expected load not served (ELNS) are evaluated as probabilistic metrics in the case of a multi-control zone power system. Moreover, we demonstrate how these criteria can be explicitly incorporated into the market-clearing formulation. The non-coincidental nature of spinning reserve requirement across the zonal boundary is effectively modeled. Two system cases including a small-scale (six-bus) test system and the IEEE reliability test system (IEEE-RTS) are used to demonstrate the effectiveness of the presented model.