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Register a new userReal-time Control of Battery Energy Storage Systems to Provide Ancillary Services Considering Voltage-Dependent Capability of DC-AC Converters
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Frequency response and voltage support are vital ancillary services for power grids. In this paper, we design and experimentally validate a real-time control framework for battery energy storage systems (BESSs) to provide ancillary services to power grids. The objective of the control system is to utilize the full capability of the BESSs to provide ancillary services. We take the voltage-dependent capability curve of the DC-AC converter and the security requirements of BESSs as constraints of the control system. The initial power set-points are obtained based on the droop control approach. To guarantee the feasibility of the power set-points with respect to both the converter capability and BESS security constraints, the final power set-points calculation is formulated as a nonconvex optimization problem. A convex and computationally efficient reformulation of the original control problem is then proposed. We prove that the proposed convex optimization gives the global optimal solution to the original nonconvex problem. We improve the computational performance of this algorithm by discretizing the feasible region of the optimization model. We achieve a 100 ms update time of the controller setpoint computation in the experimental validation of the utility-scale 720 kVA / 560 kWh BESS on the EPFL campus.
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The renewable energy is connected to the power grid through power electronic converters, which are lack of make the inertia of synchronous generator/machine (SM) be lost. The increasing penetration of renewable energy in power system weakens the frequency and voltage stability. The Grid-Forming Converters (GFCs) simulate the function of synchronous motor through control method in order to improve the stability of power grid by providing inertia and stability regulation mechanism. This kind of converter control methods include virtual synchronous machine, schedulable virtual oscillator control and so on. These control method mainly use AC side state feedback and do not monitor the DC side state. This paper analyzes the control strategy of GFC considering power grid stability, including Frequency Droop Control, Virtual Synchronous Machine Control and dispatchable Virtual Oscillator Control. The DC side voltage collapse problem is found when a large load disturbance occurs. The control methods of GFC considering DC side voltage feedback are proposed, which can ensure the synchronization characteristics of grid connection and solve the problem of DC side voltage collapse. The proposed method is verified by IEEE-9 bus system, which shows the effectiveness of the proposed method.
We give the definition of s-Vector control by using the complex power vector in the p-q plane to quantify the feasible operational region of battery energy storage system (BESS) and to find the optimal power set-point solution. The s-Vector control features in the avoidance of using costly optimization solvers to solve optimization models online which is also an execution time bottleneck in real-time control. The advantages of s-Vector control are fast and stable computational efficiency. We validate a s-Vector based real-time controller of BESS to provide frequency response and voltage support as ancillary services for the power grid. The objective is to maximize the utility of the BESS asset. We formulate the dynamic capability curve of the DC-AC converter and the security requirements of the battery cells as constrains of the control system. The initial power set-points are obtained based on the traditional droop control approach. Based on s-Vector control, a fast optimization solution algorithm is proposed to find the optimal power set-point and guarantee the security. According to the experimental validation in our 720 kVA / 560 kWh BESS on EPFL campus, we achieve 100 ms of refreshing the real-time control loop. As a benchmark, using optimization solver requires 200 ms to update the real-time control loop.
Energy storage can be used for many applications in the Smart Grid such as energy arbitrage, peak demand shaving, power factor correction, energy backup to name a few, and can play a major role at increasing the capacity of power networks to host renewable energy sources. Often, storage control algorithms will need to be textit{tailored} according to power networks billing structure, reliability restrictions, and other local power networks norms. In this paper we explore residential energy storage applications in Uruguay, one of the global leaders in renewable energies, where new low-voltage consumer contracts were recently introduced. Based on these billing mechanisms, we focus on energy arbitrage and reactive energy compensation with the aim of minimizing the cost of consumption of an end-user. Given that in the new contacts the buying and selling price of electricity are equal and that reactive power compensation is primarily governed by the installed converter, the storage operation is not sensitive to parameter uncertainties and, therefore, no lookahead is required for decision making. A threshold-based textit{hierarchical} controller is proposed which decides on the optimal active energy for arbitrage and uses the remaining converter capacity for reactive power compensation, which is shown to increase end-user profit. Numerical results indicate that storage could be profitable, even considering battery degradation, under some but not all of the studied contracts. For the cases in which it is not, we propose the best-suited contract. Results presented here can be naturally applied whenever the tariff structure satisfies the hypothesis considered in this work.
A major concern associated to the massive connection of distributed energy resources is the increasing share of power electronic interfaces resulting in the global inertia reduction of power systems. The recent literature advocated the use of voltage source converter (VSC) interfaced battery energy storage system (BESS) as a potential way to counterbalance this lack of inertia. However, the impact of VSCs on the dynamics of reduced-inertia grids is not well understood especially with respect to large transmission grids interfacing a mix of rotating machines and resources interfaced with power electronics. In this regards, we propose an extension of the IEEE 39-bus test network used to quantify the impact of VSCs on reduced-inertia grids. In this respect, a reduced-inertia 39-bus system is obtained by replacing 4 synchronous generators in the original 10-synchronous machine system, with 4 wind power plants modeled as aggregated type-3 wind turbines. Then, a large-scale BESS is integrated into the reduced-inertia network via a three-level neutral-point clamped (NPC) converter, thereby to be used for studying the impact of VSC on the dynamics of the inertia-reduced power system, as well as for comparing different VSC controls. The proposed models are implemented on a real-time simulator to conduct post-contingency analysis, respectively, for the original power system and the reduced-inertia one, with and without the BESS-VSC.
This paper introduces network flexibility into the chance constrained economic dispatch (CCED). In the proposed model, both power generations and line susceptances become variables to minimize the expected generation cost and guarantee a low probability of constraint violation in terms of generations and line flows under renewable uncertainties. We figure out the mechanism of network flexibility against uncertainties from the analytical form of CCED. On one hand, renewable uncertainties shrink the usable line capacities in the line flow constraints and aggravate transmission congestion. On the other hand, network flexibility significantly mitigates congestion by regulating the base-case line flows and reducing the line capacity shrinkage caused by uncertainties. Further, we propose an alternate iteration solver for this problem, which is efficient. With duality theory, we propose two convex subproblems with respect to generation-related variables and network-related variables, respectively. A satisfactory solution can be obtained by alternately solving these two subproblems. The case studies on the IEEE 14-bus system and IEEE 118-bus system suggest that network flexibility contributes much to operational economy under renewable uncertainties.
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