Grid-connected Distributed Energy Resources Research Articles

A tri-level programming-based frequency regulation market equilibrium under cyber attacks

Owing to their flexibility and rapid response, grid-connected distributed energy resources (DERs) are wielding growing influence in frequency regulation markets (FRMs). Nevertheless, compared with conventional large-scale generators, small-scale DERs are usually weakly shielded by cyber security measures. This offers attackers the opportunity of disrupting the clearing and settlement of FRMs by manipulating the bid information of DERs. In this paper, the frequency regulation market equilibrium is studied considering the dynamic gaming between attackers and defenders, both of which need the knowledge of FRMs for their interventions. Specifically, a tri-level programming model characterizing the attacker–defender–operator (ADO) interdiction problem in FRMs is developed and then analyzed using a column and constraint generation algorithm, thereby achieving market equilibrium representing the defender's best response to the attacker. The defense strategy in the market equilibrium can attenuate the negative influence of cyber attacks upon the FRMs to the maximum extent. Finally, based on the operating rules of the California Independent System Operator, the FRM process considering the ADO interdiction is simulated and the numerical equilibrium results are presented.

Empowering tomorrow, controlling today: A multi-criteria assessment of distribution grid tariff designs

The energy transition is in full development with an ever-growing omnipresence of low voltage grid-connected distributed energy resources which cause congestion in the low voltage (LV) distribution grid. Two plausible solutions to network congestion issues are increased grid control (flexibility) or capacity power reinforcements. Electricity distribution tariffs are a promising intersection of these solutions as pricing structures that match consumer patterns can influence demand and grid investments can be recovered by cost-causal pricing.Designing electricity grid tariffs is complex due to its multi-disciplinary character. As previous research has addressed the singular aspects of distribution tariff structures, it is necessary to assess the performance of tariff designs from a multitude of perspectives. For the aforesaid reason, the goal of this paper is to investigate which distribution grid tariffs perform better by drawing upon a complete and coherent set of stakeholder-relevant criteria on all multi-disciplinary objectives of distribution tariff structures and assessing those structures with systematic decision theory. Results based on a systematic literature review, a TOPSIS multi-criteria decision assessment and statistical uncertainty analyses show that tariff performance significantly increases for capacity real-time pricing tariffs, capacity-based rates with Paris-Metro pricing and capacity peak load contribution charges.

A Passive Islanding Detection Method for Distribution Power Systems With Multiple Inverters

The high penetration of grid-connected distributed energy resources (DERs) leads to a need for smart inverters to enhance their performance and minimize the negative impacts of these resources on grid behavior. However, the interconnection of these smart inverters may interfere with their anti-islanding algorithms, which creates detection difficulties. Advanced islanding detection techniques are therefore required to detect and disrupt islanding operations under such an environment with system’s disturbances and interferences. Even though various islanding detection methods have been developed in recent literature to identify islanding operations with high detection accuracy and minimized nondetection zone, these methods mainly focus on a single inverter system, which is incompatible in modern power system with high penetration of grid-connected inverters. In this article, an advanced passive islanding method is proposed for a single-phase distribution power system taking account of the interferences and disturbances brought by these grid-connected inverters. The effectiveness of the proposed passive islanding method is validated through experiments in a laboratory platform. Also, the experimental results have verified that the proposed methods can effectively terminate the islanding operation even with rich inverters’ interferences.

Iterative learning control of dispatchable grid-connected distributed energy resources for compensation of grid current harmonic distortions

This paper proposes a power regulation scheme for dispatchable grid-connected distributed energy resource (DER) units based on the iterative learning control (ILC) strategy. The proposed control provides fast and stable control of the real and reactive powers that the DER unit delivers to the grid. In addition, it compensates the harmonic distortion of the grid current caused by the local nonlinear loads and delivers a high quality power to the grid. To this end, the paper presents the mathematical model on which the proposed control is based, as well as the control design methodology. A new MIMO iterative learning control with perfect power tracking and harmonic rejection performance as well as minor measurement requirements is proposed. The performance of the proposed ILC strategy is demonstrated through time-domain simulation of a grid-connected DER unit under various operating scenarios, and it is compared with the performance of the conventional control based on the instantaneous power theory (IPT).

Application of the method of dynamic programming for solving the optimal unit commitment problem in distribution networks with local distributed generation

The continuous growth of communities leads to an increase in electrical energy usage. Besides the technological advance of power systems, still, there are outages which lead to an interruption in the power supply. The implementation of distributed generation provides usage of the local renewable energy sources for satisfying local power needs which in good manner complexes the distribution networks. However, because the distributed energy resources depend on the weather conditions, the islanded work is not quite reliable. Grid-connected distributed energy resources have enhanced power supply reliability. In this paper, a dynamic programming model is used for the optimisation of power generation by the local distributed energy resources. Assuming the distributed energy resources have storage systems, the model takes into account the battery charge at the moment and the availability of the distributed energy resources depending on the weather conditions and whether is day or night. It is assumed that the distributed energy resources have equal power capacities. Case study reviews a low voltage distribution network with plenty of distributed energy resources from different renewable energy sources implemented and a cluster of household consumers.

Sampling-Based Model Predictive Control of PV-Integrated Energy Storage System Considering Power Generation Forecast and Real-Time Price

This paper proposes a novel control solution designed to solve the local and grid-connected distributed energy resources (DERs) management problem by developing a generalizable framework capable of controlling DERs based on forecasted values and real-time energy prices. The proposed model uses sampling-based model predictive control (SBMPC), together with the real-time price of energy and forecasts of PV and load power, to allocate the dispatch of the available distributed energy resources (DERs) while minimizing the overall cost. The strategy developed aims to find the ideal combination of solar, grid, and energy storage (ES) power with the objective of minimizing the total cost of energy of the entire system. Both offline and controller hardware-in-the-loop (CHIL) results are presented for a 7-day test case scenario and compared with two manual base test cases and four baseline optimization algorithms (Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Quadratic Programming interior-point method (QP-IP), and Sequential Quadratic Programming (SQP)) designed to solve the optimization problem considering the current status of the system and also its future states. The proposed model uses a 24-hour prediction horizon with a 15-minute control horizon. The results demonstrate substantial cost and execution time savings when compared to the other baseline control algorithms.

Controller Hardware-in-the-Loop Validation of a Graph Search Based Energy Management Strategy for Grid-Connected Distributed Energy Resources

This article presents a controller hardware-in-the-loop (CHIL) validation of a novel energy storage management (ESM) solution designed to optimize the use of grid-connected distributed energy resources (DERs) based on the forecasting of generation, load, and real-time energy prices. The proposed control strategy aims to control the operations of the energy storage (ES) using the A* searching algorithm so that the total cost of energy used to serve the local electrical load is minimized. The proposed solution uses the energy storage states and available forecast data to generate a graph that is explored using the A* search algorithm with the objective of finding the optimum cost of energy. The proposed ESM is tested offline against genetic algorithm and sequential quadratic programming based solutions and shows cost improvement of 5% to 8.9%. A CHIL validation testbed was also implemented to evaluate the performance of the algorithm. A Florida based distribution grid was simulated using real field data in a DTRS, and the IEEE 1815 DNP3 communication protocol was used to establish the communication between the controller and the simulation. The graph search-based ESM was implemented in python in an external computer which served as the controller. Offline and real-time simulations are presented showing comparable results.

Technical grid connection guides for distributed electricity generation systems: a new DERlab database has come alive

The increasing share of distributed energy resources (DER) in electricity production requires new sources and techniques in grid support services to keep the quality and reliability of power supply high. Addressing this matter, DER systems are required to follow technical grid connection requirements determined by distribution system operators (DSOs). Currently, these requirements widely differ from country to country. Recent studies suggest developing unified grid connection requirements for DER on the international level. This unification currently is the main activity for DSOs and standardisation organisations in the field of grid-connected DER. To support this activity, the present article (i) offers a status report on recent studies relevant to the harmonisation of DER grid connection requirements, and (ii) identifies and discusses current DER grid connection guides, namely standards of international and European standardisation organisations, as well as regulations of national DSOs from Austria, Germany, Ireland, Latvia, Switzerland (German-speaking part) and the United Kingdom. The guides are collected and grouped according to the technical area and technology in a database: http://dergridrequirements.net. The database is a tool for finding relevant DER grid connection guides for a specific region, technical area and/or technology. The target audience of the database is DER system developers.