Integration Of Distributed Energy Resources Research Articles

Blockchain-based decentralized energy management platform for residential distributed energy resources in a virtual power plant

The advent of distributed energy resources (DERs), such as distributed renewables, energy storage, electric vehicles, and controllable loads, brings a significantly disruptive and transformational impact on the centralized power system. It is widely accepted that a paradigm shift to a decentralized power system with bidirectional power flow is necessary to the integration of DERs. The virtual power plant (VPP) emerges as a promising paradigm for managing DERs to participate in the power system. In this paper, we develop a blockchain-based VPP energy management platform to facilitate a rich set of transactive energy activities among residential users with renewables, energy storage, and flexible loads in a VPP. Specifically, users can interact with each other to trade energy for mutual benefits and provide network services, such as feed-in energy, reserve, and demand response, through the VPP. To respect the users’ independence and preserve their privacy, we design a decentralized optimization algorithm to optimize the users’ energy scheduling, energy trading, and network services. Then we develop a prototype blockchain network for VPP energy management and implement the proposed algorithm on the blockchain network. By experiments using real-world data trace, we validated the feasibility and effectiveness of our algorithm and the blockchain system. The simulation results demonstrate that our blockchain-based VPP energy management platform reduces the users’ cost by up to 38.6% and reduces the overall system cost by 11.2%.

Dynamic performance enhancement of interconnected hybrid thermal power system in the presence of electric vehicles

The prolific integration of non-synchronous distributed energy resources and energy storage systems (EES) into thermal-dominated grids significantly impact the power system's total synchronous inertia (TSI). The TSI, in turn, affects the frequency response of the electrical grid (EG). Although the EES supports frequency regulation, the cost is a vital factor in determining their role. Lately, it is realized that incorporating plug-in hybrid electric vehicles (PHEVs) as auxiliary power sources can provide inertial support if penetrated in huge numbers into the EG. This work proposes a supply and demand variation approach that integrates EVs in load frequency control (LFC). The proposed LFC uses the biogeography-based optimization (BBO) algorithm. A parallel direct current (DC)-alternating current (AC) interconnected hybrid thermal power system (IHTPS) with different types of high voltage direct current (HVDC) tie-links in the presence of PHEVs is simulated. The settling time, oscillations, and first peaks are mainly analyzed for the considered HVDC tie-links. The results show that the virtual synchronous power-HVDC tie-link offers better dynamic performance than that of the other tie-link, proving EV's presence in improving the frequency response. Thus, the investigation demonstrates the BBO based LFC role in enhancing the dynamic performance of the IHTPS.

Transactive Energy Market Framework for Decentralized Coordination of Demand Side Management Within a Cluster of Buildings

Flexibility in electricity demand can be leveraged for demand side management (DSM) to enable aspects such as “demand following generation” and provide ancillary services to support grid integration of renewable and distributed energy resources. The upcoming connected devices in demand centers such as commercial buildings and households may be leveraged for this. However, the coordination among distributed demand centers in a scalable decentralized manner to achieve DSM objectives is still a challenge. In this article, a generalized hierarchical transactive energy based multiagent framework is proposed. This framework includes energy management demand agents (EMDAs) at the building level, which coordinate the operation of different appliances within the buildings. EMDAs also actively participate on day-ahead Walrasian market at the cluster of buildings level. In this market, the effect of wide-adoption of DSM on generation dispatch is also studied. A particular instance of this framework is also implemented in a cyber-test system consisting of standard industrial microcontroller platforms to emulate practical implementations via smart meters. Experimental results of the proposed system are included to demonstrate the possibility of avoiding disptach from expensive generation units by reduction in peak demand and providing demand response inherently.

Decentralized Voltage Stability Monitoring and Control With Distributed Computing Coordination

The computing infrastructure to support the power grid monitoring and control evolves with the increasing system complexity and integration of distributed energy resources (DERs). The integration of DERs requires a stability assessment application to monitor and control at a faster rate compared to the legacy system. Distributed computing architecture provides opportunities for managing these key changes by introducing solutions within substation computers and digital devices such as phasor measurement unit. The proposed decentralized voltage stability using a distributed coordination platform is a secondary emergency control mechanism utilizing large amounts of data in real-time for faster monitoring and control with the legacy system. The developed algorithms have been validated using the IEEE 30, 57, 118, and 300 bus systems using offline and real-time hardware-in-the-loop testbed modeling and simulation. To demonstrate the flexibility of the distributed coordination blocks, multiple case studies and implementation are presented. With control decisions required under changing operating conditions, the IEEE 30 bus system is simulated in real-time using a digital simulator and a network simulator (NS-3). The impact of the SYN flood cyberattack and tolerance of the computing infrastructure to resulting missing data have also been illustrated.

Increasing DER integration through discrete intraday settlements

Deployment of distributed energy resources (DERs) is accelerating across the United States. These assets have the potential to provide cost-effective grid services and bulk power while supporting a low-cost energy transition to carbon-free electricity. Full integration of these resources into the bulk power system remains a barrier to unlocking the potential value of these assets. The regional wholesale energy markets, originally designed to integrate centralized, dispatchable power plants, must be reformed to adapt to the changing potential resource mix. The current day-ahead and real-time system is poorly designed for DERs. Day-ahead DER forecast errors create exposure to real-time price variations, as resources committed in the day-ahead market are required to rebalance in real-time, challenging the business model for DERs. New intraday markets with multiple discrete intermediate auctions between the day-ahead market and real-time market are needed to enable proper integration of DERs and efficient mitigation of forecast uncertainty risk. These markets must incorporate financially-binding commitments, closer-to-dispatch price signals, and adequate liquidity to ensure competition. Intermediate auctions should be built on top of existing intraday processes in each regional market, incorporating the principles of the existing market structures and leveraging the benefits of the centralized dispatch systems. Regional transmission organization (RTOs) and Independent System Operators (ISOs) should pursue and implement intermediate auctions to support fair, open, and efficient markets in the U.S.

Electrical-distance driven peer-to-peer energy trading in a low-voltage network

Given the increasing penetration of distributed energy resources (DER) in low-voltage networks, peer-to-peer (P2P) energy trading has been proposed to facilitate DER integration into power systems. In this paper, we investigate P2P energy trading driven by the electrical distance between agents in a low-voltage network. Our market design considers the role of a distributed system operator (DSO) who determines the shortest path between agents, encoded in preference lists. The DSO submits the preference lists to the agents but does not intervene in the P2P matching process. Specifically, we propose two decentralised P2P market mechanisms that are induced by the relations in the preference lists. First, we introduce a stable-matching (SM) algorithm for matching agents and guaranteeing that no agents want to mutually deviate from the matching. Second, a mechanism based on a continuous double auction (CDA) is adopted for continually matching peers. The proposed mechanisms are tested on a UK low-voltage network. Simulation results show that the outcome of the proposed SM mechanism faces a trade-off between the stability of the matching and market efficiency, whereas the proposed CDA-based mechanism deviates from the stable outcome but can still capture the high market efficiency of the CDA. We show that a P2P market driven by electrical distance leads to reduced losses and line congestion in both mechanisms.

An overview of grid-edge control with the digital transformation

Distribution networks are evolving to become more responsive with increasing integration of distributed energy resources (DERs) and digital transformation at the grid edges. This evolution imposes many challenges to the operation of the network, which then calls for new control and operation paradigms. Among others, a so-called grid-edge control is emerging to harmonise the coexistence of the grid control system and DER’s autonomous control. This paper provides a comprehensive overview of the grid-edge control with various control architectures, layers, and strategies. The challenges and opportunities for such an approach at the grid edge with the integration of DERs and digital transformation are summarised. The potential solutions to support the network operation by using the inherent controllability of DER and the availability of the digital transformation at the grid edges are discussed.

Distributed Optimization for Distribution Grids With Stochastic DER Using Multi-Agent Deep Reinforcement Learning

This article develops a special decomposition methodology for the traditional optimal power flow which facilitates optimal integration of stochastic distributed energy resources in power distribution systems. The resulting distributed optimal power flow algorithm reduces the computational complexity of the conventional linear programming approach while avoiding the challenges associated with the stochastic nature of the energy resources and loads. It does so using machine learning algorithms employed for two crucial tasks. First, two proposed algorithms, Dynamic Distributed Multi-Microgrid and Monte Carlo Tree Search based Reinforcement Learning, constitute dynamic microgrids of network nodes to confirm the electric power transaction optimality. Second, the optimal distributed energy resources are obtained by the proposed deep reinforcement learning method named Multi Leader-Follower Actors under Centralized Critic. It accelerates conventional linear programming approach by considering a reduced set of resources and their constraints. The proposed method is demonstrated through a real-time balancing electricity market constructed over the IEEE 123-bus system and enhanced using price signals based on distribution locational marginal prices. This application clearly shows the ability of the new approach to effectively coordinate multiple distribution system entities while maintaining system security constraints.

Market-Based Coordination of Transmission and Distribution Network Planning with Distributed Energy Resources Planning

Distributed energy resources (DERs) have the potential for the non-lines alternative in both transmission and distribution (T&D) systems. However, the value of DERs in substituting power lines in T&D systems is not revealed and coordinated planning of T&D networks and DERs under market environment is not studied in existing researches. This may damage the interests of DER investors, hinder the wide integration of DERs in power system and increase total cost under market environment. This paper proposes market-based coordination of transmission and distribution network planning (TDNP) with DER planning (DERP). The model is formulated as multi-stage programming. In first stage, transmission companies (TRANSCOs), distribution companies (DISCOs), and DER aggregators (DERAs) send their bidding plans to independent system operator (ISO) and distribution system operators (DSOs), respectively. In second stage, ISO and DSOs check the transmission and distribution network securities, respectively. In third stage, ISO and DSOs solve their optimal operation problems, respectively. An iterative solution algorithm is proposed to solve the multistage model. The solution embodies the interaction process among TRANSCOs, DISCOs, DERAs, ISO, and DSOs in electricity market. Numerical results demonstrate that the proposed model coordinates TDNP with DERP, promotes DER installations and reduces the total cost.

Comprehensive review on hierarchical control of cyber‐physical microgrid system

A microgrid (MG) is a cyber-physical system that facilitates integration of several distributed renewable energy resources. In the last decade, several efforts were made to standardise the framework of a cyber-physical MG network and its control structure. In this perspective, various studies discussing the different control techniques are reported in the literature. However, a comprehensive and systematic review of a cyber-physical MG is discussed rarely. In this study, a comprehensive review of a MG architecture and hierarchical control structure in both islanded and grid-connected modes are presented. The hierarchical control of the MG includes primary, secondary, and tertiary control. Recent studies provide significant opportunities in dividing the control task among various layers resulting in a distributed framework. This study analyses the cyber and physical networks separately while discussing the primary, centralised, and distributed secondary control levels with their merits, demerits, and typical applications. A Venn diagram analysis is also presented that clearly distinguishes the primary control scheme in different research sub-areas. Furthermore, the MG communication structure, protocols, design, constraints, and cyber security are also reviewed systematically. Finally, future trends are summarised based on the state-of-the-art MG research.

Onward and Upward: Distributed Energy Resource Integration [Guest Editorial

The articles in this special section focus on distributed energy resources (DER) in power systems.

Consumer-Led Transition: Australia's World-Leading Distributed Energy Resource Integration Efforts

It's a sunny spring DAY in South Australia. A light breeze is cooling the coastal state capital of Adelaide as approximately 260,000 distributed solar photovoltaic (D-PV) systems on residential and business rooftops generate electricity, setting a new state record for the lowest minimum electrical demand for the third time this season. All looks peaceful throughout the suburbs. D-PVs form an irregular yet persistent patchwork across one-third of the houses in the state. Most consumers are going about their day without a glance at the D-PV panels on these roofs. However, the mild temperature and bountiful sunshine lead the D-PV generation to climb, causing the voltage to creep higher and power to flow in reverse across large swathes of the distribution network. Some D-PVs are tripping off, unbeknownst to their owners and the local network operator.

Investigation of Black-Starting and Islanding Capabilities of a Battery Energy Storage System Supplying a Microgrid Consisting of Wind Turbines, Impedance- and Motor-Loads

Microgrids are small scale electrical power systems that comprise distributed energy resources (DER), loads, and storage devices. The integration of DER into the electrical power system basically allows the clustering of small parts of the main grid into Microgrids. Due to the increasing amount of renewable energy, which is integrated into the main grid, high power fluctuations are expected to become common in the next years. This carries the risk of blackouts to be also more likely in the future. Microgrids hold the potential of increasing reliability of supply, since they are capable of providing a backup supply during a blackout of the main grid. This paper investigates the black-starting and islanding capabilities of a battery energy storage system (BESS) in order to provide a possible backup supply for a small part of the main grid. Based on field tests in a real Microgrid, the backup supply of a residential medium voltage grid is tested. Whereas local wind turbines within this grid section are integrated into this Microgrid during the field test, the supply of households is reproduced by artificial loads consisting of impedance- and motor loads, since a supply of real households carries a high risk of safety issues and open questions regarding legal responsibility. To operate other DER during the island operation of such a Microgrid, control mechanisms have to ensure the power capabilities and energy reserves of the BESS to be respected. Since the operation during a backup supply of such a Microgrid requires a simple implementation, this paper presents a simple master–slave control approach, which influences the power output of other DER based on frequency characteristics without the need for further communication. Besides the operation of other DER, the capability to handle load changes during island operation while ensuring acceptable power quality is crucial for such a Microgrid. With the help of artificial loads, significant load changes of the residential grid section are reproduced and their influence on power quality is investigated during the field tests. Besides these load changes, the implementation and behavior of the master–slave control approach presented in this paper is tested. To prepare these field tests, simulations in Matlab/Simulink are performed to select appropriate sizes for the artificial loads and to estimate the expected behavior during the field tests. The field tests prove that a backup supply of a grid section during a blackout of the main grid by a BESS is possible. By creating the possibility of operating other DER during this backup supply, based on the master–slave control approach presented in this paper, the maximum duration for this backup supply can be increased.

Integrating distributed energy resources in electricity distribution systems: An explorative study of challenges facing DSOs in Sweden

Distribution system operators (DSOs) face challenges integrating distributed energy resources (DERs) into their grid network. This article presents an exploratory study of Swedish DSOs and their actions and capabilities to manage DER integration. The study is based on information from a combination of secondary data, interviews, and surveys. The findings include the current most pressing challenges for Swedish DSOs, different DSO responses to ongoing change, and differences in DSO capabilities to manage increasing shares of DERs. Both regulatory and organizational barriers for DSOs to integrate DERs into distribution grids are identified and discussed.

Multi-criteria decision making monarch butterfly optimization for optimal distributed energy resources mix in distribution networks

The optimal integration of distributed energy resources (DERs) is a multiobjective and complex combinatorial optimization problem that conventional optimization methods cannot solve efficiently. This paper reviews the existing DER integration models, optimization and multi-criteria decision-making approaches. Further to that, a recently developed monarch butterfly optimization method is introduced to solve the problem of DER mix in distribution systems. A new multiobjective DER integration problem is formulated to find the optimal sites, sizes and mix (dispatchable and non-dispatchable) for DERs considering multiple key performance objectives. Besides, a hybrid method that combines the monarch butterfly optimization and the technique for order of preference by similarity to ideal solution (TOPSIS) is proposed to solve the formulated large-scale multi-criteria decision-making problem. Whilst the meta-heuristic optimization method generates non-dominated solutions (creating Pareto-front), the TOPSIS approach selects that with the most promising outcome from a large number of alternatives. The effectiveness of this approach is verified by solving single and multiobjective dispatchable DER integration problems over the benchmark 33-bus distribution system and the performance is compared with the existing optimization methods. The proposed model of DER mix and the optimization technique significantly improve the system performance in terms of average annual energy loss reduction by 78.36%, mean node voltage deviation improvement by 9.59% and average branches loadability limits enhancement by 50%, and minimized the power fluctuation induced by 48.39% renewable penetration. The proposed optimization techniques outperform the existing methods with promising exploration and exploitation abilities to solve engineering optimization problems.

Optimising the value of distributed energy resources

The uptake of network-connected and consumer-owned distributed energy resources (DER) represents a transformational change to the energy mix, structure and operation of our power systems and markets. If DER can be successfully integrated into our electricity networks and markets, there is potential for all electricity system users to benefit. This paper discusses some of the important technical, economic and social opportunities and challenges of optimising the value of DER integration into electricity networks and markets.

Genetic optimisation‐based distributed energy resource allocation and recloser‐fuse coordination

Nowadays, it is possible to notice a growth in the integration of distributed energy resource (DER) in the distribution systems. Despite the many benefits caused by this integration, there are some changes in the load and short-circuit current, which may lead to mis-coordination between protective devices. Moreover, an improper DER integration can generate problems regarding the levels of current, voltage, and power factor of the network. Therefore, in this study, the authors conducted a specific study to optimise the size and location of DER in a distribution feeder, to reduce investment and operation costs, regarding the operational and physical limits of the system and generators. In addition, the optimised recloser-fuse coordination was performed to reduce the actuation time of these protective devices, taking into account the generation and load variation during the day, DER operating modes, and all the fault types. In this study, the optimisation method adopted was genetic algorithms and the IEEE 34-node test feeder was used to validate the proposed methodology. Thus, it was possible to achieve a single protection scheme based on the fuse saving scheme, which is able to coordinate the protective devices for all the analysed cases simultaneously.

Analysis of Challenges Due to Changes in Net Load Curve in South Korea by Integrating DERs

The development of Distributed Energy Resources (DERs) is essential in accordance with the mandatory greenhouse gas (GHG) emission reduction policies, resulting in many DERs being integrated into the power system. Currently, South Korea is also focusing on increasing the penetration of renewable energy sources (RES) and EV by 2030 to reduce GHGs. However, indiscriminate DER development can give a negative impact on the operation of existing power systems. The existing power system operation is optimized for the hourly net load pattern, but the integration of DERs changes it. In addition, since ToU (Time-of-Use) tariff and Demand Response (DR) programs are very sensitive to changes in the net load curve, it is essential to predict the hourly net load pattern accurately for the modification of pricing and demand response programs in the future. However, a long-term demand forecast in South Korea provides only the total amount of annual load (TWh) and the expected peak load level (GW) in summer and winter seasons until 2030. In this study, we use the annual photovoltaic (PV) installed capacity, PV generation, and the number of EV based on the target values for 2030 in South Korea to predict the change in hourly net load curve by year and season. In addition, to predict the EV charging load curve based on Monte Carlo simulation, the EV users’ charging method, charging start time, and State-of-Charge (SoC) were considered. Finally, we analyze the change in hourly net load curve due to the integration of PV and EV to determine the amplification of the duck curve and peak load time by year and season, and present the risks caused by indiscriminate DERs development.

Optimal Meter Placement in Low Observability Distribution Networks with DER

This paper presents a mixed integer linear programming (MILP) approach to deal with the volatility associated with loads and distributed energy resources (DER) in low observability distribution networks. Distribution networks, characterized by having many buses and few meters, have recently faced massive integration of DER, whose injection increases net load volatility. To better understand how to act under such increased volatility, the accuracy of state estimation (SE) needs to be improved. Our approach improves SE accuracy by providing meter placement solutions that take into account uncertainty as expressed by multiple load and DER profile scenarios, this way mitigating the impact of net load volatility. Solution results are illustrated and discussed for different case studies carried out over a radial 9 bus test feeder.

Protection strategy for fault detection in inverter-dominated low voltage AC microgrid

This paper presents a protection strategy based on active power flow direction, current magnitude and voltage sags to determine the existence of low impedance faults in inverter-dominated low voltage AC microgrids. Different fault situations are considered, concerning each element of the microgrid (line section, load, node and energy sources). Simulation is done in MATLAB/Simulink software. Microgrid was modelled based on CIGRE benchmark for network integration of renewable and distributed energy resources, considering the low voltage european distribution network characteristics. Inverter-based distributed generation units were modelled considering a control scheme composed by natural reference frame control and RMS current limiter. The results obtained from simulations indicate that the proposed strategy is able to protect the microgrid in any topology configuration or mode of operation, for all type of low impedance faults.