Coupled active and reactive market in smart distribution system considering renewable distributed energy resources and demand response programs

The distribution system operator (DSO) needs an optimal day-ahead scheduling (ODAS) for the economic and sustainable supply of electrical energy considering input parameters such as the price of the upstream grid. Next-generation distribution networks or smart distribution networks are the future networks where responsive loads are available. Renewable sources include wind turbines and solar panels have expanded. The presence of electric vehicles and the purchase from the electricity upstream market is provided, and the network can be programmed and controlled through the devices which record and transmit information. In this chapter, a robust optimization (RO) method has been proposed to minimize the cost of ODAS of smart distribution system (SDS) considering load-responsive and renewable energy sources (RESs) such as wind turbine (WT) and nonrenewable sources such as diesel generators (DGs) and battery energy storage system (BESS). The proposed method considers all the technical constraints of the upstream grid and DGs and the utilized BESS. In order to model SDSs, a 33-base IEEE test system has been used in the evaluation of the proposed model. The proposed ODAS concept determines the optimal level of exchange with the upstream network, the production of each dispersed generation unit, and the participation of demand response (DR) programs. It also provides an optimal layout for charging and discharging the BESS. It can be observed that the proposed model has the optimal scheduling capabilities of the SDSs considering the uncertainties of power market price. Moreover, it is observed that the resilient optimization method reduces the cost of network operation and confronts the price of electricity with uncertainty.

One of the most important Distribution System Operators (DSO) schemes addresses the Volt/Var control (VVC) problem. Developing a cost-based reactive power dispatch model for distribution systems, in which the reactive powers are appropriately priced, can motivate Distributed Energy Resources (DERs) to participate actively in VVC. In this paper, new reactive power cost models for DERs, including synchronous machine-based DGs and wind turbines (WTs), are formulated based on their capability curves. To address VVC in the context of competitive electricity markets in distribution systems, first, in a day-ahead active power market, the initial active power dispatch of generation units is estimated considering environmental and economic aspects. Based on the results of the initial active power dispatch, the proposed VVC model is executed to optimally allocate reactive power support among all providers. Another novelty of this paper lies in the pricing scheme that rewards transformers and capacitors for tap and step changing, respectively, while incorporating the reactive power dispatch model. A Benders decomposition algorithm is employed as a solution method to solve the proposed reactive power dispatch, which is a mixed integer non-linear programming (MINLP) problem. Finally, a typical 22-bus distribution network is used to verify the efficiency of the proposed method.

The ESS is considered as an effective tool for enhancing the flexibility and controllability of a wind farm, and the optimal control scheme of a wind farm with distributed ESSs is vital to the stable operation of wind power generation. In this paper, a coordinated active and reactive power control strategy based on model predictive control (MPC) is proposed for doubly fed induction generator (DFIG)-based wind farm (WF) with distributed energy storage systems (ESSs). The proposed control scheme coordinates the active and reactive power output among DFIG wind turbines (WTs), grid-side converters (GSCs), and distributed ESSs inside the WF, and the aim is to decrease fatigue loads of WTs, make the WT terminal voltage inside the extent practicable, and take the WF economic operation into consideration. Moreover, the best reactive power references of DFIG stator and GSC are produced independently based on their dynamics. At last, the control scheme generates optimal power references for all ESS to make the SOC of each ESS converge to their average state. With the distributed ESSs, the WF controller regulates the WTs inside WF more flexibly. A WF composed of 10 DFIG WTs was utilized to verify the control performance of the proposed coordinated active and reactive power control strategy.

In a re-structured environment, demand response (DR) programs are presented in a new style. The demand response program consists of demand-side management methods which answers to electricity price variations. With advent of electricity markets, the demand-side management programs was introduced into two categories: (1) energy efficiency program, (2) demand response program. This paper studies engagement of participants load in an electricity market having a grid with large and small loads interested to participate in the market, energy storage systems, micro-grids, and distributed generations. In the proposed scheme, it is supposed to have an aggregator which sends demand-side preferences including load curtailment, load shifting, onsite generation, and energy storage systems along with proposed value and prices and all respective system constraints to the independent system operator (ISO). In fact, load aggregators submit aggregated DR offers to the ISO in order to optimize final decisions on aggregators’ DR contributions in wholesale market. The main goal of this paper is to solve the operation problem considering demand-side, system, and pollution and reliability constraints. Compared to other methods, the results indicate that the explicit modeling of customer DR would provide ISOs with more flexible options for scheduling the available energy resources in day-ahead energy markets.

Several studies and field tests have shown the potential of conservation voltage reduction (CVR) to decrease peak demand, energy consumption, and system losses. Nonetheless, the energy savings achievable by CVR is dependent on the load model, which could be constant power, current, impedance, or any combination of these models. Also, the use of distributed energy resources (DERs) at the distribution level presents a challenge to successful CVR implementation as these resources could cause voltage fluctuations in the system. This paper studies the impact of load models on CVR implementation in a distribution system feeder interfaced with renewable DERs. Load flow analyses are carried out using constant power (PQ) and constant impedance (Z) load models, respectively, and the resulting effects on feeder losses and energy consumption are observed as CVR is implemented. In addition, the impacts of DERs and voltage regulation devices on the feeder voltage profile are analyzed. The feeder losses showed opposite trends with constant PQ and Z loads as CVR is implemented. Overall, the results showed varied impacts of load models and DER output on feeder losses, energy consumption, and bus voltages in the distribution network.

The smart grid, perceived as the next generation power grid, uses two-way flow of electricity and information to create a widely distributed automated energy delivery network. By grouping distributed renewable energy generations and loads, a microgrid, which is seen as one of the cornerstones of the future smart grids, can disconnect from the macrogrid and function autonomously. This intentional islanding of generations and loads has the potential to provide a higher local reliability than that provided by the power system as a whole. One of the fundamental issues for a user in an islanded microgrid is how to find the one among the distributed renewable energy resources (DRERs) in a microgrid, which can supply the power most efficiently, effectively and reliably, as its power supply source. This problem is difficult since the power pattern of renewable resources, such as wind and solar, is variable and generally speaking is not easy to accurately predict. In order to solve this problem, we first propose a distributed DRER discovery approach to discover all the available DRERs within a microgrid. Furthermore, based on the online machine learning theory, we propose two distributed algorithms according to the information the user can obtain, in order to compute a good DRER access strategy, with no assumption on what distribution the power patterns of the DRERs follow. We prove that when the time horizon is sufficiently large, on average the upper bound on the gap between the expected profit obtained at each time slot by using the global optimal strategy and that by using our algorithms is arbitrarily small.

Emerging types of software and communication systems that manage distributed energy resources (DERs) such as solar photovoltaic, wind turbines, flywheels, battery storage systems, etc. are termed Distributed Energy Resources Management Systems (DERMS). When properly deployed, their capabilities provide multiple benefits to both, utilities and their customers. DERMS consists of a set of software management tools that allow distribution companies and operators to manage a range of DERs, and offer almost real-time network control. DERMS can help tremendously in integrating, managing, and controlling flexible and intermittent DERs and electric demand. These analyses contribute to keeping the transmission and distribution system in sync with the efficient and reliable balance of supply and demand that should lead to ideally optimization of power flows, electric demand, DERs, and traditional centralized generation. Moreover, in order to handle distributed generation (DG) and to intensify its visibility within power markets, the idea of virtual power plant (VPP) has emerged. Dynamic, automated, and cost-effective management of the distribution system is achieved with DERMS tools that are presented in this paper. Moreover, various hierarchy-levels of DERMS tools co-exist nowadays, such as DER aggregator, VPP, Utility DERMS, and they all can tremendously improve efficiency of Active Distribution Networks (ADN). This paper presents an overview of the current state-of-the-art regarding various DERMS tools, and their capabilities to increase the overall distribution system efficiency.

Reactive power procurement: A review of current trends

With the development of science and technology, there has been growing the grid size, the growing demand for electricity and the extent of increasing the electricity market.In this paper, a mathematical morphology and genetic algorithm based dynamic reactive power optimization method for distribution network is proposed.By means of constructing mathematical morphology filter, the binary image composed by allelic genes of chromosome is filtered and the problem that deals with the action times of voltage regulating devices for compensation is turned into filtering problem of discrete binary image.With further automate scheduling, distribution automation and unmanned substation reactive power optimization of distribution line running made an urgent request.Reactive power optimization can improve the voltage passing rate, increasing the reliability of the system, the power quality, and the system runs the security and economy of the perfect combination, very broad application prospects.

Probabilistic scheduling of a comprehensive energy hub integrated with renewable energy sources considering the correlation between uncertain variables

The paper presents a new method for allocation of losses in distribution networks (DN) with dispersed generation (DG) is presented. The method uses the power summation method, and it is based on the branch oriented approach and it establishes direct relationship between losses in each branch of the network and injected active and reactive power in the nodes. Active and reactive power at ending node of each branch of the network is decomposed as a sum of all injected power in nodes plus losses in the branches supplied by the branch. Allocation of crossed terms of active and reactive power is performed using quadratic allocation of crossed terms. Dispersed generators in the summation process are treated as negative active and reactive power injections, while load injected active and reactive power are considered positive. Results of the application of the method on 32-node test system are presented and discussed. (8 pages)

The penetration of renewable energy sources (RESs) in the electrical power system has increased significantly over the past years due to increasing global concern about climate change. However, integrating RESs into the power market is highly problematic. The output of RESs such as wind turbines (WTs) and photovoltaics (PVs) is highly uncertain. Their correlation with load demand is not always guaranteed, which compromises system reliability. Distributed energy resources (DERs), especially demand response (DR) programs and energy storage systems (ESSs), are possible options to overcome these operational challenges under the virtual power plant (VPP) setting. This study investigates the impact of using a DR program and battery energy storage system (BESS) on the VPP’s internal electricity market, and also cost-minimization analysis from a utility viewpoint. Three different constrained optimal power flow (OPF) problems are solved such as base case, DR case, and BESS case to determine total incurred costs, locational marginal prices (LMPs), and generator commitments. A scenario tree approach is used to model the uncertainties associated with WTs, PVs, and load demand. The proposed model is investigated on a 14-bus distribution system. The simulation results obtained demonstrate a favorable impact of DR and a BESS on renewable operational challenges.

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

Large renewable power plants connected to the high-voltage network have the potential to make an important contribution to the grid's reactive power management. This is especially true when rather than using a predetermined Q characteristic, the system operator can control the power plant's reactive power output via a direct interface. However, the intermittent nature of the primary resources and today's reactive power requirements inhibit the permanent availability of reactive power from wind and photovoltaic (PV) power plants. This study shows that a synchronized, so-called symbiotic control of PV and wind power plants can vastly increase their capability of fulfilling reactive power demands. This is demonstrated by simulating the properties of a real PV and wind farm located in Germany. Furthermore, generating units coupled to the grid via power electronics have an even larger potential of providing reactive power when their P-Q characteristics are adapted. On the downside, this can lead to an undesired coupling of reactive and active power control in the grid. A symbiosis of wind farms and PV parks can once again improve this situation when smart power allocation methods are employed. An appropriate algorithm has been developed for this study and is tested on the above-mentioned simulation model.

Problem definition: The rapid expansion of distributed energy resources (DERs) is one of the most significant changes to electricity systems around the world. Examples of DERs include solar panels, electric storage, thermal storage, and combined heat and power plants. Because of the small supply capacities of these DERs, it is impractical for them to participate directly in the wholesale electricity market. We study in this paper the question of how to integrate these DER supplies into the electricity market, with the objective of achieving full market efficiency. Methodology/results: We study four aggregation models, where there is an aggregator who, with the knowledge of DERs’ utility functions and generations, procures electricity from DERs, and sells them in the wholesale market. In the first aggregation model, a profit-maximizing aggregator announces a differential two-part pricing policy to the DER owners. We show that this model preserves full market efficiency, that is, the social welfare achieved by this model is the same as that when DERs participate directly in the wholesale market. In the second aggregation model, the profit-seeking aggregator is forced to impose a uniform two-part pricing policy to prosumers from the same location, and we numerically show that there can be large efficiency loss. In the third (fourth) aggregation model, a uniform (semiuniform) two-part pricing policy is applied to DER owners, whereas the aggregator becomes fully regulated but is guaranteed nonnegative (positive) profit. It is shown that these models again achieve full market efficiency. Furthermore, we show that DER aggregation also leads to a reduction in the market power of conventional generators. Managerial implications: DER aggregation via profit-seeking and/or regulated aggregators has been investigated by California Independent System Operator and New York Independent System Operator, among others, and the recent Federal Energy Regulatory Commission Order No. 2222 paved the way for aggregators to bid in the wholesale market. Our four aggregation models may shed light on how DERs should be included in the wholesale electricity market. Funding: This work was supported by the King Fahd University of Petroleum and Minerals [Grant INML2106] and the National Science Foundation [Grant 1832230]. Supplemental Material: The online appendices are available at https://doi.org/10.1287/msom.2021.0539 .