According to the feed-in tariff for encouraging local consumption of photovoltaic (PV) energy, the energy sharing among neighboring PV prosumers in the microgrid could be more economical than the independent operation of prosumers. For microgrids of peer-to-peer PV prosumers, an energy-sharing model with price-based demand response is proposed. First, a dynamical internal pricing model is formulated for the operation of energy-sharing zone, which is defined based on the supply and demand ratio (SDR) of shared PV energy. Moreover, considering the energy consumption flexibility of prosumers, an equivalent cost model is designed in terms of economic cost and users’ willingness. As the internal prices are coupled with SDR in the microgrid, the algorithm and implementation method for solving the model is designed on a distributed iterative way. Finally, through a practical case study, the effectiveness of the method is verified in terms of saving PV prosumers’ costs and improving the sharing of the PV energy.

Energy-Sharing Model With Price-Based Demand Response for Microgrids of Peer-to-Peer Prosumers

Power networks are undergoing a fundamental transition, with traditionally passive consumers becoming ‘prosumers’ — proactive consumers with distributed energy resources, actively managing their consumption, production and storage of energy. A key question that remains unresolved is: how can we incentivize coordination between vast numbers of distributed energy resources, each with different owners and characteristics? Virtual power plants and peer-to-peer (P2P) energy trading offer different sources of value to prosumers and the power network, and have been proposed as different potential structures for future prosumer electricity markets. In this Perspective, we argue they can be combined to capture the benefits of both. We thus propose the concept of the federated power plant, a virtual power plant formed through P2P transactions between self-organizing prosumers. This addresses social, institutional and economic issues faced by top-down strategies for coordinating virtual power plants, while unlocking additional value for P2P energy trading. The rise of prosumers has led to creation of virtual power plants and peer-to-peer trading to help manage a diverse and distributed array of energy sources. This Perspective proposes the federated power plant, which combines these concepts to meet some of their individual challenges and offer new value.

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Using peer-to-peer energy-trading platforms to incentivize prosumers to form federated power plants

Due to different viewpoints, procedures, limitations, and objectives, the scheduling problem of distributed energy resources (DERs) is a very important issue in power systems. This problem can be solved by considering different frameworks. Microgrids and Virtual Power Plants (VPPs) are two famous and suitable concepts by which this problem is solved within their frameworks. Each of these two solutions has its own special significance and may be employed for different purposes. Therefore, it is necessary to assess and review papers and literature in this field. In this paper, the scheduling problem of DERs is studied from various aspects such as modeling techniques, solving methods, reliability, emission, uncertainty, stability, demand response (DR), and multi-objective standpoint in the microgrid and VPP frameworks. This review enables researchers with different points of view to look for possible applications in the area of microgrid and VPP scheduling.

A comprehensive review on microgrid and virtual power plant concepts employed for distributed energy resources scheduling in power systems

For microgrids with photovoltaic (PV) prosumers, the effective energy sharing management (ESM) is important for the operation. In this paper, a Stackelberg game approach for ESM is proposed. First, according to feed-in-tariff of PV energy, a system model of ESM is introduced, which includes the profit model of microgrid operator (MGO) and the utility model of PV prosumers. Moreover, an hour-ahead optimal pricing model of ESM is proposed. The model is designed based on Stackelberg game, where the MGO acts as the leader and all participating prosumers are considered as the followers. With the proof of equilibrium and uniqueness of the Stackelberg equilibrium, the MGO is obligated to coordinate the sharing of PV energy with maximization of the own profit, while the prosumers are autonomous to maximize their utilities with demand response availability. Finally, a billing mechanism is designed to deal with the uncertainty of PV energy and load consumption. By using the collected data from realistic PV-roofed buildings, the effectiveness of the model is verified in terms of the profit of MGO, the utilities of prosumers, and the net energy of the microgrid.

Energy Sharing Management for Microgrids With PV Prosumers: A Stackelberg Game Approach

Incentive-based demand response for smart grid with reinforcement learning and deep neural network

In modern power systems and electricity markets, demand response (DR) programs play an important role enabling the mitigation of critical load periods or price-peaking scenarios, thereby improving system reliability. Price fluctuations, in forward or real-time markets, can be an effective price-based DR mechanism for curtailing or shifting load. However, using dynamic pricing to achieve a desired load profile requires both an accurate demand forecast and knowledge of the price elasticity of demand, which is notoriously difficult to estimate. The limited accuracy of these parameter estimates is the main source of uncertainty limiting appropriate DR implementation. In this paper, we present a novel DR scheme that avoids the need to predict the price elasticity of demand or demand forecast, yet still delivers a significant DR. This is done based on the consumers' submissions of candidate load profiles ranked in the preference order. The load aggregator then performs the final selection of individual load profiles subject to the total system cost minimization. Additionally, the proposed DR model incorporates a fair billing mechanism that is enhanced with an ex post consumer performance tracking scheme implemented in a context of a virtual power plant aggregating load and generation units.

A Novel Demand Response Model with an Application for a Virtual Power Plant

Accumulation of dust on PV modules is one of the major issues limiting the technology adoption in many regions of the world, especially the in Middle East. Even though the solar irradiation is relatively high, the dusty environment is one of the key factors limiting a larger scale implementation of such renewable energy sources. In this paper we present a new approach for optimizing operation of a PV plant in terms of dust assessment and management. The proposed method includes analysis of PV modules' surfaces using an image processing technique. The acquisition of images is assumed to be performed by aerial robotics (i.e. drones) equipped with high resolution cameras. The key novelty of this work is the algorithm used for dust detection and the method used for assessing the level of dust on a given surface. This is done by using MATLAB image processing tool box. In this paper, the concept and methodology are presented where the algorithm is validated against electrical measurement where it showed a variation of 5% to 5.5% of detection variation based on the method used in the detection algorithm.

Assessing dust on PV modules using image processing techniques

Deregulation of electricity markets has enabled a flexible and efficient framework for generation companies to trade electricity in a competitive environment. Deregulation coupled with environmental concerns, has caused the presence of more small and medium scale renewable generation units distributed throughout the grid. The variable nature of renewable energy sources and the lack of their centralized monitoring create challenges for system operation. The idea of aggregating distributed energy resources is emerging through the concept of virtual power plants that improve generator controllability and visibility to the system operator. In this paper we present a market framework enabling a virtual power plant to participate in wholesale energy markets by offering combined services of generation and demand response. Internal and external trades are enabled by introduction of a new market structure. The formulated mathematical model captures the purposed market interactions between participants optimizing a VPP's bidding strategy in a day-ahead market environment. The developed models maximize the virtual power plant profit with respect to the forecasted power outputs of variable generation units and provide optimal demand response pricing schemes.

Optimal demand response bidding and pricing mechanism: Application for a virtual power plant

The penetration of distributed energy resources keeps increasing in most of electricity markets, becoming an essential part of smart grid systems. This, along with advancements in power converters and control systems, led to formation of various aggregation mechanisms, such as Virtual Power Plants (VPP) or demand response (DR) aggregators, enabling participation of small and medium scale distributed energy resources (DER) in electricity markets. Such mechanisms typically entail control of DER assets at specified time periods to provide grid services such as peak shaving. However, the transparency of operations when controlling the aggregated DERs is a risk from the asset owner's perspective and may lead to various types of disputes with the aggregator or operator. In order to tackle this issue, we have developed a blockchain-based mechanism that handles all transactions within a VPP on a distributed data ledger, enabling full transparency of the system. The blockchain system is integrated with an actual VPP setup with a total aggregated size of 1.8MWs composed of renewables, energy storage systems and controllable loads. The proposed mechanism contributes to grid digitalization and enables new applications in power systems, incentivizing larger penetration of DERs and their participation in ancillary services.

Blockchain-Integrated Virtual Power Plant Demonstration

Large penetration of various types of distributed energy resources and new requirements in electricity markets, have facilitated creation of sophisticated distributed energy resource aggregation systems for providing grid services. Aggregators such as Virtual Power Plants enable participation of small- and medium-scale distributed energy resources in electricity markets, interacting with grid operators to collectively provide ancillary power and energy services. These interactions between grid operator, Virtual Power Plants operator and distributed energy resources are complex both in terms of contractual agreements and provision of services. On all layers, accurate tracking of distributed energy resource usage and execution of contracts is required for establishing trust between transacting participants. Digitalisation and automation of processes such as control of distributed energy resources, verification and payouts for services will add value for solving complexity of dealing with multiple parties in a Virtual Power Plants aggregation model. The authors present a blockchain-integrated Virtual Power Plants system that enables full automation of distributed energy resource controls through smart contracts, digital trust between participants and immediate payouts for services. Effectiveness of the developed blockchain mechanism is demonstrated on a pilot Virtual Power Plants system comprising distributed energy storage systems, renewables, EV charging stations and loads with a total size of 1.8 MWs. Additionally, we propose a new mechanism for managing renewable energy curtailments through blockchain. 

Ashot Mnatsakanyan

Papers

A Novel Demand Response Model with an Application for a Virtual Power Plant

Assessing dust on PV modules using image processing techniques

Optimal demand response bidding and pricing mechanism: Application for a virtual power plant

Blockchain-Integrated Virtual Power Plant Demonstration

Blockchain mediated virtual power plant: From concept to demonstration