Blockchain Papers

AmirAli Nazari, Reza Keypour

No abstract is available for this record.

Saeid Esmaeili, Shahram Jadid, Amjad Anvari‐Moghaddam, Josep M. Guerrero

In this paper, optimal operational scheduling in smart microgrids in conjunction with hourly reconfiguration is investigated. The optimization problem has the objective function of minimizing total costs including the total loss, cost of bilateral contracts with fuel cell and photovoltaic owners, switching cost, and cost of exchanged power with wholesale market. To prevent the aged and risky switches from frequent switching actions over a short-term scheduling, a new index for switching action based on the remotely-controlled switch (RCS) ages and critical locations in the network is defined. The proposed optimization model is non-convex and non-linear, which is transformed into a Mixed-Integer Linear Programming (MILP) problem to be solvable with conventional solvers. The satisfactory performance of the proposed model is demonstrated on the 84-bus Taiwan power company system.

Jaysson Guerrero, Archie C. Chapman, Gregor Verbič

The increasing uptake of distributed energy resources (DERs) in distribution systems and the rapid advance of technology have established new scenarios in the operation of low-voltage networks. In particular, recent trends in cryptocurrencies and blockchain have led to a proliferation of peer-to-peer (P2P) energy trading schemes, which allow the exchange of energy between the neighbors without any intervention of a conventional intermediary in the transactions. Nevertheless, far too little attention has been paid to the technical constraints of the network under this scenario. A major challenge to implementing P2P energy trading is that of ensuring that network constraints are not violated during the energy exchange. This paper proposes a methodology based on sensitivity analysis to assess the impact of P2P transactions on the network and to guarantee an exchange of energy that does not violate network constraints. The proposed method is tested on a typical UK low-voltage network. The results show that our method ensures that energy is exchanged between users under the P2P scheme without violating the network constraints, and that users can still capture the economic benefits of the P2P architecture.

Armin Ghasem Azar, Mohsen Afsharchi, Mansoor Davoodi, Bahram Sadeghi Bigham

No abstract is available for this record.

Hamidreza Arasteh, Vahid Vahidinasab, Mohammad Sadegh Sepasian, Jamshid Aghaei

The incorporation of the reconfiguration into the expansion planning of smart distribution networks is addressed in this paper, in which the potential of distributed energy resources and demand response (DR) are modeled. The system of systems (SoS) architecture is employed to model the strategy of a distribution company (DISCO), a private investor (PI), and a DR provider (DRP). The SoS is an efficient modeling architecture to model the behavior of independent and autonomous systems with distinct objective functions who are able to share some data and work together. The aim of the DISCO is to upgrade the system with the optimal cost and reliability, whereas the PI and DRP want to maximize their profit. The DISCO should try to persuade the PI to install DGs (Distributed generations) by offering the guaranteed purchasing prices. Furthermore, the DRP is a market player who can negotiate with the DISCO to sign a contract to sell the purchased DR capacities from the customers. The uncertainties of the DISCO problem is handled by using the chance-constraint method, but the PI and DRP use the conditional value at risk method to model their uncertainties. Finally, to solve the proposed model, the multiobjective optimization algorithm is employed.

Majed A. Alotaibi, M.M.A. Salama

The deployment of smart grids has facilitated the integration of a variety of investor assets into power distribution systems, giving rise to the consequent necessity for positive and active interaction between those investors and local distribution companies (LDCs). This paper proposes a novel incentive-based distribution system expansion planning model that enables an LDC and distributed generation (DG) investors to work in a collaborative way for their mutual benefit. Using the proposed model, the LDC would establish a bus-wise incentive program based on long-term contracts, which would encourage DG investors to integrate their projects at specific system buses that would benefit both parties. The model guarantees that the LDC will incur minimum expansion and operation costs while concurrently ensuring the feasibility of DG investors' projects. To derive appropriate incentives for each project, the model enforces several economic metrics including internal rate of return, profit investment ratio, and discounted payback period. All investment plans committed to by the LDC and the DG investors for the full extent of the planning period are then coordinated accordingly. Several linearization approaches are applied to convert the proposed model into an MILP model. The intermittent nature of both system demand and wind- and PV-based DG output power is handled probabilistically, and a number of DG technologies are taken into account. Case study results have demonstrated the value of the proposed model.

Liuchen Chang, Xi Wang, Meiqin Mao

Distributed energy resources (DERs) include distributed generations (DGs), distributed energy storages (DESs), and the demand response resources (DRRs). With the increasing penetration of DERs in distribution network, more and more users change from power consumers to prosumers which have great influences on distribution network as well as generate new business models on the demand side. Based on the emerging change of the power system, this paper proposes a transactive energy scheme (TES) based on multi-factor evaluation and contract net protocol to determine energy trading strategies among prosumers to realize economic and stable operation of distribution network. In the proposed TES, a TE market is built in the deregulatory retail power market. Power consumers, smart homes, industrial parks, or virtual power plants with DERs take the initiative as transactive nodes (TNs), and the peer to peer transactions among TNs in TE market can be carried out based on the multi-factor evaluation and contract protocol. When a TN cannot meet its own electricity demand, it launches the contract net to other TNs, requests to carry on the electric energy transaction, and determines the selected TNs according to the multi-factor evaluation. The simulation results show compared with the traditional electricity business model, the market participants who use the proposed TES can gain more economic benefits as well as protecting their own privacy.

Junjie Qin, Ram Rajagopal, Pravin Varaiya

A coordinated trading process is proposed as a design for an electricity market with significant uncertainty, perhaps from renewables. In this process, groups of agents propose to the system operator (SO) a contingent buy and sell trade that is balanced, i.e. the sum of demand bids and the sum of supply bids are equal. The SO accepts the proposed trade if no network constraint is violated or curtails it until no violation occurs. Each proposed trade is accepted or curtailed as it is presented. The SO also provides guidance to help future proposed trades meet network constraints. The SO does not set prices, and there is no requirement that different trades occur simultaneously or clear at uniform prices. Indeed, there is no price-setting mechanism. However, if participants exploit opportunities for gain, the trading process will lead to an efficient allocation of energy and to the discovery of locational marginal prices (LMPs). The great flexibility in the proposed trading process and the low communication and control burden on the SO may make the process suitable for coordinating producers and consumers in the distribution system.

Tohid Sattarpour, Daryoosh Nazarpour, Sajjad Golshannavaz, Pierluigi Siano

No abstract is available for this record.

Ariana Ramos, Cedric De Jonghe, Virginia Gómez, Ronnie Belmans

No abstract is available for this record.

H. S. V. S. Kumar Nunna, Amit Mohan Saklani, Anudeep Sesetti, Swathi Battula · 6 authors

No abstract is available for this record.

Masood Parvania, Mahmud Fotuhi‐Firuzabad, Mohammad Shahidehpour

Advancements in smart grid technologies have made it possible to apply various options and strategies for the optimization of demand response (DR) in electricity markets. DR aggregation would accumulate potential DR schedules and constraints offered by small- and medium-sized customers for the participation in wholesale electricity markets. Despite various advantages offered by the hourly DR in electricity markets, practical market tools that can optimize the economic options available to DR aggregators and market participants are not readily attainable. In this context, this paper presents an optimization framework for the DR aggregation in wholesale electricity markets. The proposed study focuses on the modeling strategies for energy markets. In the proposed model, DR aggregators offer customers various contracts for load curtailment, load shifting, utilization of onsite generation, and energy storage systems as possible strategies for hourly load reductions. The aggregation of DR contracts is considered in the proposed price-based self-scheduling optimization model to determine optimal DR schedules for participants in day-ahead energy markets. The proposed model is examined on a sample DR aggregator and the numerical results are discussed in the paper.

Paul L. Joskow

This paper focuses on efforts to build what policymakers call the “smart grid,” involving 1) improved remote monitoring and automatic and remote control of facilities in high-voltage electricity transmission networks; 2) improved remote monitoring, two-way communications, and automatic and remote control of local distribution networks; and 3) installation of “smart” metering and associated communications capabilities on customer premises so that customers can receive real-time price information and/or take advantage of opportunities to contract with their retail supplier to manage the consumer's electricity demands remotely in response to wholesale prices and network congestion. I examine the opportunities, challenges, and uncertainties associated with investments in “smart grid” technologies. I discuss some basic electricity supply and demand, pricing, and physical network attributes that are critical for understanding the opportunities and challenges associated with expanding deployment of smart grid technologies. Then I cover issues associated with the deployment of these technologies at the high voltage transmission, local distribution, and end-use metering levels.

Pedro Oliveira, Zita Vale, Hugo Morais, Tiago Pinto · 5 authors

No abstract is available for this record.

Christine Brandstätt, Gert Brunekreeft, Nele Friedrichsen

No abstract is available for this record.

Dionysios Aliprantis, Scott Penick, Leigh Tesfatsion, Huan Zhao

Our research team is developing an agent-based test bed for the integrated study of retail and wholesale power markets operating over transmission and distribution networks with smart-grid functionality. This test bed seams together two existing test beds, the AMES Wholesale Power Market Test Bed and the GridLAB-D distribution platform. As a first step, we have designed an integrated retail/wholesale market module specifically based on the ERCOT (Texas) energy region, and we are using simplified versions of this module to study potential retail consumer response to real-time-pricing contracts supported by advanced metering. This study reports on the latter work.

Ross Baldick

In this paper, a property rights model for electric transmission is proposed and its properties analyzed. The proposed rights, called "border flow rights," support financial hedging of transmission risk and merchant transmission expansion through associated financial rights, called "contracts for differences of differences." These financial rights allow for forward trading of both energy and transmission by a unified exchange, avoiding the bifurcation in current markets between decentralized long-term energy trading and centralized long-term transmission trading. Such long-term trading can help to support the financing of both generation and transmission assets. We consider incentive properties of such a right in the absence of lumpiness, economies of scale, and market power.