With the advent of small‐scale heat and electricity producers in distribution energy systems, the interdependencies between energy carriers have been increased. Moreover, the rapid deployment of ...micro CHP, electric heat pumps, electricity‐to‐heat appliances etc., calls for new local market frameworks to be employed in distribution energy systems. In response, this paper presents a new energy market framework based on the concept of peer‐to‐peer negotiations to facilitate energy transactions between agents at the distribution level while addressing the interdependencies between different energy carriers. Moreover, linear optimization problems are proposed to investigate the optimal strategies of market participants with various configurations. These optimization problems not only obtain the optimum strategy of agents to participate in the day‐ahead peer‐to‐peer electricity market, the day‐ahead heat market, and gas distribution systems but also obtain their optimal operation scheduling for the entire next day. The numerical results successfully demonstrate the applicability and merits of the proposed market framework.
The rapid deployment of district heating systems in local energy markets and increasing the number of small‐scale heat producers along with the expansion of local electricity markets increase the ...need for a transaction framework to manage the transactions between local participants in both heat and electricity markets. This paper presents a peer‐to‐peer thermal energy transaction framework to manage the transactions between small‐scale heat prosumers. This framework enables small‐scale thermal energy producers and consumers to participate in the market as price maker agents. Moreover, the optimal strategy of heat market participants is determined by proposing a linear profit function for each agent. This optimization problem enables the agents to determine their optimal participation strategy in electricity and heat markets by addressing the interdependencies of electricity market, gas price, and heat market. The numerical results successfully demonstrate the benefits and applicability of the proposed framework.
Residential energy management (REM) program is a demand response (DR) tool that automatically manages energy consumption of controllable household appliances to improve the energy consumption profile ...of a house according to electricity price. REM intends not only to improve technical aspects of distribution systems but also motivate customers for active participation in DR programs. In this regard, this paper proposes a two-level REM framework. In the first level, each customer runs an optimization problem to minimize his payment cost and sends the desired operation scheduling of appliances and the payment cost to the system operator. In the second level, a multiobjective (MO) optimization framework is designed to improve technical characteristics of the distribution system such as total load demand deviation, given the least desired payment cost of each customer. The objective functions of this MO optimization structure are to minimize deviation of distribution system load and to minimize costs of modifying the desired scheduling of customers. The proposed algorithm is mathematically modeled and applied to the IEEE 34-node test feeder to prove its advantages for customers and system operators in comparison with the available REM strategies.
Recently, power system operators have initiated procurement of a new service in electricity markets named flexible ramping product (FRP). With the main goal of enhancing the grid flexibility, this ...product can provide a remarkable opportunity for an enhanced short-term profitability. Energy storage systems (ESSs) with high ramping capability can leverage their profitability when properly participating in this market. This study introduces a stochastic optimisation framework for participation of ESSs in the FRP market. The proposed model formulates the optimal bidding strategy of ESSs considering the real-time energy, flexible ramp-up and ramp-down marginal price signals and the associated uncertainties. In addition, as the market participants cannot directly submit bids for the FRP, the corresponding energy bidding adjustments required to award the proper FRP amounts are elaborated. The mathematical model is linearised and its application in real-time market is investigated. The proposed framework is numerically analysed through which its effectiveness on enhancing the ESS profitability in the real-time electricity markets is verified.
Due to the lack of data in active distribution networks, employing new accurate measurement devices like phasor measurement units (PMUs) and micro-PMUs with a high reporting rate becomes an ...inevitable choice for the future vision of distribution systems. As a result, different algorithms have been presented to optimally place PMUs cost-effectively based on the estimation errors of the distribution state estimation (DSE) results. However, any component failure in measurement devices or communication links between sending ends and monitoring system of the distribution management system can significantly affect the DSE results. In response, this study introduces the reliability of satisfying accuracy constraints (RSACs) as an important requirement in the DSE problem. This reliability index along with the estimation errors of the DSE results are then used as two performance indices for determining the optimal number and location (configuration) of PMUs. Finally, the performance of the proposed algorithm in comparison with traditional approaches in different topologies and operating conditions of two considered ADNs is evaluated. The results proved that employing the RSACs in the optimal PMU placement problems leads to a PMU configuration with the optimum RSACs and also the cost and latency of the communication system between all configurations which have the same measurement cost and satisfy accuracy constraints of DSE results.
Unpredictable occurrence of natural disasters in modern power systems has significantly increased the attentions to the outage management of multi‐microgrid (MMG) systems. In this regard, a ...multi‐objective two‐stage outage management scheme is presented in this paper to protect undamaged microgrids (MGs) against load curtailment and minimize the curtailed loads simultaneously. Considering the importance of power system economic, this scheme is designed in a privacy‐preserved transactive energy (TE) market and enables all MGs to participate in outage management voluntarily. In detail, a DC optimization is autonomously operated in the first stage in each MG to supply its demand loads. Then, the second stage is designed to exchange the surplus power of the last stage with the damaged MGs. These voluntary power transactions are pre‐specified in contracts, adjusted between each MG and distributed system operator (DSO). Moreover, in this stage, the ADMM algorithm based on DC‐OPF has prepared a privacy protection platform and proved the results’ accuracy. The presented test grid is the IEEE 34‐node test system and the numeric results demonstrate the effectiveness of the proposed multi‐objective scheme.
Smart grids help local distribution companies (LDCs) facilitate the communication between grid operators and residential prosumers. While the prosumers are striving to optimize their daily load ...profile by home energy management systems (HEMSs) deployment, the LDCs attempt to enhance the operation of the grid in an efficient way and decrease network losses. This paper attempts to develop a new bi‐level probabilistic optimization framework wherein an HEMS optimizes its respective daily load profile, and determines its flexibility provision, which is communicated to an LDC. In the proposed framework, a decentralized approach is used to achieve the flexibility product, which is the modulation of energy, through the incentive‐based demand response (DR) programs. Finally, the LDC applies the prosumer's flexibility' offers to optimize its operational performance. The two‐point estimate method (2PEM) is employed to model the uncertainties. The applicability of the framework is demonstrated by applying it to a system with one residential feeder.
The concept of flexibility is defined as the power systems’ ability to effectively respond to changes in power generation and demand profiles to maintain the supply–demand balance. However, the ...inherent flexibility margins required for successful operation have been recently challenged by the unprecedented arrival of uncertainties, driven by constantly changing demand, failure of conventional units, and the intermittent outputs of renewable energy sources (RES). Tackling these challenges, energy storage systems (ESS) as one important player of the new power grids can enhance the system flexibility. It, therefore, calls for an efficient planning procedure to ensure flexibility margins by considering ESS's role in modern power systems. This paper proposes a novel mixed integer linear programming (MILP) model for transmission expansion planning (TEP) framework taking into account the role of compressed air energy storage (CAES) integration on improvements in system flexibility. The proposed framework is housed with a quantitative metric of grid‐scale system flexibility, while a new offline repetitive mechanism is suggested to account for the N − 1 reliability criterion. The model is applied to different test systems, where the numerical results demonstrate the impacts of CAES units on system flexibility, investment plans, and the total costs.
This paper presents a two‐stage adaptive robust optimization framework for day‐ahead energy and intra‐day flexibility self‐scheduling of a technical virtual power plant (TVPP). The TVPP exploits ...diverse distributed energy resources’ (DERs) flexibility capabilities in order to offer flexibility services to wholesale flexibility market as well as preserving the distribution network's operational constraints in the presence of DER uncertainties. The TVPP aims at maximizing its profit in energy and flexibility markets considering the worst‐case uncertainty realization. In the proposed framework, the first stage models the TVPP's participation strategy in day‐ahead energy market and determines the DERs’ optimal energy dispatch. The second stage addresses the TVPP's strategy in intra‐day flexibility market to determine the DERs’ optimal flexibility capability provision by adjusting their energy dispatch for the worst‐case realization of uncertainties. The uncertainty characteristics associated with photovoltaic units, electric vehicles, heating, ventilation and air conditioning systems, and other responsive loads as well as the transmission network's flexibility capability requests are considered using an adaptive robust approach. Adopting the duality theory, the model is formulated as a mixed‐integer linear programming problem and is solved using a column‐and‐constraint generation algorithm. This model is implemented on a standard test system and the model effectiveness is demonstrated.
This paper presents a two‐stage adaptive robust optimization framework for a technical virtual power plant (TVPP) to participate in day‐ahead energy and intra‐day flexibility markets. The TVPP exploits flexibility capabilities of diverse distributed energy resources (DERs) to satisfy the distribution network operational constraints in the presence of uncertainties as well as offering flexibility to meet the transmission network's flexibility requests. In this model, the worst‐case realization of uncertainties associated with diverse DERs as well as the transmission system operator's requested flexibility is considered to determine the DERs' optimal flexibility capability provision by adjusting their output power in flexibility market.
Optimal placement of switches can play a key role in providing resilience to power distribution systems against major faults caused by natural disasters. This study presents a resilience-based ...framework for optimal switch placement in distribution systems being consistent with the expansion plans of distributed generation units. At first, the impact of hurricanes on distribution system components is modelled using the geographic information system of distribution grid and the strength of components against extreme weather-related events. Then, a new resiliency index is proposed to assess the resilience of distribution grids. This index is involved in a mathematical model of the switch placement problem and the obtained formulation is modelled as a mixed integer linear programming optimisation problem. The presented framework is implemented on two test systems, i.e. an illustrative test system and Bus 4 of the Roy Billinton test system. The results prove the effectiveness of this approach to improving the resiliency of distribution systems.
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