Micro-economic Analysis of the Physical Constrained Markets: Game Theory Application to Competitive Electricity Markets

Competition has been introduced in the electricity markets with the goal of reducing prices and improving efficiency. The basic idea which stays behind this choice is that, in competitive markets, a greater quantity of the good is exchanged at a lower and a lower price, leading to higher market efficiency. Electricity markets are pretty different from other commodities mainly due to the physical constraints related to the network structure that may impact the market performance. The network structure of the system on which the economic transactions need to be undertaken poses strict physical and operational constraints. Strategic interactions among producers that game the market with the objective of maximizing their producer surplus must be taken into account when modeling competitive electricity markets. The physical constraints, specific of the electricity markets, provide additional opportunity of gaming to the market players. Game theory provides a tool to model such a context. This paper discussed the application of game theory to physical constrained electricity markets with the goal of providing tools for assessing the market performance and pinpointing the critical network constraints that may impact the market efficiency. The basic models of game theory specifically designed to represent the electricity markets will be presented. IEEE30 bus test system of the constrained electricity market will be discussed to show the network impacts on the market performances in presence of strategic bidding behavior of the producers.Comment: Accepted for publication in the European Journal of Physics B. Presented at the Int. Conf. NEXT-SigmaPhi, 13-18 August 2005, Cret

Big data analytics in smart grids: a review

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Impact of Wind and Solar Generation on the Italian Zonal Electricity Price

This paper assesses the impact of increasing wind and solar power generation on zonal market prices in the Italian electricity market from 2015 to 2019, employing a multivariate regression model. A significant aspect to be considered is how the additional wind and solar generation brings changes in the inter-zonal export and import flows. We constructed a zonal dataset consisting of electricity price, demand, wind and solar generation, net input flow, and gas price. In the first and second steps of this study, the impact of additional wind and solar generation that is distributed across zonal borders is calculated separately based on an empirical approach. Then, the Merit Order Effect of the intermittent renewable energy sources is quantified in every six geographical zones of the Italian day-ahead market. The results generated by the multivariate regression model reveal that increasing wind and solar generation decreases the daily zonal electricity price. Therefore, the Merit Order Effect in each zonal market is confirmed. These findings also suggest that the Italian electricity market operator can reduce the National Single Price by accelerating wind and solar generation development. Moreover, these results allow to generate knowledge advantageous for decision-makers and market planners to predict the future market structure

RISK ASSESSMENT OF MALICIOUS ATTACKS AGAINST POWER SYSTEMS

The new scenarios of malicious attack prompt for their deeper consideration and mainly when critical systems are at stake. In this framework, infrastructural systems, including power systems, represent a possible target due to the huge impact they can have on society. Malicious attacks are different in their nature from other more traditional cause of threats to power system, since they embed a strategic interaction between the attacker and the defender (characteristics that cannot be found in natural events or systemic failures). This difference has not been systematically analyzed by the existent literature. In this respect, new approaches and tools are needed. This paper presents a mixed-strategy game-theory model able to capture the strategic interactions between malicious agents that may be willing to attack power systems and the system operators, with its related bodies, that are in charge of defending them. At the game equilibrium, the different strategies of the two players, in terms of attacking/protecting the critical elements of the systems, can be obtained. The information about the attack probability to various elements can be used to assess the risk associated with each of them, and the efficiency of defense resource allocation is evidenced in terms of the corresponding risk. Reference defense plans related to the online defense action and the defense action with a time delay can be obtained according to their respective various time constraints. Moreover, risk sensitivity to the defense/attack-resource variation is also analyzed. The model is applied to a standard IEEE RTS-96 test system for illustrative purpose and, on the basis of that system, some peculiar aspects of the malicious attacks are pointed ou

A three‐stage stochastic planning model for enhancing the resilience of distribution systems with microgrid formation strategy

In recent years, severe outages caused by natural disasters such as hurricanes have highlighted the importance of boosting the resilience level of distribution systems. However, due to the uncertain characteristics of natural disasters and loads, there exists a research gap in the selection of optimal planning strategies coupled with provisional microgrid (MG) formation. For this purpose, this study proposes a novel three‐stage stochastic planning model considering the planning step and emergency response step. In the first stage, the decisions on line hardening and Distributed Generation (DG) placement are made with the aim of maximising the distribution system resilience. Then, in the second stage, the line outage uncertainty is imposed via the given scenarios to form the provisional MGs based on a master‐slave control technique. In addition, the non‐anticipativity constraints are presented to guarantee that the MG formation decision is based on the line damage uncertainty. Last, with the realisation of the load demand, the cost of load shedding in each provisional MG is minimised based on a demand‐side management program. The proposed method can consider the step‐by‐step uncertainty realisation that is near to the reality in MG formation strategy. Two standard distribution systems are utilised to validate the correctness and effectiveness of the presented model

Allowing Large Penetration of Concentrated RES in Europe and North Africa via a Hybrid HVAC-HVDC Grid

Renewable energy sources (RESs) and electricity demand are not evenly distributed geographically across Europe. Thus, harvesting the wind energy from the north and solar energy from the south and delivering them to the demand in central Europe is a more viable solution. However, the present High-voltage alternating current (HVAC) transmission grids have been sometimes congested; thus, High-voltage direct current (HVDC) provides another possibility along the existing HVAC infrastructure. In this paper, we propose a hybrid HVAC-HVDC grid, allowing a large penetration of concentrated RES in Europe and North Africa. More specifically, the HVDC network is constructed to transfer wind and hydro electricity from northwestern Europe and solar electricity from north Africa, while the HVAC network is used to distribute electricity within each country or among adjacent areas. To quantitatively evaluate the feasibility and relevant performances, multiple dimensions of indicators are designed. Employing several European energy scenarios up to 2050, the performances of the proposed HVAC-HVDC infrastructure are analyzed and compared. The calculation results show that compared with the pure HVAC grid, the integrated HVAC-HVDC grid can significantly reduce greenhouse gas emissions and pollutants, leading to a further reduction in the number of deaths from air pollution. In addition, the HVAC-HVDC grids can accommodate a higher penetration of RES without causing infeasible power flows

Frequency Models and Control in Normal Operation: the Sardinia Case Study

Frequency signal is an indicator of the unbalance between the power generation and the load demand. Frequency power reserves in different timeframes are commonly deployed to keep this signal inside strict ranges around the nominal value. Reserves must be carefully dimensioned, and their dynamic performance correctly evaluated to enhance system security. This paper proposes a novel methodology to reproduce frequency fluctuations of entire days and to compute the power reserves activation dynamics by using a two-step process. Firstly, given a real power system frequency signal, a reverse aggregate model provides the unbalance in the system. Secondly, this unbalance is used to recreate and validate the original frequency signal by a forward aggregate model. After this procedure, Battery Energy Storage Systems (BESSs) are added and their impact on the frequency signal is quantified, in terms of different control schemes. The proposed method is tested in the real case of the Sardinian power system. Results show that this methodology can provide accurate estimation of the unbalance, frequency and reserves in the system, giving an understanding of the BESS impact on the frequency control

Energy and Complexity

Sustainable energy systems are complex sociotechnical systems with a social network of many players that “together” develop, operate, and maintain the technical infrastructure. No single player controls the system, but their actions are coordinated through a range of institutions—informal and formal rules—and regulations. As the control is distributed among actors, the overall system behaviour (at different time scales) emerges from operating practices and characteristics, from(dis)investment decisions, and fromother aspects of the players’ strategies

An Extended Approach to the Evaluation of Energy Storage Systems: A Case Study of Li-Ion Batteries

Energy storage technologies can act as flexibility sources for supporting the energy tran- sition, enabling the decarbonisation of the grid service provision and the active engagement of the customers (both prosumers and consumers), opening for them new business opportunities. Within storage technologies, Lithium-ion (Li-ion) batteries represent an interesting solution for dealing with the majority of these services. In this context, this study addresses an evaluation of economic, environ- mental and geopolitical risks with reference to the critical raw materials used in the manufacturing of Lithium Iron Phosphate (LFP) Li-ion batteries. The assessment entailes grid and prosumer services that these batteries can provide. The exploited economic indicator is the Levelised Cost of Storage, whereas six environmental indicators are used for environmental impact estimation. Cycle stages accounted for in the analysis are the manufacturing and use phases. Finally, the evaluation of the impact of critical raw materials is performed by deploying a Supply Risk indicator, which is instead assessed considering every single material and the overall risk for the battery. High-risk materials are represented by Graphite and Phosphorous. Results denote that, for each service, the number of cycles and the discharge duration are pivotal to make the investment economically and environmentally sustainable. The reduction in the Net Import Reliance, as well as the increase in the Recycling Rate, could sensibly reduce the risk associated with battery raw material

Techno-economic impacts of automatic undervoltage load shedding under emergency

Different schemes for voltage control under emergency are adopted in different jurisdictions around the world. While some features, such as Automatic Voltage Regulation (AVR), are common in all countries, for what concerns undervoltage load shedding (UVLS), to contrast voltage instability or collapse, different schemes are adopted. Most US transmission system operators (TSOs) adopt automatic UVLS schemes, with different capabilities and settings while TSOs in EU usually do not implement automatic UVLS but leave the decisions to the control room operators. The two options may lead to different impacts in terms of trajectory and final status of the transmission grid under emergency, with different unserved energy. In this paper we analyze the impacts from a technical and economic perspective, modeling the grid behavior with different UVLS schemes (none, manual and automatic). The comparison between the different schemes is done resorting to the Incident Response System (IRS), a software tool developed by the authors in the EU-FP7 SESAME project. An illustrative example to a realistic test case is presented and discussed. This paper shows that automatic UVLS is superior to Manual UVLS, from both technical and economic point of view, due to the fast evolution of voltage collapse phenomena and insufficient time for system operators' manual reaction. The benefits of the scheme involving the automatic UVLS can be then compared with the investment costs of equipping the network with those devices