Optimal generation and reserve dispatch in a multi-area competitive market using a hybrid direct search method

With restructuring of the power industry, competitive bidding for energy and ancillary services are increasingly recognized as an important part of electricity markets. It is desirable to optimize not only the generator’s bid prices for energy and for providing minimized ancillary services but also the transmission congestion costs. In this paper, a hybrid approach of combining sequential dispatch with a direct search method is developed to deal with the multi-product and multi-area electricity market dispatch problem. The hybrid direct search method (HDSM) incorporates sequential dispatch into the direct search method to facilitate economic sharing of generation and reserve across areas and to minimize the total market cost in a multi-area competitive electricity market. The effects of tie line congestion and area spinning reserve requirement are also consistently reflected in the marginal price in each area. Numerical experiments are included to understand the various constraints in the market cost analysis and to provide valuable information for market participants in a pool oriented electricity market.     

Electricity market models and RES integration: The Greek case

This paper presents an extensive analysis of the Greek electricity market for the next 7-year period (2014–2020) based on an hour-by-hour simulation considering five different RES technologies, namely wind, PV, small hydro, biomass and CHP with emphasis on PV integration. The impact of RES penetration on the electricity market operation is evaluated under two different models regarding the organization of the Greek wholesale day-ahead electricity market: a mandatory power pool for year 2014 (current market design) and a power exchange for the period 2015–2020 (Target Model). An integrated software tool is used for the simulation of the current and the future day-ahead market clearing algorithm of the Greek wholesale electricity market. Simulation results indicate the impact of the anticipated large-scale RES integration, in conjunction with each market model, on specific indicators of the Greek electricity market in the long-term.     

Congestion management enhancing transient stability of power systems

In a competitive electricity market, where market parties try to maximize their profits, it is necessary to keep an acceptable level of power system security to retain the continuity of electricity services to customers at a reasonable cost. Congestion in a power system is turned up due to network limits. After relieving congestion, the network may be operated with a reduced transient stability margin because of increasing the contribution of risky participants. In this paper, a novel congestion management method based on a new transient stability criterion is introduced. Using the sensitivity of corrected transient stability margin with respect to generations and demands, the proposed method so alleviates the congestion that the network can more retain its transient security compared with earlier methods. The proposed transient stability index is constructed considering the likelihood of credible faults. Indeed, market parties participate by their security-effective bids rather than raw bids. Results of testing the proposed method along with the earlier ones on the New-England test system elaborate the efficiency of the proposed method from the viewpoint of providing a better transient stability margin with a lower security cost.     

An approach to locational marginal price based zonal congestion management in deregulated electricity market

Congestion of transmission line is a vital issue and its management pose a technical challenge in power system deregulation. Congestion occurs in deregulated electricity market when transmission capacity is not sufficient to simultaneously accommodate all constraints of power transmission through a line. Therefore, to manage congestion, a locational marginal price (LMP) based zonal congestion management approach in a deregulated electricity market has been proposed in this paper. As LMP is an economic indicator and its difference between two buses across a transmission line provides the measure of the degree of congestion, therefore, it is efficiently and reliably used in deregulated electricity market for congestion management. This paper utilizes the difference of LMP across a transmission line to categorize various congestion zones in the system. After the identification of congestion zones, distributed generation is optimally placed in most congestion sensitive zones using LMP difference in order to manage congestion. The performance of the proposed methodology has been tested on the IEEE 14-bus system and IEEE 57-bus system.     

A proposed market power monitoring model for restructuringelectricity markets

This paper presents a market power monitoring model for electricity markets. It is a social welfare maximization model subject to nonnegative short-term profit constraints. Traditional economics claims that market power exists whenever the price is above the corresponding marginal cost. However, this paper argues that a generator cannot be considered to be exercising any market power if it earns zero profit considering only variable cost     

An energy management approach for renewable energy integration with power generation and water desalination

The share of the renewable energy sources (RES) in the global electricity market is substantially increasing as a result of the commitment of many countries to increase the contribution of the RES to their energy mix. However, the integration of RES in the electricity grid increases the complexity of the grid management due to the variability and the intermittent nature of these energy sources. Energy storage solutions such as batteries offer either short-term storage that is not sufficient or longer period storage that is significantly expensive. This paper introduces an energy management approach which can be applied in the case of power and desalinated water generation. The approach is based on mathematical optimization model which accounts for random variations in demands and energy supply. The approach allows using desalination plants as a deferrable load to mitigate for the variability of the renewable energy supply and water and/or electricity demands. A mathematical linear programming model is developed to show the applicability of this idea and its effectiveness in reducing the impact of the uncertainty in the environment. The model is solved for the real world case of Saudi Arabia. The optimal solution accounts for random variations in the renewable energy supply and water and/or electricity demands while minimizing the total costs for generating water and power.     

Grid integration of intermittent renewable energy sources using price-responsive plug-in electric vehicles

Plug-in electric vehicles (PEVs) are expected to balance the fluctuation of renewable energy sources (RES). To investigate the contribution of PEVs, the availability of mobile battery storage and the control mechanism for load management are crucial. This study therefore combined the following: a stochastic model to determine mobility behavior, an optimization model to minimize vehicle charging costs and an agent-based electricity market equilibrium model to estimate variable electricity prices. The variable electricity prices are calculated based on marginal generation costs. Hence, because of the merit order effect, the electricity prices provide incentives to consume electricity when the supply of renewable generation is high. Depending on the price signals and mobility behavior, PEVs calculate a cost minimizing charging schedule and therefore balance the fluctuation of RES. The analysis shows that it is possible to limit the peak load using the applied control mechanism. The contribution of PEVs to improving the integration of intermittent renewable power generation into the grid depends on the characteristic of the RES generation profile. For the German 2030 scenario used here, the negative residual load was reduced by 15–22% and the additional consumption of negative residual load was between 34 and 52%.     

Measuring the competitiveness benefits of a transmission investment policy: The case of the Alberta electricity market

Transmission expansions can increase the extent of competition faced by wholesale electricity suppliers with the ability to exercise unilateral market power. This can cause them to submit offer curves closer to their marginal cost curves, which sets market-clearing prices closer to competitive benchmark price levels. These lower wholesale market-clearing prices are the competitiveness benefit consumers realize from the transmission expansion. This paper quantifies empirically the competitiveness benefits of a transmission expansion policy that causes strategic suppliers to expect no transmission congestion. Using hourly generation-unit level offer, output, market-clearing price and congestion data from the Alberta wholesale electricity market from January 1, 2009 to July 31, 2013, an upper and lower bound on the hourly consumer competitiveness benefits of this transmission policy is computed. Both of these competitiveness benefits measures are economically significant, which argues for including them in transmission planning processes for wholesale electricity markets to ensure that all transmission expansions with positive net benefits to electricity consumers are undertaken.     

Large-scale integration of optimal combinations of PV, wind and wave power into the electricity supply

This article presents the results of analyses of large-scale integration of wind power, photo voltaic (PV) and wave power into a Danish reference energy system. The possibility of integrating Renewable Energy Sources (RES) into the electricity supply is expressed in terms of the ability to avoid excess electricity production. The different sources are analysed in the range of an electricity production from 0 to 100% of the electricity demand. The excess production is found from detailed energy system analyses on the computer model EnergyPLAN. The analyses have taken into account that certain ancillary services are needed in order to secure the electricity supply system.The idea is to benefit from the different patterns in the fluctuations of different renewable sources. And the purpose is to identify optimal mixtures from a technical point of view. The optimal mixture seems to be when onshore wind power produces approximately 50% of the total electricity production from RES. Meanwhile, the mixture between PV and wave power seems to depend on the total amount of electricity production from RES. When the total RES input is below 20% of demand, PV should cover 40% and wave power only 10%. When the total input is above 80% of demand, PV should cover 20% and wave power 30%. Meanwhile the combination of different sources is alone far from a solution to large-scale integration of fluctuating resources. This measure is to be seen in combination with other measures such as investment in flexible energy supply and demand systems and the integration of the transport sector.     

The effect of counter-trading on competition in electricity markets

In a competitive electricity market, nodal pricing is the most efficient way to manage congestion. Counter-trading is inefficient as it gives the wrong long term signals for entry and exit of power plants. However, in a non-competitive market, additional entry will improve the competitiveness of the market, and will increase social benefit by reducing price–cost margins. This paper studies whether the potential pro-competitive entry effects could make counter-trading more efficient than nodal pricing. We find that this is unlikely to be the case, and expect counter-trading to have a negative effect on overall welfare. The potential benefits of additional competition (more competitive prices and lower production cost) do not outweigh the distortions (additional investment cost for the entrant, and socialization of the congestion cost to final consumers).     

Towards dynamic security-constrained congestion management in openpower market

Security and reliability are major concerns in the deregulated and unbundled electricity supply industry due to the increased number of market participants and the changing demand patterns. This letter presents an approach and investigates the impact of incorporating dynamic security considerations in an open market environment. It is possible to reschedule the real power generation along with curtailment of real power loads/transactions to make the system dynamically secure after a fault. A conceptually plausible and computationally feasible approach for the solution of this problem has been developed for a system with a mix of pool and contract dispatches     

Optimizing hybrid offshore wind farms for cost-competitive hydrogen production in Germany

Nearly 96% of the world's current hydrogen production comes from fossil-fuel-based sources, contributing to global greenhouse gas emissions. Hydrogen is often discussed as a critical lever in decarbonizing future power systems. Producing hydrogen using unsold offshore wind electricity may offer a low-carbon production pathway and emerging business model. This study investigates whether participating in an ancillary service market is cost competitive for offshore wind-based hydrogen production. It also determines the optimal size of a hydrogen electrolyser relative to an offshore wind farm. Two flexibility strategies for offshore wind farms are developed in this study: an optimal bidding strategy into ancillary service markets for offshore wind farms that build hydrogen production facilities and optimal sizing of Power-to-Hydrogen (PtH) facilities at wind farms. Using empirical European power market and wind generation data, the study finds that offshore-wind based hydrogen must participate in ancillary service markets to generate net positive revenues at current levels of wind generation to become cost competitive in Germany. The estimated carbon abatement cost of “green” hydrogen ranges between 187 EUR/tonCO₂e and 265 EUR/tonCO₂e. Allowing hydrogen producers to receive similar subsidies as offshore wind farms that produce only electricity could facilitate further cost reduction. Utilizing excess and intermittent offshore wind highlights one possible pathway that could achieve increasing returns on greenhouse gas emission reductions due to technological learning in hydrogen production, even under conditions where low power prices make offshore wind less competitive in the European electricity market.     

Cross-border transmission capacity allocation mechanisms in South East Europe

South East Europe (SEE) is moving rapidly toward the creation of a regional electricity market and wholesale electricity market/power exchange that will improve competitive performance and increase liquidity and reliability. We describe the current applied and future possible congestion management methods in Europe including the SEE region. The paper identifies the potential benefits of a regional electricity and cross-border trade within the region and neighboring countries, and concludes with a brief discussion of policy issues.     

A Mixed Integer Linear Programming model of a zonal electricity market with a dominant producer

We consider a liberalized electricity market, divided in zones interconnected by capacitated transmission links, where a large dimensional power producer operates. We introduce a model for determining the optimal bidding strategies of the large dimensional producer, so as to maximize his own market share, while guaranteeing an annual profit target and satisfying technical constraints. The model determines the optimal medium-term resource scheduling and yields the hourly zonal electricity prices, as it includes constraints representing the Market Clearing process. In order to compute the global solution, the complementarity conditions are formulated as mixed integer linear constraints and the revenue terms are expressed by piece-wise linear functions. The model can be used for analyzing the behavior of market prices in electricity markets where a large dimensional producer can exert market power. It can also be used by investors as a simulation tool for evaluating both the impact on the market and the profitability of investment decisions in the zonal electricity market. A case study related to the Italian electricity market is discussed.     

Reactive power market management considering voltage control area reserve and system security

This paper presents a new algorithm to optimize reactive power procurement through commercial transactions considering system voltage security. The proposed algorithm minimizes reactive power provision and transmission loss costs in addition to maximizing system voltage security margin through a multiobjective function. In order to maintain the voltage profile of power system during sever contingencies or due to load uncertainty, all voltage control areas (VCA) of the system are detected and then optimal reactive power reserve is provided for each VCA during the market settlement. A four-stage multiobjective mathematical programming method is proposed to settle the reactive power market. The proposed algorithm has been applied on IEEE-RTS test system. The simulation results show the effectiveness of the proposed algorithm for reactive power market management.     

Long-term cross-border electricity trading model under the background of Global Energy Interconnection

Environmental problems caused by traditional power production and the unbalanced distribution of energy resources and demand limit the development of sustainable societies. A feasible method to optimize the resource allocation has been proposed, and it involves cross-border and cross-regional electricity transactions. However, the uncertainty of renewable energy and the specific features of the cross-border electricity market are key issues which need to be considered in the trading mechanism design. Based on this, this paper sets up a long-term cross-border electricity trading model considering the uncertainty of renewable energy. First, annual transactions are matched according to the declared data of bidders with consideration of cross-border interconnection development benefits, potential benefit risks, and transmission costs. Second, for annual contract decomposition, the model uses the minimum generation cost function with a penalty item for power shortages to allocate electricity to each month. Additionally, the scenario reduction algorithm is combined with the unit commitment to construct a stochastic generation plan. Finally, a case study of the numerical results for the multinational electricity market in northeast Asia is used to show that the proposed trading model is feasible for cross-border electricity trading with high penetration of renewable energy.     

Financial optimization in the Turkish electricity market: Markowitz's mean-variance approach

Electricity constitutes the input into many products that produced by industry and used by people. Hence, it can be considered as a product or service that has vital importance in human life and economy. Since it has such special properties of instantaneous production and consumption obligation and unfeasible storage, electricity market is not like other markets. In a competitive electricity market, generation company faces price risks and delivery risks. So that risk management is an important part of a generation company and can deeply effect companies’ profitability. This paper focuses on electricity generation asset allocation between bilateral contracts, such as forward contracts, and daily spot market, considering constraints of generating units and spot price risks. The problem is to find the optimal portfolio based on known electricity generation total costs, bilateral contract prices, it employed Turkish historical balanced market hourly system marginal and day-ahead hourly market prices between of 2006 and 2011. There are limited studies about portfolio optimization in electricity markets in literature and this paper should be considered frontier study taking spot market's hourly prices separately as risky assets. Markowitz mean-variance optimization which is claimed to be the beginning of modern portfolio theory in financial sector is used to demonstrate this approach. Mean-variance optimization has been successfully applied to all cases that modeled for electricity market. Some suggestions for future work are also listed in this paper.     

Two-stage stochastic-based scheduling of multi-energy microgrids with electric and hydrogen vehicles charging stations,considering transactions through pool market and bilateral contracts

In order to mitigate greenhouse gas emissions and improve energy efficiency, sustainable energy systems such as multi-energy microgrids (MEMGs) with the high penetration of renewable energy resources (RES) and satisfying different energy needs of consumers have received significant attention in recent years. MEMGs, by relying on renewable resources and energy storage systems along with energy conversion systems, play an essential role in sustainability of energy supply. However, renewable energies are uncertain due to the intermittent nature of solar and wind energy sources. Thus, optimal operation of the MEMGs with the consideration of the uncertainties of RES is necessary to achieve sustainability. In this paper, risk constrained scheduling of a MEMG is carried out with the presence of the PV, wind, biomass, electric vehicles (EVs) and hydrogen vehicles (HVs) charging stations, combined heat and power (CHP), boiler, hydrogen electrolyzer (HE), cryptocurrency miners (CMs), electrical, thermal and hydrogen storage systems, responsive demands. From the trading and business model side, the proposed MEMG optimized operation relies on bilateral contracts between producers and consumers and pool electricity markets. A two-stage stochastic programming method is used for considering the uncertainties of electrical, thermal and hydrogen demands, EV and HV charging stations load, CM load, PV and wind power, and the price of electricity purchased from the pool market. The proposed mixed integer linear programming (MILP) model is solved using the CPLEX solver in GAMS which guarantees to achieve a globally optimal solution. The results show that due to the certain prices of bilateral contracts, the possibility of transaction by bilateral contracts decreases the risk metric CVaR by 50.42%. The simulation results demonstrate that risk of high operation costs while considering flexibility sources, such as storages and demand response (DR) programs, is decreased by 5.45% and 4.6%, respectively. As far as operation costs are concerned, results reveal that using renewable resources decreases operation costs by 34.47%. Moreover, the operation cost is reduced by 5.94% and 4.57% in the presence of storage units and DR programs, respectively. In the same way, storages and DR programs decrease cost of purchased electricity by 13.47% and 14.46%, respectively.     

适应能源互联网多主体合作共享的区块链交易平台

随着售电侧的放开,配电网中接入了大规模小容量的分布式发电单元,形成了如微电网、综合能源服务商和虚拟电厂等多类型市场主体.由于分布式能源大规模接入,能源互联网下的能源市场与传统的输电网也有所区别,正朝着主体多元化、结构扁平化、商品多样化的方向发展,最终形成多方的竞争性市场机制和灵活性市场环境.因此针对上述背景,本文分析了...     

Electricity pricing under “carbon emissions trading”: A dominant firm with competitive fringe model

The aim of this paper is to analyze the impact of trading of CO₂ emissions allowances on electricity pricing in the short run. We mainly refer to the European Emissions Trading Scheme (ETS) and are interested in understanding the role of electricity market structures. We carry out a simple analytical model useful to verify whether (and under which conditions) the impact of the ETS under market power could be lower (or higher) than that under perfect competition. We analyze a context where generators compete in a uniform, first price auction. Market power in the form of a dominant firm facing a competitive fringe model is assumed. The paper highlights that the marginal CO₂ opportunity costs are fully included in energy prices when the electricity market is perfectly competitive. Under market power the impact of the ETS equals or exceeds that under the competitive scenario only when there is excess capacity and the share of most polluting plants in the market is low enough. Otherwise, the impact under market power is less than under perfect competition and significantly decreases in the degree of market concentration. This especially occurs when there is not high excess capacity and regardless of either the plant mix or the allowance price. In this case, moreover, the marginal pass-through rate is lower in the peak than in the off-peak hours and can be even nil if the degree of market concentration is high enough.