Generation Adequacy Research Articles

Adequacy aware long-term energy-system optimization models considering stochastic peak demand

An important aspect of long-term power system planning models is their adequacy awareness, i.e., their ability to ensure generation adequacy in the final solution, which in turn strongly depends on the level of temporal detail included in the model structure. To maintain computational tractability, the temporal detail included in long-term planning models is, however, often limited, which decreases their adequacy awareness resulting in inadequate capacity mixes. To compensate for this, several adequacy-improving measures can be taken. The aim of this paper is to investigate the performance of three of these measures, namely (i) adding a traditional static planning reserve margin (PRM) constraint, (ii) adding a dynamic PRM constraint and (iii) a novel approach that increases the level of temporal detail with which critical peak periods are modeled. To this end, we compare each of these three adequacy methods in a long-term planning exercise based on (i) total system costs, (ii) adequacy of the resulting capacity mix and (iii) technology choices. Our results suggest that the novel approach more effectively increases the adequacy of the obtained capacity mix, resulting in lower total system costs and less technology biases. Also the dynamic PRM approach performs well, although occasional inadequacies can occur in individual milestone years due to exogenously imposed capacity credits.

Systematic comparison of high-resolution electricity system modeling approaches focusing on investment, dispatch and generation adequacy

The transparency and open availability of energy system models and their input data are of particular importance due to their increasing complexity and policy relevance. In recent years, a large number of model-based scenario analyses have been carried out. These analyses are based on diverse model approaches and lead to a rather broad range of results, which due to different data structures and mathematical approaches are hardly directly comparable. In this paper, detailed and harmonized scenario input parameters are the basis of a systematic model experiment including four electricity system models. In the following, the different model approaches are classified and their respective results are discussed transparently. Consequently, differences in results can be interlinked directly with model properties. The results are compared focusing on a selection of output parameters, such as investment and dispatch decisions in flexible power plants, storage dispatch, wholesale electricity prices, CO2 emissions and generation adequacy in hours with critical supply situations in Germany until 2030. Differences in the results are traced back to conceptual differences as the models can be distinguished not only with regard to their mathematical approaches, but also to their level of detail. Results indicate that next to the differences of the mathematical approaches (i.e., linear optimization vs. agent-based simulation), the myopic foresight perspective (e.g., rolling planning algorithm with 24- and 36-hours loops vs. perfect foresight in a closed loop for one year) are decisive for the range of obtained results.

Reliability assessment of island multi‐energy microgrids

Multi-energy microgrids could result in more flexibility and increase reliability by interconnecting networks. Electricity and gas networks exhibit very different dynamic behaviours in response to a fault or failure. Gas networks have built-in energy storages that can continue to provide a reliable supply if gas inputs to the system are compromised. This study presents a novel reliability assessment method applied to multi-energy microgrids; the method combines an incidence matrix analysis that identifies the connectivity between sources and load points with a sequential Monte Carlo simulation and generation adequacy evaluation. A case study is conducted by using an electricity-gas microgrid. The electricity network is a multi-sourced grid, whereas the gas network is supplied by a biogas plant. The linepack (gas stored along the pipelines) is modelled to account for the slower gas dynamics. The proposed method is evaluated on a real-world electricity distribution network in Austria. The results indicate the reliability benefits of forming a multi-energy microgrid.

Research on Reliability of Grid Connected Photovoltaic Renewable Generation System

Renewable energy sources are increasingly being implemented in power systems to curb global warming and improve generation adequacy. These renewable sources include Hydro, wind, tidal, and solar power systems. Since Pakistan experiences decent solar irradiation throughout the year, the most viable renewable energy option is photovoltaic generation. Before solar systems are implemented, the proposed design is first simulated using design software such as MATLAB-Simulink to correct and adjust parameters to attain the DC voltage and current through the irradiation and environment temperature. Reliability studies and analysis are performed on the simulated systems to ascertain the success and long life before the system components’ failure. In this thesis, the grid-connected PV system’s reliability model established based on the reliability block diagram method using the MIL-HDBK-217F handbook. The handbook provides the methodology of calculating failure rates of specific physical electronics operations. The mean time to failure (MTTF) and Mean time to repair (MTTR) of the system is calculated from the overall system reliability. Photovoltaic power output varies greatly, and it is dependent on solar irradiation and temperature, resulting in intermittent and variable energy production. All of these considerations have a significant effect on the entire system adequacy of the power generation system. This study uses a probabilistic analytical methodology to develop comprehensive reliability models of grid-connected Photovoltaic generation systems.

Impact of capacity mechanisms and demand elasticity on generation adequacy with risk-averse generation companies

While on-going and future developments will likely increase the short-term elasticity of the electricity demand, capacity markets are often put forward as a possible remedy to ensure generation adequacy. In this paper, we provide a model formulation of a stochastic non-cooperative capacity planning problem reflecting short-term elastic energy demand, risk-averse investors, and a capacity market. The Conditional-Value-At-Risk is used as a coherent risk-measure. For solving the model, we deploy an Alternating Direction Method of Multipliers. We analyze the impact of short-term demand elasticity on the social welfare, agents’ surpluses, and Loss-of-Load-Expectation of an energy-only market and a market complemented by a capacity market. Moreover, we consider the impact of set capacity targets. For the energy-only market, we show that short-term demand elasticity even amplifies the negative effect of risk aversion on social welfare. A capacity market can be used to hedge against the negative effects of risk aversion, even if the capacity target is not set ideally. Furthermore, we show that a capacity market can be used to mitigate welfare transfer to investors and lower the loss-of-load-expectation induced by scarcity times.

Моделювання розвитку електроенергетичної системи України для обґрунтування Другого національно визначеного внеску щодо обмеження викидів парникових газів

Ukraine is obligated to adopt Nationally Determined Contribution to the Paris Agreement (NDC2) in 2021 for a period up to 2030 as a percent of 1990, requiring correct projection of green-houses gases (GHG) emissions first of all in key categories, one of that is heat and electricity production by thermal power plants (TPP) and combined heat and electricity production (CHP) which are burning organic fuel. The Ministry of environment protection and natural resources of Ukraine (MEP) proposed GHG reduction of 65% compared to 1990 which is about 3.2% lower compared to 2018, and there is a very ambitious goal taking into account desired rapid Ukrainian economic growth. To assess the reliability of this proposal the appropriate modeling GHG emission reduction from TPP and CHP was made and presented in the article. The modelling was made taking into account methodological approaches of TIMES-Ukraine modeling system, which is the basic tool for assessment of GHG reduction potential in Ukraine for MEP, and also alternative one used in BACS-RVE modeling tool, which was used for calculations for "Generation Adequacy report" which was developed by Ukrainian transmission system operator "Ukrenergo". The analysis of the modeling results showed that neglecting in the methodology used in TIMES-Ukraine the operation modes of generation and required levels of power grid balance reliability indicators does not allow fully adequately project power system development. The modeling results using BACS-RVE modeling tool showed that the reference case scenario of generation development (according to the TIMES-Ukraine) could be feasible under the condition that GHG emission tax should not be less than 100 EUR per tonne of CO2eqv, and potentially will cause the increase of electricity price. Another important result obtained using BACS-RVE is that GHG emission level for 2030 is higher compared to the reference case scenario, hence additional modeling and discussion of results are required to ensure well-grounded GHG emission projection which will allow reviewing NDC obligation for the power sector of Ukraine. Keywords: power system, greenhouse gases, modeling, load profiles, grid balance reliability

Renewable Energy Integration in Vietnam’s Power System: Generation Adequacy Assessment and Strategic Implications

Vietnam is widely considered as an energy-intensive economy. Renewable energy integration has been set as an important goal in the country’s revised Power Development Plan 7 (PDP7). This study first conducted a generation adequacy assessment using the basic probabilistic modeling approach to evaluate how the generation fleet, as foreseen in the PDP7, can meet the demand, despite the fast-changing renewable energy sources (RES) generation. The adequacy of the generation was measured using the Loss of Load Expectation (LOLE, expressed in hours) index. The study then conducted in-depth interviews with key stakeholders to identify and propose efficient strategic approach and policy implementations for integration of RES into the current power system in Vietnam. The results suggested that three major pillars should be considered to ensure the success of RES integration: strategic objectives, structural reforms and system transformation.

Optimal strategy for energy allocation and bidding decision of generators considering generation adequacy

The goal of China’s new round of electricity market reform is to orderly release the plan of power generation and power utilization and gradually expand the scale of market-oriented transactions. The generation adequacy is an indicator that needs to be paid attention to during releasing the plan of power generation and power utilization. Insufficient generation adequacy will result in market monopoly and high market-clearing prices. Given this background, the market power and bidding strategies of generators under the low and high generation adequacy are analyzed in this paper. Then, a synthetic decision model for the energy allocation between bilateral contracts and a pool market and the bidding strategy in the pool market is constructed considering the generation adequacy. Case studies are performed for demonstrating the decision-making model and simulation results show that the proposed model can assist generators to make energy allocation and bidding decision based on the generation adequacy, own power generation capacity and bilateral contract prices, and can provide guidance for market operation agencies to gradually release the plan of power generation and power utilization.

Joint assessment of generation adequacy with intermittent renewables and hydro storage: A case study in Finland

Large-scale entry of intermittent renewables needs to be balanced with a source of flexibility to retain generation adequacy. Storage offers such flexibility but sufficient capacities are currently available only indirectly via hydropower reservoirs. Yet hydropower is not insulated from adequacy concerns because reservoir levels also depend on the weather. This paper shows how to estimate the availability of intermittent renewables and long-term hydro storage from historic data with the use of modern regression techniques. The novelty of the paper is to introduce a robust methodology to add the estimated availability distributions directly to the computationally light and transparent recursive convolution approach; and the principles extend to other computational methods. An application to the Finnish power system makes it clear how both the short-term availability shocks from intermittent renewables and the long-term shocks from hydropower availability should be properly accounted for to avoid misguided generation adequacy estimates.

Chance Constraints Optimal Planning Strategy of Energy Storage Systems and Tie-Lines under Wind Power Uncertainties to Improve the Reliability

The energy storage devices and renewable energy integration have great impacts on modern power system. The optimal site selection and network expansion under several uncertainties, however, are the challenging tasks in modern interconnected power system. This paper proposes a robust optimal planning strategy to find the location and the size of the energy storage system (ESS) among the power network buses and transmission lines expansion to accommodate the wind power energy integration to serve the future demand growth under uncertainties. The proposed methodology provides the optimal location concerning the required size of ESS at each bus, along with the optimal selections to reinforce existing lines or recommending new ones in a single solving stage. The co-optimization problem is formulated as a mixed-integer linear programming problem, in which the power balance constraint is developed as an optimal power flow. The stochastic optimization problem is solved robustly using the chance-constrained method. Furthermore, the load shedding and wind curtailment are taken into account in the cost function. The methodology is tested in the IEEE RTS-96 system. The simulation results demonstrate the effectiveness of the proposed strategy to find optimal size and location of ESS. The optimal candidates and transfer capacity for the tie-lines expansion planning are also determined. The results are found using different confidence levels to assess the optimality when the confidence level changes. The primary generation adequacy indices are evaluated to highlight the effectiveness of the proposed methodology. The optimally sized batteries allocated in the optimally selected locations around the system enhance the system’s performance economically and reliably.

The Variation in Capacity Remunerations Requirements in European Electricity Markets

This paper provides the first EU wide analysis of the variation in Capacity Remuneration Requirements throughout Europe which aim to resolve the “missing money” problems in various member states. The findings of this analysis point to an asymmetric investment case for gas-fired peaking power plants throughout the EU. Under the assumptions of the European Commission Reference Scenario, pan-European power optimisation and investment models are specified for 2030. The results show that future investment in gas generators will depend on the availability of capacity payments. Capacity remuneration mechanisms can provide this “missing money,” but we show that capacity remuneration requirements vary considerably across countries. We consider and model the impacts of country specific climate policy targets, sovereign risk, capital allowances, corporate taxes and future gas network tariffs on investor returns and therefore remuneration requirements. In the context of harmonised energy trading, this raises questions of how generation adequacy should be achieved, particularly in the context of higher penetrations of renewables.

Cross-border Effects of Capacity Remuneration Mechanisms: The Swiss Case

In this article, cross-border effects of different market design options are analyzed using Switzerland, which is strongly interconnected to larger neighboring markets, as a case study. An investigation is conducted with an agent-based model where in one scenario, all market designs are represented according to the current legislation, and in another, energy-only markets (EOM) are assumed in all considered countries. The results show that wholesale electricity prices are highly dependent on the chosen market design and in the annual average are up to 27% higher in the EOM scenario. Due to expected larger interconnector capacities, this increase is evident in all simulated markets. Furthermore, the results indicate that the planned market design changes in the neighboring countries decrease investments in Switzerland. However, generation adequacy is still guaranteed due to the high Swiss hydropower storage capacity. Our results suggest that, under the current circumstances, a domestic mechanism in Switzerland is not required.

On the role of electricity storage in capacity remuneration mechanisms

In electricity markets around the world, the substantial increase of intermittent renewable electricity generation has intensified concerns about generation adequacy, ultimately driving the implementation of capacity remuneration mechanisms. Although formally technology-neutral, substantial barriers often exist in these mechanisms for non-conventional capacity such as electricity storage. In this article, we provide a rigorous theoretical discussion on design parameters and show that the concrete design of a capacity remuneration mechanism always creates a bias towards one technology or the other. In particular, we can identify the bundling of capacity auctions with call options and the definition of the storage capacity credit as essential drivers affecting the future technology mix as well as generation adequacy. In order to illustrate and confirm our theoretical findings, we apply an agent-based electricity market model and run a number of simulations. Our results show that electricity storage has a capacity value and should therefore be allowed to participate in any capacity remuneration mechanism. Moreover, we find the implementation of a capacity remuneration mechanism with call options and a strike price to increase the competitiveness of storages against conventional power plants. However, determining the amount of firm capacity an electricity storage unit can provide remains a challenging task.

A probabilistic analysis of power generation adequacy towards a climate-neutral Europe

Over the last decades, the actions aimed to realize an integrated pan-European electricity market brought about profound modifications on the physical, information and communication systems upon which the electricity delivery process occurs. In order to assess some of the techno-economic challenges relating to the single electricity market functioning, including the future needs of electricity, several dispatch models have been developed in recent years in Europe and the rest of the world. In particular, EUPowerDispatch, a minimum cost dispatch model, was originally developed to investigate the need for cross-border transmission investment in Europe. This paper proposes an improved version of EUPowerDispatch that aims at analysing the generation adequacy of the European electricity system in a probabilistic manner. For this purpose, planned and unplanned outages of all single conventional generating units are modelled. The former are optimally and timely allocated while the latter are stochastically generated with chronological Monte Carlo simulations. Data of wind and solar PV production from several meteorological years are accounted for as well as hydro series of run-of-river and natural inflows to the hydro reservoirs. The case study is composed of 33 European countries/regions which are linked through interconnectors. Indexes for the reliability assessment of electric power systems are calculated in order to study the generation adequacy of the European electricity system in 2025.

Coordination of risk-based generation investments in conventional and renewable capacities in oligopolistic electricity markets: A robust regulatory tool

Investment in new generation capacity is considerably affected by issues such as regulatory-determined incentives, techno-economic uncertainties and financial risks. In addition, increased penetration of renewables such as wind capacities resulting in decreased market prices, leads to the augmented risk of investing in conventional generations such as thermal technologies, which may hamper generation adequacy. Thus, to meet regulatory goals for adequacy and environmental considerations, regulators should determine investment incentives considering targets for techno-environmental issues and generation investors’ risks. So, this paper presents a bi-level robust regulatory model, in which regulator in the first level designs incentives considering generation companies’ (GENCOs’) investment response to regulatory decisions. In the second level, a robust game-theoretic model is considered to capture interactions between risk-averse GENCOs, facing uncertainties such as rivals’ behavior and nondispatchable generations. The effectiveness of proposed model is demonstrated by IEEE-RTS and ERCOT test systems and the results are compared with those obtained in the deterministic cases. As the results show, capacity payments and feed-in premiums should be coordinately designed to meet regulatory targets for techno-environmental conditions. Besides, more levels of uncertainties lead to designing more levels of investment incentives with respect to the deterministic case. Moreover, the more is the level of GENCOs’ risk-aversion, the more is the cost of designed incentives for promising regulatory targets considering GENCOs’ risk-hedging.

Designing a regulatory tool for coordinated investment in renewable and conventional generation capacities considering market equilibria

Environmental concerns and energy security issues have led to the rapid growth of renewable capacities in the power sector. With the increase in the penetration of renewables, conventional generations such as thermal technologies have faced the decreased market prices, reduced volume of sold energies and thus diminished revenues. The decrease in the interests for investment in conventional capacities resulting from revenue deficiency from one side and high penetration of non-dispatchable renewables such as wind and solar generations from the other side may hinder the generation adequacy. So, the investment in conventional and renewable capacities should be done in a coordinated manner to meet both adequacy and environmental goals. Thus, the present study is conducted to present a regulatory tool for coordinated incentive design of investment in conventional and renewable generation capacities considering market equilibria. To this aim, a bi-level model is proposed where in the first level, regulator determines capacity-based and energy-based incentives paid for conventional and renewable generations, respectively, considering targets for adequacy and environmental issues. In the second level, the investment behavior of generation companies in response to investment incentives is anticipated using a game-theoretic model. Our results show that regulatory targets for adequacy and environmental issues are simultaneously realized by the proposed coordinated incentive design. Besides, cost of the designed incentives considerably reduces compared to the recent works.

Assessing the security of electricity supply through multi-scale modeling: The TIMES-ANTARES linking approach

Long-term energy planning models and dispatch simulations are two key stages in the methodology for a cost-effective transition to a low-carbon power system. Although these stages are equally important, they are often performed independently. This decoupled approach can lead to future investment trajectories decided by long-term energy planning models with no guarantee of a reliable electricity supply.To tackle this problem, the aim of this study was to develop a general methodological framework using a multi-model approach to address adequacy requirements in the long term. An automated soft-linking model was used to successively:i.Plan the optimal power generation mix to satisfy a given level of future expected electricity demand subject to various constraints using the TIMES framework (The Integrated MARKAL–EFOM System).ii.Assess the adequacy of the obtained power generation mix under several climatic and operational future states using the probabilistic operational open-source model ANTARES (A New Tool for the generation Adequacy Reporting of Electric Systems).iii.Implement iterative feedback loops based on the estimated ability of different generating technologies to support peak demand (capacity credit) to ensure a total firm capacity in line with the electricity supply criterion.This methodology was applied to a case study of power generation planning in France for the period 2013–2050. The results show that using TIMES alone provides a power generation mix for 2030 that risks insufficient supply levels. On the other hand, activating iterative feedback loops over capacity-credit exogenous parametershas the potential to ensure both the economic effectiveness of the mix and the security of the electricity supply criterion set by the French public authorities.

Generation expansion planning under correlated uncertainty of mass penetration renewable energy sources

This study presents a methodology for generation expansion planning (GEP) under the presence of uncertainty of multiple renewable energy sources (RES). Both long- and short-term uncertainties are represented and incorporated within the proposed GEP model. The long-term RES uncertainty is simulated by the annual variation of the capacity credit. The short-term uncertainty is modelled by means of the net power based on the hourly variation of RES output power and load curve. The proposed GEP model is solved through three steps. In the first step, the proposed robust GEP model is solved considering the long-term uncertainty of the multiple RES. Short-term uncertainty is considered when solving the GEP model in the second step. In the last step, the robustness of the obtained robust GEP model results is verified by checking the reliability criteria. A new correlated polyhedral uncertainty set is introduced considering the correlation between the different RES uncertain coefficients through its correlation matrix. Different GEP results are presented for different uncertainty scenarios. The results demonstrate that considering the correlation among uncertain coefficients provides insight for effects of correlation on investment strategies. Reserve margin is adapted to cope with uncertainty impact. Reliability criteria are verified by DIgSILENT generation adequacy tool.

Assessment of generation adequacy by modeling a joint probability distribution model

The socio-politically motivated energy transition leads to expansion of renewable energy power plants (REPP) and simultaneous shutdowns of conventional power plants. As the electric load always needs to be balanced by sufficient generation and the energy production by REPP cannot be steered adequate to the demand but depends on weather situations, new methods are needed to assess generation adequacy. These results could be used afterwards to define measures to ensure reliable energy supply.To evaluate the generation adequacy a joint probability distribution model is proposed. It models the dependencies of weather characteristics, the electrical load and unavailabilities of conventional power plants using pair-copula constructions. The model is, then, applied to determine the probability of generation imbalance. The implementation is shown for Germany in the scenario year 2030.

A Novel Model for VPP to Participate in Capacity Market Auction

With the development of intermittent renewable energy, power system needs more capacity resources to ensure the generation adequacy during peak load periods. Flexible resources such as electric vehicles(EVs) and demand response resources(DRRs) will play important roles in the capacity market auction. However, due to the uncertainty of outputs, they are not competitive enough in the market and face high investment risks. In order to deal with this situation, we integrate renewable energy resources(RESs), EVs and DRRs into a virtual power plant (VPP) and proposed a novel auction model for the VPP to participate in the capacity market. The objective function is to maximize the social welfare while satisfying the reliability of the system. This paper also presents the results of a case study with three scenarios to prove the validity. The proposed model provides a novel path for distributed flexible resources to participate in capacity market.