Methodology to analyze combined heat and power plant operation considering electricity reserve market opportunities

Haakana, Juha; Tikka, Ville; Lassila, Jukka; Partanen, Jarmo

doi:10.1016/j.energy.2017.03.134

Cited by 40 publications

(13 citation statements)

References 10 publications

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“…A similar approach is followed by (Haakana, et al, 2017), except that the spot and reserve market in question here are Nord Pool and the Finnish Frequency Containment Reserve (FCR) markets, respectively. Haakana et al also identify opportunities between electricity and reserve markets and argue that reserve provision from CHP bears additional economic potential; however, they also underscore the need for additional flexibility in the heating network such as the availability of heat storages to realize said potentials without risking missing heat delivery obligations.…”

Section: Modelling Of Reserve From Chpmentioning

confidence: 99%

Reserve Provision by CHP Units and Its Impact on Equilibria in Spot and Reserve Markets

Furtwaengler

2018

SSRN Journal

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There is a broad consensus that the energy transition planned in Europe, along with an increasing share of renewable energy sources, demands a sufficient number of flexibility providers. The established flexibility procurement mechanisms, notably the reserve markets, are expected to reflect the cost of flexibility provision. As more flexibility is needed-given a higher resulting uncertainty of residual load levels-prices for such provision are expected to rise. In recent years, however, reserve provision prices in Germany have shown a decreasing tendency, with overall reserve demand remaining constant. This contribution proposes to analyse first the equilibrium pricing of reserve power against the electricity spot market in a stylized setting. A fundamental market model is used to analyse the price effects of reserve flexibility from Combined Heat and Power (CHP) entering both markets, using 2016 data as input. Four cases are analysed to assess the effects of different reserve market characteristics. In Case 1, CHP plants may not provide secondary reserve for the reserve market and a stylized heat demand curve is considered as operating restriction of CHP plants in the spot market. Case 2 allows reserve provision by CHP plants, but models these plants without heat restrictions. Case 3 considers the combination of the stylized heat demand curve and reserve from CHP plants. Case 4 extends Case 3 by 100 small CHP power plant pools, analysing their additional effect on reserve prices. From June 2018 on, secondary reserve in Germany will be auctioned in four-hour tenders, instead of the current weekly peak/off-peak auction design. We therefore compare the results to such an alternative auction regime with the same demand, but four-hour reserve provision tenders to reflect upcoming market design changes. Our approach leads to spot prices at a similar mean level compared to historical data, with MAE values in a range from 5.91-6.64 €/MWh for all cases. The positive reserve price levels in this approach also compare to mean historical price levels. The price lowering effect of flexibility provision from CHP is clearly identifiable, underscoring the importance of explicit modelling of heat demand restrictions. A change of the reserve tender regime towards 4-hour tenders further lowers positive reserve prices in all cases. As a result, low reserve price levels may be expected to persist in the medium term despite the expected increase of intermitting generation.

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Section: Modelling Of Reserve From Chpmentioning

confidence: 99%

Reserve Provision by CHP Units and Its Impact on Equilibria in Spot and Reserve Markets

Furtwaengler

2018

SSRN Journal

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“…Further, there is some work considering provision of multiple services from CHP-based systems. References [28]- [30] all consider the joint provision of energy arbitrage and reserve, although these works either do not consider excess or deficit heat in the event of a reserve call. Considering the wider class of thermostatic loads [31], [32] present a model which is designed to exploit large groups of thermostatic appliances to provide energy arbitrage and reserve.…”

Section: Introductionmentioning

confidence: 99%

Flexibility in Multi-Energy Communities With Electrical and Thermal Storage: A Stochastic, Robust Approach for Multi-Service Demand Response

Good

Mancarella

2019

IEEE Trans. Smart Grid

169

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There is increasing interest in multi-energy communities, which could become important sources of demand response flexibility, especially when equipped with storage. Their location on distribution networks mean their exploitation to solve local capacity congestions may be particularly valuable, whilst their ability to partake in energy/reserve markets can improve their business cases. However, maximizing this flexibility potential by providing multiple services that are subject to uncertain calls is a challenging modeling task. To address this, we present a stochastic energy/reserve mixed integer linear program for a community energy system with consideration of local network constraints. By covering all the relevant energy vectors, the multi-energy formulation allows comprehensive modeling of different flexibility options, namely, multi-energy storage, energy vector substitution, end-service curtailment, and power factor manipulation. A key feature of the approach is its robustness against any reserve call, ensuring that occupant thermal comfort cannot be degraded beyond agreed limits in the event of a call. The approach is demonstrated through a case study that illustrates how the different flexibility options can be used to integrate more electric heat pumps into a capacity constrained smart district that is managed as a community energy system, while maximizing its revenues from multiple markets/services.

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“…At the same time, compared with traditional power-only units and heat-only units, CHP units can save 10%~40% of the cost of generation, which means that less fuels are needed to produce equal amounts of heat and electricity [5]. Furthermore, recent research suggest that CHP units are considered as an environmentally friendly syste m, since the greenhouse gas emissions can be reduced by nearly 13%~18% by making use of cogenerations [6]. 7 CHP economic dispatch (CHPED) has been recognized as an important means to achieve optimal operation for CHP systems, since it is able to significantly reduce the unit energy consumption of coal-fired power plants through optimizing the allocation of thermal and electrical load instructions.…”

Section: Introductionmentioning

confidence: 99%

A two-stage approach for combined heat and power economic emission dispatch: Combining multi-objective optimization with integrated decision making

Wang

Zhao

et al. 2018

Energy

192

108

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To address the problem of combined heat and power economic emission dispatch (CHPEED), a two-stage approach is proposed by combining multi-objective optimization (MOO) with integrated decision making (IDM). First, a practical CHPEED model is built by taking into account power transmission losses and the valve-point loading effects. To solve this model, a two-stage methodology is thereafter proposed.The first stage of this approach relies on the use of a powerful multi-objective evolutionary algorithm, called θ-dominance based evolutionary algorithm (θ-DEA), to find multiple Pareto-optimal solutions of the model. Through fuzzy c-means (FCM) clustering, the second stage separates the obtained Pareto-optimal solutions into different clusters and thereupon identifies the best compromise solutions (BCSs) by assessing the relative projections of the solutions belonging to the same cluster using grey relation projection (GRP). The novelty of this work is in the incorporation of an IDM technique FCM-GRP into CHPEED to automatically determine the BCSs that represent decision makers' different, even conflicting, preferences. The simulation results on three test cases with varied complexity levels verify the effectiveness and superiority of the proposed approach. (Yang Li). 2 multi-objective optimization; integrated decision making; valve-point loading effects; θ-dominance based evolutionary algorithm; grey relational projection; integrated energy system. NOMENCLATURE Acronyms CHP combined heat and power CHPED CHP economic dispatch CHPEED CHP economic emission dispatch MOEAs multi-objective evolutionary algorithms MOPSO multi-objective particle swarm optimization EFA enhanced firefly algorithm MOO multi-objective optimization

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Methodology to analyze combined heat and power plant operation considering electricity reserve market opportunities

Cited by 40 publications

References 10 publications

Reserve Provision by CHP Units and Its Impact on Equilibria in Spot and Reserve Markets

Reserve Provision by CHP Units and Its Impact on Equilibria in Spot and Reserve Markets

Flexibility in Multi-Energy Communities With Electrical and Thermal Storage: A Stochastic, Robust Approach for Multi-Service Demand Response

A two-stage approach for combined heat and power economic emission dispatch: Combining multi-objective optimization with integrated decision making

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