傳統的電力供給規劃模型未考量發電成本之風險，在成本最小化目標下進行不同發電技術選擇，但近年來化石燃料的價格波動顯著，利用傳統方法可能使規劃結果偏好使用化石燃料的發電技術，而低估再生能源趨避化石燃料價格波動風險之效益，此對於高度仰賴進口能源的國家(如：台灣)並不合適；再者，近年再生能源技術進步顯著使其發電成本降低，因此當電力供給規劃引進再生能源時，其所面對之未來技術發展與成本變化的不確定性比僅考量傳統能源更高；然而再生能源具間歇性(intermittence)對電力系統可能之衝擊，亦須加以考量，因此發展一適合評估再生能源電力之供給規劃模型，實有其必要性。
目前國內應用於評估再生能源的模型，在發電技術的選擇上並未考量發電成本風險，而假定燃料成本穩定並透過折現的方法計算均化發電成本，以進行不同技術之選擇，對高度仰賴進口能源的台灣而言，此方法可能會使模擬結果產生偏誤。此外，缺乏對再生能源技術之詳細刻畫，由於再生能源種類多，各種再生能源利用方式亦不同，應分別考量其技術特性。在技術進步方面，一般假設成本下降率由外生給定，並未考慮因技術進步內生化而造成的成本下降。上述均係國內電力供給規劃模型須再深入研究者。
基此，本研究主要目的係以台灣電力部門為範例，建構考量再生能源特性之電力供給規劃模型。研究中應用數學規劃方法，設定「風險調整後的發電成本現值」最小化為目標，即同時考量發電成本現值最小化與風險(發電成本之變異數)最小化。模型中的發電成本風險主要考量化石燃料價格波動、發電技術進步及設備成本下降等三類風險；同時將再生能源之間歇性產出與減少溫室氣體排放等特性納入模型，並結合電力相關限制式(如：電力供需平衡關係、機組運轉限制、機組累積裝置容量關係、電力尖峰容量限制、發電容量限制、再生能源發電量限制、燃氣機組發電量限制、二氧化碳排放關係、發電技術潛力限制等)，建構電力供給規劃模型。此外，利用此模型進行情境模擬分析，評估在考量發電成本風險、二氧化碳減量與再生能源間歇性情境下，再生能源裝置容量配比之變化及其對發電成本、二氧化碳排放量之影響，並提出政策建議，以供電力部門未來規劃之參考。
模擬結果顯示再生能源具有趨避風險及降低二氧化碳排放之效益，能取代化石燃料以降低發電成本之風險與二氧化碳排放量。因此當風險趨避程度越大或減量目標越高時，都會使再生能源裝置容量佔比提高，同時也會提前新增裝置容量以取代化石燃料技術。但因其開發潛力有侷限性，即使在高風險趨避程度下，模擬結果顯示再生能源之總裝置容量佔比亦不會超過15%。未來須能有效提高能源密度(如：增加風機單機容量、太陽光電板效率)，才可提高發展上限，並進一步取代化石能源。
分析結果亦顯示核能發電具有燃料價格波動低與降低二氧化碳排放之特性，以減低發電風險的面向及二氧化碳排放而言，增加核能發電佔比允有助於減少化石燃料價格波動之風險及降低二氧化碳排放。此外，在再生能源間歇性方面，因台灣目前風力發電之發展上限僅為3,000 MW，在考量其間歇性後，對電力系統備載容量及總發電成本之影響並不顯著。
本研究建構之理論模型係將投資組合理論與傳統電力供給規劃模型整合，納入投資組合理論中風險之概念，亦結合傳統電力規劃模型之設定(如：機組運轉特性、電力負載區分、操作容量、發電量、燃料耗用量、二氧化碳排放量與發電技術潛力限制等)。模型除可考量發電成本風險外，因同時整合傳統電力供給規劃模型，故可使規劃結果兼顧發電技術之負載特性與操作限制。

The conventional approach to electricity planning uses the least-cost method to select from a range of alternative technologies without assessing cost-related risks. The results inherently are biased in favor of fossil fuel generating technology. Recent fossil fuel price volatility underlines the potential benefit of including renewable energy sources in the generating portfolio. Furthermore, rapid technological progress has significantly reduced the cost of renewable energy. When renewable energies are introduced into electricity supply planning, the uncertainties associated with the decline in cost and technological development increase. Additionally, the impact of the intermittent characteristics of renewable energy on a power system must be considered. Hence, it is desirable to formulate an adequate electricity supply planning model to evaluate the issue of renewable energy.
Current models for evaluating renewable energy in Taiwan select from a range of generating technologies without assessing cost-related risks. These models do not enable renewable energy to be described in detail. Since the various forms of renewable energy are used in different ways, the model should consider each renewable energy technology separately. Cost reductions associated with technological progress are exogenous in these models. In summary, the current models in Taiwan are inaccurate in determining the selection of renewable power generation technologies.
This study applies portfolio theory in conventional electricity planning with Taiwan as a case study. The overall objective of the model is to minimize the “risk-weighted present value of total generation cost”. This work considers both the present value of generating cost and risk (variance of generating cost). The risk of the generating cost focuses on volatile fuel prices, uncertainty in technological changes and capital cost reduction, as the most important cost volatility determinants in the electricity sector. Some simulation scenarios are also examined to evaluate the impact on the portfolio of power generation technologies and generating cost. Finally, policy suggestions are proposed for Taiwan’s electricity sector based on the simulation results.
The simulation results obtained by applying the model to Taiwan’s electricity sector indicate that incorporating the risk concept and CO2 emission constraints in electricity supply planning model leads to the generation of a lower proportion of electricity from fossil fuel technology and a higher proportion from renewable energy sources. Higher risk-aversion and tighter CO2 emission restrictions are associated with a stronger effect. However, there is an upper bound of 15% on the maximum share of renewable energy in the generating portfolio due to limited renewable development potential in Taiwan. Renewable energy will only play a more important role in electricity generation should its energy density improve in terms of unit capacity and conversion efficiency.
Simulation results also reveal the low fuel price volatility and low CO2 emission associated with nuclear power reduce exposure to price fluctuations associated with fossil fuels and CO2 emissions. Regarding the intermittent nature of renewable energy, since an upper bound of 3000MW is set on wind power, the impact on the reserve margin and total generating cost is not remarkable.
Unlike the current portfolio theory that is applied to the energy market, the model herein integrates portfolio theory into a vintage electricity planning framework. Aside from risk, the model accommodates components of conventional electricity planning, including unit characteristics, load segments, capacity constraints, power output constraints, fuel consumption constraints, CO2 emission constraints and constraints on potential technologies development. The model considers explicitly many characteristics of power generation technologies and the risks that accrue investing in electricity generation.

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